Customized recommendations for production management clusters of North American automatic milking systems.

PubMed

Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte

2016-07-01

Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Metrics and methods for characterizing dairy farm intensification using farm survey data.

PubMed

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul; Gibbons, James

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the "average farm" level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a "Virtual Farm" Concept for Enhancement of Site-Specific IPM.

PubMed

Lux, Slawomir A; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a "virtual farm" concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a "bottom-up ethological" approach and emulates behavior of the "primary IPM actors"-large cohorts of individual insects-within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the "virtual farm" approach-were discussed.

Metrics and methods for characterizing dairy farm intensification using farm survey data

PubMed Central

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the “average farm” level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales. PMID:29742166

Estimating challenge load due to disease outbreaks and other challenges using reproduction records of sows.

PubMed

Mathur, P K; Herrero-Medrano, J M; Alexandri, P; Knol, E F; ten Napel, J; Rashidi, H; Mulder, H A

2014-12-01

A method was developed and tested to estimate challenge load due to disease outbreaks and other challenges in sows using reproduction records. The method was based on reproduction records from a farm with known disease outbreaks. It was assumed that the reduction in weekly reproductive output within a farm is proportional to the magnitude of the challenge. As the challenge increases beyond certain threshold, it is manifested as an outbreak. The reproduction records were divided into 3 datasets. The first dataset called the Training dataset consisted of 57,135 reproduction records from 10,901 sows from 1 farm in Canada with several outbreaks of porcine reproductive and respiratory syndrome (PRRS). The known disease status of sows was regressed on the traits number born alive, number of losses as a combination of still birth and mummified piglets, and number of weaned piglets. The regression coefficients from this analysis were then used as weighting factors for derivation of an index measure called challenge load indicator. These weighting factors were derived with i) a two-step approach using residuals or year-week solutions estimated from a previous step, and ii) a single-step approach using the trait values directly. Two types of models were used for each approach: a logistic regression model and a general additive model. The estimates of challenge load indicator were then compared based on their ability to detect PRRS outbreaks in a Test dataset consisting of records from 65,826 sows from 15 farms in the Netherlands. These farms differed from the Canadian farm with respect to PRRS virus strains, severity and frequency of outbreaks. The single-step approach using a general additive model was best and detected 14 out of the 15 outbreaks. This approach was then further validated using the third dataset consisting of reproduction records of 831,855 sows in 431 farms located in different countries in Europe and America. A total of 41 out of 48 outbreaks detected using data analysis were confirmed based on diagnostic information received from the farms. Among these, 30 outbreaks were due to PRRS while 11 were due to other diseases and challenging conditions. The results suggest that proposed method could be useful for estimation of challenge load and detection of challenge phases such as disease outbreaks.

Farm-level economics of innovative tillage technologies: the case of no-till in the Altai Krai in Russian Siberia.

PubMed

Bavorova, Miroslava; Imamverdiyev, Nizami; Ponkina, Elena

2018-01-01

In the agricultural Altai Krai in Russian Siberia, soil degradation problems are prevalent. Agronomists recommend "reduced tillage systems," especially no-till, as a sustainable way to cultivate land that is threatened by soil degradation. In the Altai Krai, less is known about the technologies in practice. In this paper, we provide information on plant cultivation technologies used in the Altai Krai and on selected factors preventing farm managers in this region from adopting no-till technology based on our own quantitative survey conducted across 107 farms in 2015 and 2016. The results of the quantitative survey show that farm managers have high uncertainty regarding the use of no-till technology including its economics. To close this gap, we provide systematic analysis of factors influencing the economy of the plant production systems by using a farm optimization model (linear programming) for a real farm, together with expert estimations. The farm-specific results of the optimization model show that under optimal management and climatic conditions, the expert Modern Canadian no-till technology outperforms the farm min-till technology, but this is not the case for suboptimal conditions with lower yields.

A control-oriented dynamic wind farm flow model: “WFSim”

NASA Astrophysics Data System (ADS)

Boersma, S.; Gebraad, P. M. O.; Vali, M.; Doekemeijer, B. M.; van Wingerden, J. W.

2016-09-01

In this paper, we present and extend the dynamic medium fidelity control-oriented Wind Farm Simulator (WFSim) model. WFSim resolves flow fields in wind farms in a horizontal, two dimensional plane. It is based on the spatially and temporally discretised two dimensional Navier-Stokes equations and the continuity equation and solves for a predefined grid and wind farm topology. The force on the flow field generated by turbines is modelled using actuator disk theory. Sparsity in system matrices is exploited in WFSim, which enables a relatively fast flow field computation. The extensions to WFSim we present in this paper are the inclusion of a wake redirection model, a turbulence model and a linearisation of the nonlinear WFSim model equations. The first is important because it allows us to carry out wake redirection control and simulate situations with an inflow that is misaligned with the rotor plane. The wake redirection model is validated against a theoretical wake centreline known from literature. The second extension makes WFSim more realistic because it accounts for wake recovery. The amount of recovery is validated using a high fidelity simulation model Simulator fOr Wind Farm Applications (SOWFA) for a two turbine test case. Finally, a linearisation is important since it allows the application of more standard analysis, observer and control techniques.

The Research of Computer Aided Farm Machinery Designing Method Based on Ergonomics

NASA Astrophysics Data System (ADS)

Gao, Xiyin; Li, Xinling; Song, Qiang; Zheng, Ying

Along with agricultural economy development, the farm machinery product type Increases gradually, the ergonomics question is also getting more and more prominent. The widespread application of computer aided machinery design makes it possible that farm machinery design is intuitive, flexible and convenient. At present, because the developed computer aided ergonomics software has not suitable human body database, which is needed in view of farm machinery design in China, the farm machinery design have deviation in ergonomics analysis. This article puts forward that using the open database interface procedure in CATIA to establish human body database which aims at the farm machinery design, and reading the human body data to ergonomics module of CATIA can product practical application virtual body, using human posture analysis and human activity analysis module to analysis the ergonomics in farm machinery, thus computer aided farm machinery designing method based on engineering can be realized.

Research on large-scale wind farm modeling

NASA Astrophysics Data System (ADS)

Ma, Longfei; Zhang, Baoqun; Gong, Cheng; Jiao, Ran; Shi, Rui; Chi, Zhongjun; Ding, Yifeng

2017-01-01

Due to intermittent and adulatory properties of wind energy, when large-scale wind farm connected to the grid, it will have much impact on the power system, which is different from traditional power plants. Therefore it is necessary to establish an effective wind farm model to simulate and analyze the influence wind farms have on the grid as well as the transient characteristics of the wind turbines when the grid is at fault. However we must first establish an effective WTGs model. As the doubly-fed VSCF wind turbine has become the mainstream wind turbine model currently, this article first investigates the research progress of doubly-fed VSCF wind turbine, and then describes the detailed building process of the model. After that investigating the common wind farm modeling methods and pointing out the problems encountered. As WAMS is widely used in the power system, which makes online parameter identification of the wind farm model based on off-output characteristics of wind farm be possible, with a focus on interpretation of the new idea of identification-based modeling of large wind farms, which can be realized by two concrete methods.

Modeling small-scale dairy farms in central Mexico using multi-criteria programming.

PubMed

Val-Arreola, D; Kebreab, E; France, J

2006-05-01

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multi-criteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, ryegrass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Organic Farming, Gender, and the Labor Process

ERIC Educational Resources Information Center

Hall, Alan; Mogyorody, Veronika

2007-01-01

This paper seeks to explain variations in gender participation in farm production and decision-making through an analysis of organic farm types, sizes, and orientations. Based on both survey and case study data, the analysis shows that female farmers on vegetable farms and mixed livestock/cash crop farms are more likely to be involved in farm…

Effect of feed-related farm characteristics on relative values of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain.

PubMed

Van Middelaar, C E; Berentsen, P B M; Dijkstra, J; Van Arendonk, J A M; De Boer, I J M

2015-07-01

Breeding has the potential to reduce greenhouse gas (GHG) emissions from dairy farming. Evaluating the effect of a 1-unit change (i.e., 1 genetic standard deviation improvement) in genetic traits on GHG emissions along the chain provides insight into the relative importance of genetic traits to reduce GHG emissions. Relative GHG values of genetic traits, however, might depend on feed-related farm characteristics. The objective of this study was to evaluate the effect of feed-related farm characteristics on GHG values by comparing the values of milk yield and longevity for an efficient farm and a less efficient farm. The less efficient farm did not apply precision feeding and had lower feed production per hectare than the efficient farm. Greenhouse gas values of milk yield and longevity were calculated by using a whole-farm model and 2 different optimization methods. Method 1 optimized farm management before and after a change in genetic trait by maximizing labor income; the effect on GHG emissions (i.e., from production of farm inputs up to the farm gate) was considered a side effect. Method 2 optimized farm management after a change in genetic trait by minimizing GHG emissions per kilogram of milk while maintaining labor income and milk production at least at the level before the change in trait; the effect on labor income was considered a side effect. Based on maximizing labor income (method 1), GHG values of milk yield and longevity were, respectively, 279 and 143kg of CO2 equivalents (CO2e)/unit change per cow per year on the less efficient farm, and 247 and 210kg of CO2e/unit change per cow per year on the efficient farm. Based on minimizing GHG emissions (method 2), GHG values of milk yield and longevity were, respectively, 538 and 563kg of CO2e/unit change per cow per year on the less efficient farm, and 453 and 441kg of CO2e/unit change per cow per year on the efficient farm. Sensitivity analysis showed that, for both methods, the absolute effect of a change in genetic trait depends on model inputs, including prices and emission factors. Substantial changes in relative importance between traits due to a change in model inputs occurred only in case of maximizing labor income. We concluded that assumptions regarding feed-related farm characteristics affect the absolute level of GHG values, as well as the relative importance of traits to reduce emissions when using a method based on maximizing labor income. This is because optimizing farm management based on maximizing labor income does not give any incentive for lowering GHG emissions. When using a method based on minimizing GHG emissions, feed-related farm characteristics affected the absolute level of the GHG values, but the relative importance of the traits scarcely changed: at each level of efficiency, milk yield and longevity were equally important. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

PubMed

Vigre, Håkan; Domingues, Ana Rita Coutinho Calado; Pedersen, Ulrik Bo; Hald, Tine

2016-03-01

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters. © 2016 Society for Risk Analysis.

The Environmental Impact of a Wave Dragon Array Operating in the Black Sea

PubMed Central

Rusu, Eugen

2013-01-01

The present work describes a study related to the influence on the shoreline dynamics of a wave farm consisting of Wave Dragon devices operating in the western side of the Black Sea. Based on historical data analysis of the wave climate, the most relevant environmental conditions that could occur were defined, and for these cases, simulations with SWAN spectral phase averaged wave model were performed. Two situations were considered for the most representative patterns: model simulations without any wave energy converter and simulations considering a wave farm consisting of six Wave Dragon devices. Comparisons of the wave model outputs have been carried out in both geographical and spectral spaces. The results show that although a significant influence appears near the wave farm, this gradually decreases to the coast line level. In order to evaluate the influence of the wave farm on the longshore currents, a nearshore circulation modeling system was used. In relative terms, the longshore current velocities appear to be more sensitive to the presence of the wave farm than the significant wave height. Finally, the possible impact on the marine flora and fauna specific to the target area was also considered and discussed. PMID:23844401

The environmental impact of a Wave Dragon array operating in the Black Sea.

PubMed

Diaconu, Sorin; Rusu, Eugen

2013-01-01

The present work describes a study related to the influence on the shoreline dynamics of a wave farm consisting of Wave Dragon devices operating in the western side of the Black Sea. Based on historical data analysis of the wave climate, the most relevant environmental conditions that could occur were defined, and for these cases, simulations with SWAN spectral phase averaged wave model were performed. Two situations were considered for the most representative patterns: model simulations without any wave energy converter and simulations considering a wave farm consisting of six Wave Dragon devices. Comparisons of the wave model outputs have been carried out in both geographical and spectral spaces. The results show that although a significant influence appears near the wave farm, this gradually decreases to the coast line level. In order to evaluate the influence of the wave farm on the longshore currents, a nearshore circulation modeling system was used. In relative terms, the longshore current velocities appear to be more sensitive to the presence of the wave farm than the significant wave height. Finally, the possible impact on the marine flora and fauna specific to the target area was also considered and discussed.

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

Simulating forage crop production in a northern climate with the Integrated Farm System Model

USDA-ARS?s Scientific Manuscript database

Whole-farm simulation models are useful tools for evaluating the effect of management practices and climate variability on the agro-environmental and economic performance of farms. A few process-based farm-scale models have been developed, but none have been evaluated in a northern region with a sho...

Is farm-related job title an adequate surrogate for pesticide exposure in occupational cancer epidemiology?

PubMed

MacFarlane, E; Glass, D; Fritschi, L

2009-08-01

Accurate assessment of exposure is a key factor in occupational epidemiology but can be problematic, particularly where exposures of interest may be many decades removed from relevant health outcomes. Studies have traditionally relied on crude surrogates of exposure based on job title only, for instance farm-related job title as a surrogate for pesticide exposure. This analysis was based on data collected in Western Australia in 2000-2001. Using a multivariate regression model, we compared expert-assessed likelihood of pesticide exposure based on detailed, individual-specific questionnaire and job specific module interview information with reported farm-related job titles as a surrogate for pesticide exposure. Most (68.8%) jobs with likely pesticide exposure were farm jobs, but 78.3% of farm jobs were assessed as having no likelihood of pesticide exposure. Likely pesticide exposure was more frequent among jobs on crop farms than on livestock farms. Likely pesticide exposure was also more frequent among jobs commenced in more recent decades and jobs of longer duration. Our results suggest that very little misclassification would have resulted from the inverse assumption that all non-farming jobs are not pesticide exposed since only a very small fraction of non-agricultural jobs were likely to have had pesticide exposure. Classification of all farm jobs as pesticide exposed is likely to substantially over-estimate the number of individuals exposed. Our results also suggest that researchers should pay special attention to farm type, length of service and historical period of employment when assessing the likelihood of pesticide exposure in farming jobs.

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

A sample theory-based logic model to improve program development, implementation, and sustainability of Farm to School programs.

PubMed

Ratcliffe, Michelle M

2012-08-01

Farm to School programs hold promise to address childhood obesity. These programs may increase students’ access to healthier foods, increase students’ knowledge of and desire to eat these foods, and increase their consumption of them. Implementing Farm to School programs requires the involvement of multiple people, including nutrition services, educators, and food producers. Because these groups have not traditionally worked together and each has different goals, it is important to demonstrate how Farm to School programs that are designed to decrease childhood obesity may also address others’ objectives, such as academic achievement and economic development. A logic model is an effective tool to help articulate a shared vision for how Farm to School programs may work to accomplish multiple goals. Furthermore, there is evidence that programs based on theory are more likely to be effective at changing individuals’ behaviors. Logic models based on theory may help to explain how a program works, aid in efficient and sustained implementation, and support the development of a coherent evaluation plan. This article presents a sample theory-based logic model for Farm to School programs. The presented logic model is informed by the polytheoretical model for food and garden-based education in school settings (PMFGBE). The logic model has been applied to multiple settings, including Farm to School program development and evaluation in urban and rural school districts. This article also includes a brief discussion on the development of the PMFGBE, a detailed explanation of how Farm to School programs may enhance the curricular, physical, and social learning environments of schools, and suggestions for the applicability of the logic model for practitioners, researchers, and policy makers.

Assessing risk factors in the organic control system: evidence from inspection data in Italy.

PubMed

Zanoli, Raffaele; Gambelli, Danilo; Solfanelli, Francesco

2014-12-01

Certification is an essential feature in organic farming, and it is based on inspections to verify compliance with respect to European Council Regulation-EC Reg. No 834/2007. A risk-based approach to noncompliance that alerts the control bodies to activate planning inspections would contribute to a more efficient and cost-effective certification system. An analysis of factors that can affect the probability of noncompliance in organic farming has thus been developed. This article examines the application of zero-inflated count data models to farm-level panel data from inspection results and sanctions obtained from the Ethical and Environmental Certification Institute, one of the main control bodies in Italy. We tested many a priori hypotheses related to the risk of noncompliance. We find evidence of an important role for past noncompliant behavior in predicting future noncompliance, while farm size and the occurrence of livestock also have roles in an increased probability of noncompliance. We conclude the article proposing that an efficient risk-based inspection system should be designed, weighting up the known probability of occurrence of a given noncompliance according to the severity of its impact. © 2014 Society for Risk Analysis.

A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing

2018-01-01

To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.

Lessons Learned Developing an Extension-Based Training Program for Farm Labor Supervisors

ERIC Educational Resources Information Center

Roka, Fritz M.; Thissen, Carlene A.; Monaghan, Paul F.; Morera, Maria C.; Galindo-Gonzalez, Sebastian; Tovar-Aguilar, Jose Antonio

2017-01-01

This article outlines a four-step model for developing a training program for farm labor supervisors. The model draws on key lessons learned during the development of the University of Florida Institute of Food and Agricultural Sciences Farm Labor Supervisor Training program. The program is designed to educate farm supervisors on farm labor laws…

Cost analysis of immunisation against east coast fever on smallholder dairy farms in Kenya.

PubMed

Muraguri, G R; Mbogo, S K; McHardy, N; Kariuki, D P

1998-03-27

A spreadsheet model was developed and used to estimate the total cost of immunising cattle against East Coast fever (ECF) based on the infection-and-treatment method. Using data from an immunisation trial carried out on 102 calves and yearlings on 64 farms in the Githunguri division, Kiambu district, Kenya, a reference base scenario of a mean herd of five animals, a 10% rate of reaction to immunisation and a 2-day interval monitoring regimen (a total of 10 farm visits) was simulated. Under these conditions, the mean cost of immunisation per animal was US$16.48 (Ksh 955.78); this was equivalent to US$82.39 (Ksh 4778.90) per five-animal farm. A commonly reported reactor rate of 3% would decrease the cost of US$14.63 (Ksh 848.29) per animal. Reducing the number of farm monitoring visits from 10 to 7 would reduce the total cost by 10%, justified if farmers are trained to undertake some of the monitoring work. The fixed costs were 53% of the total cost of immunisation per farm. The cost of immunisation decreased with increasing number of animals per farm, showing economies of scale.

Flow Field Analysis of Fish Farm and Planting Area in Floodplain during Flood

NASA Astrophysics Data System (ADS)

Wu, M.; Tan, H. N.; Lo, W. C.; Tsai, C. T.

2017-12-01

Fish farms constructing and crops planting is common in floodplain in Taiwan. The physiographic soil erosion-deposition (PSED) model was applied to simulate the sediment yield, the runoff, and sediment transport rate of the river watershed corresponding to one-day rainstorms of the return periods of 25, 50, and 100 year. The variation of flow field in the river sections could be simulated by utilizing the alluvial river-movable bed two dimensional (ARMB-2D) model. The results reveal that the tendency of river discharge, sediment deposition and erosion obtained from these two models is agreeable by calibration and verification. The water flow affected by fish farms and planting areas in floodplain during flood was analyzed. Lastly, based on the simulation results obtained from the PESD and ARMB-2D models for one-day rainstorms of the return periods of 25, 50, and 100 year, the illegal fish farms and planting area with severe variations of river flow and affected he capability for flood conveyance will be referred to as the demolishing-to-be areas. We could also suggest the management strategy of application for fish farms constructing and crops planting in river areas by incorporating the ability of our model to provide information of river flow to enhance the flood conveyance.

An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

NASA Astrophysics Data System (ADS)

Mittelmeier, N.; Blodau, T.; Steinfeld, G.; Rott, A.; Kühn, M.

2016-09-01

Atmospheric conditions have a clear influence on wake effects. Stability classification is usually based on wind speed, turbulence intensity, shear and temperature gradients measured partly at met masts, buoys or LiDARs. The objective of this paper is to find a classification for stability based on wind turbine Supervisory Control and Data Acquisition (SCADA) measurements in order to fit engineering wake models better to the current ambient conditions. Two offshore wind farms with met masts have been used to establish a correlation between met mast stability classification and new aggregated statistical signals based on multiple measurement devices. The significance of these new signals on power production is demonstrated for two wind farms with met masts and validated against data from one further wind farm without a met mast. We found a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity when the wind turbines were operating in partial load.

SD simulation study on degraded farmland policy on farming-pastoral area under the constrains of water resources-Taking Tongliao City of Inner Mongolia as example

NASA Astrophysics Data System (ADS)

Xu, D. P.; Zhao, B.; Li, T. S.; Zhu, J. W.; Yu, M. M.

2017-08-01

Water resources are the primary factor in restricting the sustainable development of farming-pastoral regions. To support the sustainable development of water resources, whether or not the land uses patterns of farming-pastoral areas is a reasonably important issue. This paper takes Tongliao city as example for the purpose of sustainably developing the farming-pastoral area in the north. Several scientific preductions and evaluations were conducted to study the farming-pastoral landuse pattern, which is the key problem that effects sustainable development of farming-pastoral areas. The paper then proposes that 1:7 landuse pattern is suitable for the sustainable development of farming-pastotal area. Based on the analysis of the research findings on sustainable development of farming-pastoral area, the paper established a suitability evaluation indicators system of degraded farmland policies in Tongliao city, and used an Analytical Hierarchy Process (AHP) method to determine the weight to run system dynamic (SD) model. The simulation results were then obtained on social economic ecological development in Tongliao city under different degraded farmland policies, and used the comprehensive evaluation model to optimize the results. It is concluded that stabilizing the policy of degraded farmland policy is the preferential policy in Tongliao, which provides useful theoretical research for the sustainable development of farming-pastoral area.

Economic analysis of wind-powered farmhouse and farm building heating systems

NASA Astrophysics Data System (ADS)

Stafford, R. W.; Greeb, F. J.; Smith, M. H.; Deschenes, C.; Weaver, N. L.

1981-01-01

The break even values of wind energy for selected farmhouses and farm buildings focusing on the effects of thermal storage on the use of WECS production were evaluated. Farmhouse structural models include three types derived from a national survey: an older, a more modern, and a passive solar structure. The eight farm building applications include: (1) poultry layers; (2) poultry brooding/layers; (3) poultry broilers; (4) poultry turkeys; (5) swine farrowing; (6) swine growing/finishing; (7) dairy; and (8) lambing. The farm buildings represent the spectrum of animal types, heating energy use, and major contributions to national agricultural economic values. All energy analyses are based on hour by hour computations which allow for growth of animals, sensible and latent heat production, and ventilation requirements.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a “Virtual Farm” Concept for Enhancement of Site-Specific IPM

PubMed Central

Lux, Slawomir A.; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a “virtual farm” concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a “bottom-up ethological” approach and emulates behavior of the “primary IPM actors”—large cohorts of individual insects—within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the “virtual farm” approach—were discussed. PMID:27602000

Modeling, analysis, control and design application guidelines of Doubly Fed Induction Generator (DFIG) for wind power applications

NASA Astrophysics Data System (ADS)

Masaud, Tarek

Double Fed Induction Generators (DFIG) has been widely used for the past two decades in large wind farms. However, there are many open-ended problems yet to be solved before they can be implemented in some specific applications. This dissertation deals with the general analysis, modeling, control and applications of the DFIG for large wind farm applications. A detailed "d-q" model of DFIG along with other applications is simulated using the MATLAB/Simulink platform. The simulation results have been discussed in detail in both sub-synchronous and super-synchronous mode of operation. An improved vector control strategy based on the rotor flux oriented vector control has been proposed to control the active power output of the DFIG. The new vector control strategy is compared with the stator flux oriented vector control which is commonly used. It is observed that the new improved vector control method provides a better active power tracking accuracy compare with the stator flux oriented vector control. The behavior of the DFIG -based wind farm under the various grid disturbances is also studied in this dissertation. The implementation of the Flexible AC Transmission System devices (FACTS) to overcome the voltage stability issue for such applications is investigated. The study includes the implementation of both a static synchronous compensator (STATCOM), and the static VAR compensator (SVC) as dynamic reactive power compensators at the point of common coupling to support DFIG-based wind farm during disturbances. Integrating FACTS protect the grid connected DFIG-based wind farm from going offline during and after the disturbances. It is found that the both devices improve the transient performance and therefore helps the wind turbine generator system to remain in service during grid faults. A comparison between the performance of the two devices in terms of the amount of reactive power injected, time response and the application cost has been discussed in this dissertation. Finally, the integration of the battery energy storage system (BESS) into a grid connected DFIG- based wind turbine as a proposed solution to smooth out the output power during wind speed variations is also addressed.

Temporal and spatial water use on irrigated and nonirrigated pasture-based dairy farms.

PubMed

Higham, C D; Horne, D; Singh, R; Kuhn-Sherlock, B; Scarsbrook, M R

2017-08-01

Robust information for water use on pasture-based dairy farms is critical to farmers' attempts to use water more efficiently and the improved allocation of freshwater resources to dairy farmers. To quantify the water requirements of dairy farms across regions in a practicable manner, it will be necessary to develop predictive models. The objectives of this study were to compare water use on a group of irrigated and nonirrigated farms, validate existing water use models using the data measured on the group of nonirrigated farms, and modify the model so that it can be used to predict water use on irrigated dairy farms. Water use data were collected on a group of irrigated dairy farms located in the Canterbury, New Zealand, region with the largest area under irrigation. The nonirrigated farms were located in the Manawatu region. The amount of water used for irrigation was almost 52-fold greater than the amount of all other forms of water use combined. There were large differences in measured milking parlor water use, stock drinking water, and leakage rates between the irrigated and nonirrigated farms. As expected, stock drinking water was lower on irrigated dairy farms. Irrigation lowers the dry matter percentage of pasture, ensuring that the amount of water ingested from pasture remains high throughout the year, thereby reducing the demand for drinking water. Leakage rates were different between the 2 groups of farms; 47% of stock drinking water was lost as leakage on nonirrigated farms, whereas leakage on the irrigated farms equated to only 13% of stock drinking water. These differences in leakage were thought to be related to regional differences rather than differences in irrigated versus nonirrigated farms. Existing models developed to predict milking parlor, corrected stock drinking water, and total water use on nonirrigated pasture-based dairy farms in a previous related study were tested on the data measured in the present research. As expected, these models performed well for nonirrigated dairy farms but provided poor predictive power for irrigated farms. Partial least squares regression models were developed specifically to simulate corrected stock drinking water, milking parlor water, and total water use on irrigated dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Numerical analysis of the wake of a 10kW HAWT

NASA Astrophysics Data System (ADS)

Gong, S. G.; Deng, Y. B.; Xie, G. L.; Zhang, J. P.

2017-01-01

With the rising of wind power industry and the ever-growing scale of wind farm, the research for the wake performance of wind turbine has an important guiding significance for the overall arrangement of wind turbines in the large wind farm. The wake simulation model of 10kW horizontal-axis wind turbine is presented on the basis of Averaged Navier-Stokes (RANS) equations and the RNG k-ε turbulence model for applying to the rotational fluid flow. The sliding mesh technique in ANSYS CFX software is used to solve the coupling equation of velocity and pressure. The characters of the average velocity in the wake zone under rated inlet wind speed and different rotor rotational speeds have been investigated. Based on the analysis results, it is proposed that the horizontal spacing between the wind turbines is less than two times radius of rotor, and its longitudinal spacing is less than five times of radius. And other results have also been obtained, which are of great importance for large wind farms.

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development

PubMed Central

Alvarez, Stéphanie; Timler, Carl J.; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A.; Groot, Jeroen C. J.

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia’s Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies. PMID:29763422

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development.

PubMed

Alvarez, Stéphanie; Timler, Carl J; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A; Groot, Jeroen C J

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling.

PubMed

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm's capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate 'eco-efficiency' score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental 'sustainability' of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands.

Real time wind farm emulation using SimWindFarm toolbox

NASA Astrophysics Data System (ADS)

Topor, Marcel

2016-06-01

This paper presents a wind farm emulation solution using an open source Matlab/Simulink toolbox and the National Instruments cRIO platform. This work is based on the Aeolus SimWindFarm (SWF) toolbox models developed at Aalborg university, Denmark. Using the Matlab Simulink models developed in SWF, the modeling code can be exported to a real time model using the NI Veristand model framework and the resulting code is integrated as a hardware in the loop control on the NI 9068 platform.

Epidemiological modelling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy).

PubMed

Rossi, Gianluigi; De Leo, Giulio A; Pongolini, Stefano; Natalini, Silvano; Vincenzi, Simone; Bolzoni, Luca

2015-06-01

Assessing the performance of a surveillance system for infectious diseases of domestic animals is a challenging task for health authorities. Therefore, it is important to assess what strategy is the most effective in identifying the onset of an epidemic and in minimizing the number of infected farms. The aim of the present work was to evaluate the performance of the bovine tuberculosis (bTB) surveillance system in the network of dairy farms in the Emilia-Romagna (ER) Region, Italy. A bTB-free Region since 2007, ER implements an integrated surveillance strategy based on three components, namely routine on-farm tuberculin skin-testing performed every 3 years, tuberculin skin-testing of cattle exchanged between farms, and post-mortem inspection at slaughterhouses. We assessed the effectiveness of surveillance by means of a stochastic network model of both within-farm and between-farm bTB dynamics calibrated on data available for ER dairy farms. Epidemic dynamics were simulated for five scenarios: the current ER surveillance system, a no surveillance scenario that we used as the benchmark to characterize epidemic dynamics, three additional scenarios in which one of the surveillance components was removed at a time so as to outline its significance in detecting the infection. For each scenario we ran Monte Carlo simulations of bTB epidemics following the random introduction of an infected individual in the network. System performances were assessed through the comparative analysis of a number of statistics, including the time required for epidemic detection and the total number of infected farms during the epidemic. Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Retrospective analysis of Bluetongue farm risk profile definition, based on biology, farm management practices and climatic data.

PubMed

Cappai, Stefano; Loi, Federica; Coccollone, Annamaria; Contu, Marino; Capece, Paolo; Fiori, Michele; Canu, Simona; Foxi, Cipriano; Rolesu, Sandro

2018-07-01

Bluetongue (BT) is a vector-borne disease transmitted by species of Culicoides midges (Diptera: Ceratopogonidae). Many studies have contributed to clarifying various aspects of its aetiology, epidemiology and vector dynamic; however, BT remains a disease of epidemiological and economic importance that affects ruminants worldwide. Since 2000, the Sardinia region has been the most affected area of the Mediterranean basin. The region is characterised by wide pastoral areas for sheep and represents the most likely candidate region for the study of Bluetongue virus (BTV) distribution and prevalence in Italy. Furthermore, specific information on the farm level and epidemiological studies needs to be provided to increase the knowledge on the disease's spread and to provide valid mitigation strategies in Sardinia. This study conducted a punctual investigation into the spatial patterns of BTV transmission to define a risk profile for all Sardinian farmsby using a logistic multilevel mixed model that take into account agro-meteorological aspects, as well as farm characteristics and management. Data about animal density (i.e. sheep, goats and cattle), vaccination, previous outbreaks, altitude, land use, rainfall, evapotranspiration, water surface, and farm management practices (i.e. use of repellents, treatment against insect vectors, storage of animals in shelter overnight, cleaning, presence of mud and manure) were collected for 12,277 farms for the years 2011-2015. The logistic multilevel mixed model showed the fundamental role of climatic factors in disease development and the protective role of good management, vaccination, outbreak in the previous year and altitude. Regional BTV risk maps were developed, based on the predictor values of logistic model results, and updated every 10 days. These maps were used to identify, 20 days in advance, the areas at highest risk. The risk farm profile, as defined by the model, would provide specific information about the role of each factor for all Sardinian institutions involved in devising BT prevention and control strategies. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Spatial epidemiology of Toxoplasma gondii infection in goats in Serbia.

PubMed

Djokic, Vitomir; Klun, Ivana; Musella, Vincenzo; Rinaldi, Laura; Cringoli, Giuseppe; Sotiraki, Smaragda; Djurkovic-Djakovic, Olgica

2014-05-01

A major risk factor for Toxoplasma gondii infection is consumption of undercooked meat. Increasing demand for goat meat is likely to promote the role of this animal for human toxoplasmosis. As there are virtually no data on toxoplasmosis in goats in Serbia, we undertook a cross-sectional serological study, including prediction modelling using geographical information systems (GIS). Sera from 431 goats reared in 143 households/farms throughout Serbia, sampled between January 2010 and September 2011, were examined for T. gondii antibodies by a modified agglutination test. Seroprevalence was 73.3% at the individual level and 84.6% at the farm level. Risk factor analysis showed above two-fold higher risk of infection for goats used for all purposes compared to dairy goats (P = 0.012), almost seven-fold higher risk for goats kept as sole species versus those kept with other animals (P = 0.001) and a two-fold lower risk for goats introduced from outside the farm compared to those raised on the farm (P = 0.027). Moreover, households/farms located in centre-eastern Serbia were found to be less often infected than those in northern Serbia (P = 0.004). The risk factor analysis was fully supported by spatial analysis based on a GIS database containing data on origin, serology, land cover, elevation, meteorology and a spatial prediction map based on kriging analysis, which showed western Serbia as the area most likely for finding goats positive for T. gondii and centre-eastern Serbia as the least likely. In addition, rainfall favoured seropositivity, whereas temperature, humidity and elevation did not.

Simulation of logistics to supply Corn Stover to the Ontario Power Generation (OPG) Plant in Lambton, Ontario

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khaleghi Hamedani, Hamid; Lau, Anthony K.; DeBruyn, Jake

The overall goal of this research is to investigate the logistics of agricultural biomass in Ontario, Canada using the Integrated Biomass Supply Analysis and Logistics Model (IBSAL). The supply of corn stover to the Ontario Power Generation (OPG) power plant in Lambton is simulated. This coal-fired power plant is currently not operating and there are no active plans by OPG to fuel it with biomass. Rather, this scenario is considered only to demonstrate the application of the IBSAL Model to this type of scenario. Here, five scenarios of delivering corn stover to the Lambton Generating Station (GS) power plant inmore » Lambton Ontario are modeled: (1) truck transport from field edge to OPG (base scenario); (2) farm to central storage located on the highway, then truck transport bales to OPG; (3) direct truck transport from farm (no-stacking) to OPG; (4) farm to a loading port on Lake Huron and from there on a barge to OPG; and (5) farm to a railhead and then to OPG by rail.« less

Simulation of logistics to supply Corn Stover to the Ontario Power Generation (OPG) Plant in Lambton, Ontario

DOE PAGES

Khaleghi Hamedani, Hamid; Lau, Anthony K.; DeBruyn, Jake; ...

2016-05-10

The overall goal of this research is to investigate the logistics of agricultural biomass in Ontario, Canada using the Integrated Biomass Supply Analysis and Logistics Model (IBSAL). The supply of corn stover to the Ontario Power Generation (OPG) power plant in Lambton is simulated. This coal-fired power plant is currently not operating and there are no active plans by OPG to fuel it with biomass. Rather, this scenario is considered only to demonstrate the application of the IBSAL Model to this type of scenario. Here, five scenarios of delivering corn stover to the Lambton Generating Station (GS) power plant inmore » Lambton Ontario are modeled: (1) truck transport from field edge to OPG (base scenario); (2) farm to central storage located on the highway, then truck transport bales to OPG; (3) direct truck transport from farm (no-stacking) to OPG; (4) farm to a loading port on Lake Huron and from there on a barge to OPG; and (5) farm to a railhead and then to OPG by rail.« less

Using state-space models to predict the abundance of juvenile and adult sea lice on Atlantic salmon.

PubMed

Elghafghuf, Adel; Vanderstichel, Raphael; St-Hilaire, Sophie; Stryhn, Henrik

2018-04-11

Sea lice are marine parasites affecting salmon farms, and are considered one of the most costly pests of the salmon aquaculture industry. Infestations of sea lice on farms significantly increase opportunities for the parasite to spread in the surrounding ecosystem, making control of this pest a challenging issue for salmon producers. The complexity of controlling sea lice on salmon farms requires frequent monitoring of the abundance of different sea lice stages over time. Industry-based data sets of counts of lice are amenable to multivariate time-series data analyses. In this study, two sets of multivariate autoregressive state-space models were applied to Chilean sea lice data from six Atlantic salmon production cycles on five isolated farms (at least 20 km seaway distance away from other known active farms), to evaluate the utility of these models for predicting sea lice abundance over time on farms. The models were constructed with different parameter configurations, and the analysis demonstrated large heterogeneity between production cycles for the autoregressive parameter, the effects of chemotherapeutant bath treatments, and the process-error variance. A model allowing for different parameters across production cycles had the best fit and the smallest overall prediction errors. However, pooling information across cycles for the drift and observation error parameters did not substantially affect model performance, thus reducing the number of necessary parameters in the model. Bath treatments had strong but variable effects for reducing sea lice burdens, and these effects were stronger for adult lice than juvenile lice. Our multivariate state-space models were able to handle different sea lice stages and provide predictions for sea lice abundance with reasonable accuracy up to five weeks out. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Increased risk of pneumonia in residents living near poultry farms: does the upper respiratory tract microbiota play a role?

PubMed

Smit, Lidwien A M; Boender, Gert Jan; de Steenhuijsen Piters, Wouter A A; Hagenaars, Thomas J; Huijskens, Elisabeth G W; Rossen, John W A; Koopmans, Marion; Nodelijk, Gonnie; Sanders, Elisabeth A M; Yzermans, Joris; Bogaert, Debby; Heederik, Dick

2017-01-01

Air pollution has been shown to increase the susceptibility to community-acquired pneumonia (CAP). Previously, we observed an increased incidence of CAP in adults living within 1 km from poultry farms, potentially related to particulate matter and endotoxin emissions. We aim to confirm the increased risk of CAP near poultry farms by refined spatial analyses, and we hypothesize that the oropharyngeal microbiota composition in CAP patients may be associated with residential proximity to poultry farms. A spatial kernel model was used to analyze the association between proximity to poultry farms and CAP diagnosis, obtained from electronic medical records of 92,548 GP patients. The oropharyngeal microbiota composition was determined in 126 hospitalized CAP patients using 16S-rRNA-based sequencing, and analyzed in relation to residential proximity to poultry farms. Kernel analysis confirmed a significantly increased risk of CAP when living near poultry farms, suggesting an excess risk up to 1.15 km, followed by a sharp decline. Overall, the oropharyngeal microbiota composition differed borderline significantly between patients living <1 km and ≥1 km from poultry farms (PERMANOVA p  = 0.075). Results suggested a higher abundance of Streptococcus pneumoniae (mean relative abundance 34.9% vs. 22.5%, p  = 0.058) in patients living near poultry farms, which was verified by unsupervised clustering analysis, showing overrepresentation of a S. pneumoniae cluster near poultry farms ( p  = 0.049). Living near poultry farms is associated with an 11% increased risk of CAP, possibly resulting from changes in the upper respiratory tract microbiota composition in susceptible individuals. The abundance of S. pneumoniae near farms needs to be replicated in larger, independent studies.

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling

PubMed Central

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm’s capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate ‘eco-efficiency’ score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental ‘sustainability’ of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands. PMID:27832199

Cost Analysis of Various Low Pathogenic Avian Influenza Surveillance Systems in the Dutch Egg Layer Sector

PubMed Central

Rutten, Niels; Gonzales, José L.; Elbers, Armin R. W.; Velthuis, Annet G. J.

2012-01-01

Background As low pathogenic avian influenza viruses can mutate into high pathogenic viruses the Dutch poultry sector implemented a surveillance system for low pathogenic avian influenza (LPAI) based on blood samples. It has been suggested that egg yolk samples could be sampled instead of blood samples to survey egg layer farms. To support future decision making about AI surveillance economic criteria are important. Therefore a cost analysis is performed on systems that use either blood or eggs as sampled material. Methodology/Principal Findings The effectiveness of surveillance using egg or blood samples was evaluated using scenario tree models. Then an economic model was developed that calculates the total costs for eight surveillance systems that have equal effectiveness. The model considers costs for sampling, sample preparation, sample transport, testing, communication of test results and for the confirmation test on false positive results. The surveillance systems varied in sampled material (eggs or blood), sampling location (farm or packing station) and location of sample preparation (laboratory or packing station). It is shown that a hypothetical system in which eggs are sampled at the packing station and samples prepared in a laboratory had the lowest total costs (i.e. € 273,393) a year. Compared to this a hypothetical system in which eggs are sampled at the farm and samples prepared at a laboratory, and the currently implemented system in which blood is sampled at the farm and samples prepared at a laboratory have 6% and 39% higher costs respectively. Conclusions/Significance This study shows that surveillance for avian influenza on egg yolk samples can be done at lower costs than surveillance based on blood samples. The model can be used in future comparison of surveillance systems for different pathogens and hazards. PMID:22523543

Technical indicators of economic performance in dairy sheep farming.

PubMed

Theodoridis, A; Ragkos, A; Roustemis, D; Arsenos, G; Abas, Z; Sinapis, E

2014-01-01

In this study, the level of technical efficiency of 58 sheep farms rearing the Chios breed in Greece was measured through the application of the stochastic frontier analysis method. A Translog stochastic frontier production function was estimated using farm accounting data of Chios sheep farms and the impact of various socio-demographic and biophysical factors on the estimated efficiency of the farms was evaluated. The farms were classified into efficiency groups on the basis of the estimated level of efficiency and a technical and economic descriptive analysis was applied in order to illustrate an indicative picture of their structure and productivity. The results of the stochastic frontier model indicate that there are substantial production inefficiencies among the Chios sheep farms and that these farms could increase their production through the improvement of technical efficiency, whereas the results of the inefficiency effects model reveal that the farm-specific explanatory factors can partly explain the observed efficiency differentials. The measurement of technical inefficiency and the detection of its determinants can be used to form the basis of policy recommendations that could contribute to the development of the sector.

Offshore wind farm layout optimization

NASA Astrophysics Data System (ADS)

Elkinton, Christopher Neil

Offshore wind energy technology is maturing in Europe and is poised to make a significant contribution to the U.S. energy production portfolio. Building on the knowledge the wind industry has gained to date, this dissertation investigates the influences of different site conditions on offshore wind farm micrositing---the layout of individual turbines within the boundaries of a wind farm. For offshore wind farms, these conditions include, among others, the wind and wave climates, water depths, and soil conditions at the site. An analysis tool has been developed that is capable of estimating the cost of energy (COE) from offshore wind farms. For this analysis, the COE has been divided into several modeled components: major costs (e.g. turbines, electrical interconnection, maintenance, etc.), energy production, and energy losses. By treating these component models as functions of site-dependent parameters, the analysis tool can investigate the influence of these parameters on the COE. Some parameters result in simultaneous increases of both energy and cost. In these cases, the analysis tool was used to determine the value of the parameter that yielded the lowest COE and, thus, the best balance of cost and energy. The models have been validated and generally compare favorably with existing offshore wind farm data. The analysis technique was then paired with optimization algorithms to form a tool with which to design offshore wind farm layouts for which the COE was minimized. Greedy heuristic and genetic optimization algorithms have been tuned and implemented. The use of these two algorithms in series has been shown to produce the best, most consistent solutions. The influences of site conditions on the COE have been studied further by applying the analysis and optimization tools to the initial design of a small offshore wind farm near the town of Hull, Massachusetts. The results of an initial full-site analysis and optimization were used to constrain the boundaries of the farm. A more thorough optimization highlighted the features of the area that would result in a minimized COE. The results showed reasonable layout designs and COE estimates that are consistent with existing offshore wind farms.

Assessing agro-environmental performance of dairy farms in northwest Italy based on aggregated results from indicators.

PubMed

Gaudino, Stefano; Goia, Irene; Grignani, Carlo; Monaco, Stefano; Sacco, Dario

2014-07-01

Dairy farms control an important share of the agricultural area of Northern Italy. Zero grazing, large maize-cropped areas, high stocking densities, and high milk production make them intensive and prone to impact the environment. Currently, few published studies have proposed indicator sets able to describe the entire dairy farm system and their internal components. This work had four aims: i) to propose a list of agro-environmental indicators to assess dairy farms; ii) to understand which indicators classify farms best; iii) to evaluate the dairy farms based on the proposed indicator list; iv) to link farmer decisions to the consequent environmental pressures. Forty agro-environmental indicators selected for this study are described. Northern Italy dairy systems were analysed considering both farmer decision indicators (farm management) and the resulting pressure indicators that demonstrate environmental stress on the entire farming system, and its components: cropping system, livestock system, and milk production. The correlations among single indicators identified redundant indicators. Principal Components Analysis distinguished which indicators provided meaningful information about each pressure indicator group. Analysis of the communalities and the correlations among indicators identified those that best represented farm variability: Farm Gate N Balance, Greenhouse Gas Emission, and Net Energy of the farm system; Net Energy and Gross P Balance of the cropping system component; Energy Use Efficiency and Purchased Feed N Input of the livestock system component; N Eco-Efficiency of the milk production component. Farm evaluation, based on the complete list of selected indicators demonstrated organic farming resulted in uniformly high values, while farms with low milk-producing herds resulted in uniformly low values. Yet on other farms, the environmental quality varied greatly when different groups of pressure indicators were considered, which highlighted the importance of expanding environmental analysis to effects within the farm. Statistical analysis demonstrated positive correlations between all farmer decision and pressure group indicators. Consumption of mineral fertiliser and pesticide negatively influenced the cropping system. Furthermore, stocking rate was found to correlate positively with the milk production component and negatively with the farm system. This study provides baseline references for ex ante policy evaluation, and monitoring tools for analysis both in itinere and ex post environment policy implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

A preliminary benefit-cost study of a Sandia wind farm.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlen, Mark Andrew; Griffin, Taylor; Loose, Verne W.

In response to federal mandates and incentives for renewable energy, Sandia National Laboratories conducted a feasibility study of installing an on-site wind farm on Sandia National Laboratories and Kirtland Air Force Base property. This report describes this preliminary analysis of the costs and benefits of installing and operating a 15-turbine, 30-MW-capacity wind farm that delivers an estimated 16 percent of 2010 onsite demand. The report first describes market and non-market economic costs and benefits associated with operating a wind farm, and then uses a standard life-cycle costing and benefit-cost framework to estimate the costs and benefits of a wind farm.more » Based on these 'best-estimates' of costs and benefits and on factor, uncertainty and sensitivity analysis, the analysis results suggest that the benefits of a Sandia wind farm are greater than its costs. The analysis techniques used herein are applicable to the economic assessment of most if not all forms of renewable energy.« less

An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies.

PubMed

Soteriades, A D; Faverdin, P; Moreau, S; Charroin, T; Blanchard, M; Stott, A W

2016-11-01

Eco-efficiency is a useful guide to dairy farm sustainability analysis aimed at increasing output (physical or value added) and minimizing environmental impacts (EIs). Widely used partial eco-efficiency ratios (EIs per some functional unit, e.g. kg milk) can be problematic because (i) substitution possibilities between EIs are ignored, (ii) multiple ratios can complicate decision making and (iii) EIs are not usually associated with just the functional unit in the ratio's denominator. The objective of this study was to demonstrate a 'global' eco-efficiency modelling framework dealing with issues (i) to (iii) by combining Life Cycle Analysis (LCA) data and the multiple-input, multiple-output production efficiency method Data Envelopment Analysis (DEA). With DEA each dairy farm's outputs and LCA-derived EIs are aggregated into a single, relative, bounded, dimensionless eco-efficiency score, thus overcoming issues (i) to (iii). A novelty of this study is that a model providing a number of additional desirable properties was employed, known as the Range Adjusted Measure (RAM) of inefficiency. These properties altogether make RAM advantageous over other DEA models and are as follows. First, RAM is able to simultaneously minimize EIs and maximize outputs. Second, it indicates which EIs and/or outputs contribute the most to a farm's eco-inefficiency. Third it can be used to rank farms in terms of eco-efficiency scores. Thus, non-parametric rank tests can be employed to test for significant differences in terms of eco-efficiency score ranks between different farm groups. An additional DEA methodology was employed to 'correct' the farms' eco-efficiency scores for inefficiencies attributed to managerial factors. By removing managerial inefficiencies it was possible to detect differences in eco-efficiency between farms solely attributed to uncontrollable factors such as region. Such analysis is lacking in previous dairy studies combining LCA with DEA. RAM and the 'corrective' methodology were demonstrated with LCA data from French specialized dairy farms grouped by region (West France, Continental France) and feeding strategy (regardless of region). Mean eco-efficiency score ranks were significantly higher for farms with 30% maize in the total forage area before correcting for managerial inefficiencies. Mean eco-efficiency score ranks were higher for West than Continental farms, but significantly higher only after correcting for managerial inefficiencies. These results helped identify the eco-efficiency potential of each region and feeding strategy and could therefore aid advisors and policy makers at farm or region/sector level. The proposed framework helped better measure and understand (dairy) farm eco-efficiency, both within and between different farm groups.

Modeling livestock population structure: a geospatial database for Ontario swine farms.

PubMed

Khan, Salah Uddin; O'Sullivan, Terri L; Poljak, Zvonimir; Alsop, Janet; Greer, Amy L

2018-01-30

Infectious diseases in farmed animals have economic, social, and health consequences. Foreign animal diseases (FAD) of swine are of significant concern. Mathematical and simulation models are often used to simulate FAD outbreaks and best practices for control. However, simulation outcomes are sensitive to the population structure used. Within Canada, access to individual swine farm population data with which to parameterize models is a challenge because of privacy concerns. Our objective was to develop a methodology to model the farmed swine population in Ontario, Canada that could represent the existing population structure and improve the efficacy of simulation models. We developed a swine population model based on the factors such as facilities supporting farm infrastructure, land availability, zoning and local regulations, and natural geographic barriers that could affect swine farming in Ontario. Assigned farm locations were equal to the swine farm density described in the 2011 Canadian Census of Agriculture. Farms were then randomly assigned to farm types proportional to the existing swine herd types. We compared the swine population models with a known database of swine farm locations in Ontario and found that the modeled population was representative of farm locations with a high accuracy (AUC: 0.91, Standard deviation: 0.02) suggesting that our algorithm generated a reasonable approximation of farm locations in Ontario. In the absence of a readily accessible dataset providing details of the relative locations of swine farms in Ontario, development of a model livestock population that captures key characteristics of the true population structure while protecting privacy concerns is an important methodological advancement. This methodology will be useful for individuals interested in modeling the spread of pathogens between farms across a landscape and using these models to evaluate disease control strategies.

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

NASA Astrophysics Data System (ADS)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

USDA-ARS?s Scientific Manuscript database

Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus.

PubMed

VanderWaal, Kimberly; Perez, Andres; Torremorrell, Montse; Morrison, Robert M; Craft, Meggan

2018-04-12

Epidemiological models of the spread of pathogens in livestock populations primarily focus on direct contact between farms based on animal movement data, and in some cases, local spatial spread based on proximity between premises. The roles of other types of indirect contact among farms is rarely accounted for. In addition, data on animal movements is seldom available in the United States. However, the spread of porcine epidemic diarrhea virus (PEDv) in U.S. swine represents one of the best documented emergences of a highly infectious pathogen in the U.S. livestock industry, providing an opportunity to parameterize models of pathogen spread via direct and indirect transmission mechanisms in swine. Using observed data on pig movements during the initial phase of the PEDv epidemic, we developed a network-based and spatially explicit epidemiological model that simulates the spread of PEDv via both indirect and direct movement-related contact in order to answer unresolved questions concerning factors facilitating between-farm transmission. By modifying the likelihood of each transmission mechanism and fitting this model to observed epidemiological dynamics, our results suggest that between-farm transmission was primarily driven by direct mechanisms related to animal movement and indirect mechanisms related to local spatial spread based on geographic proximity. However, other forms of indirect transmission among farms, including contact via contaminated vehicles and feed, were responsible for high consequence transmission events resulting in the introduction of the virus into new geographic areas. This research is among the first reports of farm-level animal movements in the U.S. swine industry and, to our knowledge, represents the first epidemiological model of commercial U.S. swine using actual data on farm-level animal movement. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Agent Based Model of Livestock Movements

NASA Astrophysics Data System (ADS)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

Soil Protection measures based on the analysis if sediment sources in a commercial farm at the Guadalquivir Valley (Spain)

NASA Astrophysics Data System (ADS)

Albert, Enrique; Brígido, Consuelo; Herrera, Pascual; Migallón, Jose Ignacio; Taguas, Encarnación V.

2016-04-01

High soil losses are associated with agricultural areas dedicated to traditional crops in Spain (olive, grapevine, almond and sunflower, among others) and they caused by interacting drivers such as frequent intense events, steep/hilly slopes and unsuitable managements (De Santisteban et al., 2006). These crops are essential for the Spanish economy but at the same time, they constitute important areas of soil degradation. This work has been promoted by a farm owner interested in improving the sustainability of his farm as well as solving traffic problems derived from a gully. An analysis based on a modeling approach and field measurements was carried out in order to diagnose the main sediment sources of a farm with traditional Mediterranean crops (sunflower and olives) and to propose actions for optimizing soil conservation efforts. Firstly, an environmental study to characterize meteorological and topographical features, soil properties and managements was performed. The farm was divided in different areas belonging to the same hydrological catchment, land-use and management. Secondly, splash and inter-rill erosion were evaluated in each spatial unit through the RUSLE model. Rills and gullies in the catchment were also measured by using orthophotographies and a tape in the field to calculate their corresponding sediment volume. Finally, a plan of soil protection measures was designed and presented to the owner who will apply the proposed actions, mainly cover crop seeding and construction of check dams. REFERENCES: De Santisteban, L. M., J. Casalí, and J. J. López. 2006. Assessing soil erosion rates in cultivated areas of Navarre (Spain). Earth Surf. Process. Landforms 31: 487-506.

Preserving privacy whilst maintaining robust epidemiological predictions.

PubMed

Werkman, Marleen; Tildesley, Michael J; Brooks-Pollock, Ellen; Keeling, Matt J

2016-12-01

Mathematical models are invaluable tools for quantifying potential epidemics and devising optimal control strategies in case of an outbreak. State-of-the-art models increasingly require detailed individual farm-based and sensitive data, which may not be available due to either lack of capacity for data collection or privacy concerns. However, in many situations, aggregated data are available for use. In this study, we systematically investigate the accuracy of predictions made by mathematical models initialised with varying data aggregations, using the UK 2001 Foot-and-Mouth Disease Epidemic as a case study. We consider the scenario when the only data available are aggregated into spatial grid cells, and develop a metapopulation model where individual farms in a single subpopulation are assumed to behave uniformly and transmit randomly. We also adapt this standard metapopulation model to capture heterogeneity in farm size and composition, using farm census data. Our results show that homogeneous models based on aggregated data overestimate final epidemic size but can perform well for predicting spatial spread. Recognising heterogeneity in farm sizes improves predictions of the final epidemic size, identifying risk areas, determining the likelihood of epidemic take-off and identifying the optimal control strategy. In conclusion, in cases where individual farm-based data are not available, models can still generate meaningful predictions, although care must be taken in their interpretation and use. Copyright © 2016. Published by Elsevier B.V.

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed

Yatabe, Tadaishi; More, Simon J; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm's disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders.

Network analysis of swine shipments in Ontario, Canada, to support disease spread modelling and risk-based disease management.

PubMed

Dorjee, S; Revie, C W; Poljak, Z; McNab, W B; Sanchez, J

2013-10-01

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada. Copyright © 2013 Elsevier B.V. All rights reserved.

Power-Production Diagnostic Tools for Low-Density Wind Farms with Applications to Wake Steering

NASA Astrophysics Data System (ADS)

Takle, E. S.; Herzmann, D.; Rajewski, D. A.; Lundquist, J. K.; Rhodes, M. E.

2016-12-01

Hansen (2011) provided guidelines for wind farm wake analysis with applications to "high density" wind farms (where average distance between turbines is less than ten times rotor diameter). For "low-density" (average distance greater than fifteen times rotor diameter) wind farms, or sections of wind farms we demonstrate simpler sorting and visualization tools that reveal wake interactions and opportunities for wind farm power prediction and wake steering. SCADA data from a segment of a large mid-continent wind farm, together with surface flux measurements and lidar data are subjected to analysis and visualization of wake interactions. A time-history animated visualization of a plan view of power level of individual turbines provides a quick analysis of wake interaction dynamics. Yaw-based sectoral histograms of enhancement/decline of wind speed and power from wind farm reference levels reveals angular width of wake interactions and identifies the turbine(s) responsible for the power reduction. Concurrent surface flux measurements within the wind farm allowed us to evaluate stability influence on wake loss. A one-season climatology is used to identify high-priority candidates for wake steering based on estimated power recovery. Typical clearing prices on the day-ahead market are used to estimate the added value of wake steering. Current research is exploring options for identifying candidate locations for wind farm "build-in" in existing low-density wind farms.

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis

USGS Publications Warehouse

Walter, W. David; Smith, Rick; Vanderklok, Mike; VerCauterren, Kurt C.

2014-01-01

Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles), brushtail possum (Trichosurus vulpecula), and white-tailed deer (Odocoileus virginianus). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research onM. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovisidentified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd factors and cattle farm prevalence is documented.

A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru.

PubMed

Martínez-López, B; Ivorra, B; Fernández-Carrión, E; Perez, A M; Medel-Herrero, A; Sánchez-Vizcaíno, F; Gortázar, C; Ramos, A M; Sánchez-Vizcaíno, J M

2014-04-01

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI-II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI-III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I-IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru. Copyright © 2014 Elsevier B.V. All rights reserved.

Gradient-Based Optimization of Wind Farms with Different Turbine Heights: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanley, Andrew P. J.; Thomas, Jared; Ning, Andrew

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hubmore » heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.« less

Gradient-Based Optimization of Wind Farms with Different Turbine Heights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanley, Andrew P. J.; Thomas, Jared; Ning, Andrew

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hubmore » heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.« less

Economic efficiency analysis of different strategies to control post-weaning multi-systemic wasting syndrome and porcine circovirus type 2 subclinical infection in 3-weekly batch system farms

PubMed Central

Alarcon, Pablo; Rushton, Jonathan; Nathues, Heiko; Wieland, Barbara

2013-01-01

The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between ‘vac’ and ‘vac + bios’ being small. Other strategies such as ‘diets’, ‘vac + diets’ and ‘bios + diets’ were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome. PMID:23375866

Comparison of Greenhouse Gas Emissions between Two Dairy Farm Systems (Conventional vs. Organic Management) in New Hampshire Using the Manure DNDC Biogeochemical Model

NASA Astrophysics Data System (ADS)

Dorich, C.; Contosta, A.; Li, C.; Brito, A.; Varner, R. K.

2013-12-01

Agriculture contributes 20 to 25 % of the total anthropogenic greenhouse gas (GHG) emissions globally. These agricultural emissions are primarily in the form of methane (CH4) and nitrous oxide (N2O) with these GHG accounting for roughly 40 and 80 % of the total anthropogenic emissions of CH4 and N2O, respectively. Due to varied management and the complexities of agricultural ecosystems, it is difficult to estimate these CH4 and N2O emissions. The IPCC emission factors can be used to yield rough estimates of CH4 and N2O emissions but they are often based on limited data. Accurate modeling validated by measurements is needed in order to identify potential mitigation areas, reduce GHG emissions from agriculture, and improve sustainability of farming practices. The biogeochemical model Manure DNDC was validated using measurements from two dairy farms in New Hampshire, USA in order to quantify GHG emissions under different management systems. One organic and one conventional dairy farm operated by the University of New Hampshire's Agriculture Experiment Station were utilized as the study sites for validation of Manure DNDC. Compilation of management records started in 2011 to provide model inputs. Model results were then compared to field collected samples of soil carbon and nitrogen, above-ground biomass, and GHG fluxes. Fluxes were measured in crop, animal, housing, and waste management sites on the farms in order to examine the entire farm ecosystem and test the validity of the model. Fluxes were measured by static flux chambers, with enteric fermentation measurements being conducted by the SF6 tracer test as well as a new method called Greenfeeder. Our preliminary GHG flux analysis suggests higher emissions than predicted by IPCC emission factors and equations. Results suggest that emissions from manure management is a key concern at the conventional dairy farm while bedded housing at the organic dairy produced large quantities of GHG.

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed Central

More, Simon J.; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E.; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm’s disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders. PMID:29381760

Survey of quantitative antimicrobial consumption in two different pig finishing systems.

PubMed

Moreno, M A

2012-09-29

The primary objectives of this study were to: (a) collect on-farm antimicrobial use (AMU) data in fattener pigs employing two questionnaire-based surveys; (b) assess different quantitative measures for quantifying AMU in fattener pigs; (c) compare AMU in fattener pigs between two different management systems producing finishers: farrow-to-finish (FtF) farms versus finisher farms. Two questionnaires were designed both containing five groups of questions focused on the responder, the farm and AMU (eg, in-feed, in-drinking water and parenteral); both surveys were carried out by means of personal face-to-face interviews. Both surveys started with a sample size of 108 potentially eligible farms per survey; nevertheless, finally 67 finisher farms and 49 FtF farms were recruited. Overall percentages of animals exposed to antimicrobials (AM) were high (90 per cent in finisher farms and 54 per cent FtF farms); colistin (61 per cent and 33 per cent) and doxycycline (62 per cent and 23 per cent) were the most common AMs, followed by amoxicillin (51 per cent and 19 per cent) and lincomycin (49 per cent), respectively. Questionnaire-based surveys using face-to-face interviews are useful for capturing information regarding AMU at the farm level. Farm-level data per administration route can be used for comparative AMU analysis between farms. Nevertheless, for the analysis of the putative relationships between AMU and AM resistance, measures based on exposed animals or exposure events are needed.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 2: Wind farm wake models

NASA Astrophysics Data System (ADS)

Moriarty, Patrick; Sanz Rodrigo, Javier; Gancarski, Pawel; Chuchfield, Matthew; Naughton, Jonathan W.; Hansen, Kurt S.; Machefaux, Ewan; Maguire, Eoghan; Castellani, Francesco; Terzi, Ludovico; Breton, Simon-Philippe; Ueda, Yuko

2014-06-01

Researchers within the International Energy Agency (IEA) Task 31: Wakebench have created a framework for the evaluation of wind farm flow models operating at the microscale level. The framework consists of a model evaluation protocol integrated with a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to wind farm wake models, including best practices for the benchmarking and data processing procedures for validation datasets from wind farm SCADA and meteorological databases. A hierarchy of test cases has been proposed for wake model evaluation, from similarity theory of the axisymmetric wake and idealized infinite wind farm, to single-wake wind tunnel (UMN-EPFL) and field experiments (Sexbierum), to wind farm arrays in offshore (Horns Rev, Lillgrund) and complex terrain conditions (San Gregorio). A summary of results from the axisymmetric wake, Sexbierum, Horns Rev and Lillgrund benchmarks are used to discuss the state-of-the-art of wake model validation and highlight the most relevant issues for future development.

Simulation of Long-Term Carbon and Nitrogen Dynamics in Grassland-Based Dairy Farming Systems to Evaluate Mitigation Strategies for Nutrient Losses

PubMed Central

Shah, Ghulam Abbas; Groot, Jeroen C.J.; Shah, Ghulam Mustafa; Lantinga, Egbert A.

2013-01-01

Many measures have been proposed to mitigate gaseous emissions and other nutrient losses from agroecosystems, which can have large detrimental effects for the quality of soils, water and air, and contribute to eutrophication and global warming. Due to complexities in farm management, biological interactions and emission measurements, most experiments focus on analysis of short-term effects of isolated mitigation practices. Here we present a model that allows simulating long-term effects at the whole-farm level of combined measures related to grassland management, animal housing and manure handling after excretion, during storage and after field application. The model describes the dynamics of pools of organic carbon and nitrogen (N), and of inorganic N, as affected by farm management in grassland-based dairy systems. We assessed the long-term effects of delayed grass mowing, housing type (cubicle and sloping floor barns, resulting in production of slurry and solid cattle manure, respectively), manure additives, contrasting manure storage methods and irrigation after application of covered manure. Simulations demonstrated that individually applied practices often result in compensatory loss pathways. For instance, methods to reduce ammonia emissions during storage like roofing or covering of manure led to larger losses through ammonia volatilization, nitrate leaching or denitrification after application, unless extra measures like irrigation were used. A strategy of combined management practices of delayed mowing and fertilization with solid cattle manure that is treated with zeolite, stored under an impermeable sheet and irrigated after application was effective to increase soil carbon stocks, increase feed self-sufficiency and reduce losses by ammonia volatilization and soil N losses. Although long-term datasets (>25 years) of farm nutrient dynamics and loss flows are not available to validate the model, the model is firmly based on knowledge of processes and measured effects of individual practices, and allows the integrated exploration of effective emission mitigation strategies. PMID:23826255

Farm-by-farm analysis of microsatellite, mtDNA and SNP genotype data reveals inbreeding and crossbreeding as threats to the survival of a native Spanish pig breed.

PubMed

Herrero-Medrano, J M; Megens, H J; Crooijmans, R P; Abellaneda, J M; Ramis, G

2013-06-01

The Chato Murciano (CM), a pig breed from the Murcia region in the southeastern region of Spain, is a good model for endangered livestock populations. The remaining populations are bred on approximately 15 small farms, and no herdbook exists. To assess the genetic threats to the integrity and survival of the CM breed, and to aid in designing a conservation program, three genetic marker systems - microsatellites, SNPs and mtDNA - were applied across the majority of the total breeding stock. In addition, mtDNA and SNPs were genotyped in breeds that likely contributed genetically to the current CM gene pool. The analyses revealed the levels of genetic diversity within the range of other European local breeds (H(e) = 0.53). However, when the eight farms that rear at least 10 CM pigs were independently analyzed, high levels of inbreeding were found in some. Despite the evidence for recent crossbreeding with commercial breeds on a few farms, the entire breeding stock remains readily identifiable as CM, facilitating the design of traceability assays. The genetic management of the breed is consistent with farm size, farm owner and presence of other pig breeds on the farm, demonstrating the highly ad hoc nature of current CM breeding. The results of genetic diversity and substructure of the entire breed, as well as admixture and crossbreeding obtained in the present study, provide a benchmark to develop future conservation strategies. Furthermore, this study demonstrates that identifying farm-based practices and farm-based breeding stocks can aid in the design of a sustainable breeding program for minority breeds. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

Sustainability assessment of greenhouse vegetable farming practices from environmental, economic, and socio-institutional perspectives in China.

PubMed

Yang, Lanqin; Huang, Biao; Mao, Mingcui; Yao, Lipeng; Niedermann, Silvana; Hu, Wenyou; Chen, Yong

2016-09-01

To provide growing population with sufficient food, greenhouse vegetable production has expanded rapidly in recent years in China and sustainability of its farming practices is a major concern. Therefore, this study assessed the sustainability of greenhouse vegetable farming practices from environmental, economic, and socio-institutional perspectives in China based on selected indicators. The empirical data were collected through a survey of 91 farm households from six typical greenhouse vegetable production bases and analysis of environmental material samples. The results showed that heavy fertilization in greenhouse vegetable bases of China resulted in an accumulation of N, P, Cd, Cu, Pb, and Zn in soil, nutrient eutrophication in irrigation water, and high Cd in some leaf vegetables cultivated in acidic soil. Economic factors including decreased crop yield in conventional farming bases, limited and site-dependent farmers' income, and lack of complete implementation of subsidy policies contributed a lot to adoption of heavy fertilization by farmers. Also, socio-institutional factors such as lack of unified management of agricultural supplies in the bases operated in cooperative and small family business models and low agricultural extension service efficiency intensified the unreasonable fertilization. The selection of cultivated vegetables was mainly based on farmers' own experience rather than site-dependent soil conditions. Thus, for sustainable development of greenhouse vegetable production systems in China, there are two key aspects. First, it is imperative to reduce environmental pollution and subsequent health risks through integrated nutrient management and the planting strategy of selected low metal accumulation vegetable species especially in acidic soil. Second, a conversion of cooperative and small family business models of greenhouse vegetable bases to enterprises should be extensively advocated in future for the unified agricultural supplies management and improved agricultural extension service efficiency, which in turn can stabilize vegetable yields and increase farmers' benefits.

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems.

PubMed

Del Prado, A; Crosson, P; Olesen, J E; Rotz, C A

2013-06-01

The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

A process-based emission model of volatile organic compounds from silage sources on farms

NASA Astrophysics Data System (ADS)

Bonifacio, H. F.; Rotz, C. A.; Hafner, S. D.; Montes, F.; Cohen, M.; Mitloehner, F. M.

2017-03-01

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively.

Temporal and spatial analysis of psittacosis in association with poultry farming in the Netherlands, 2000-2015.

PubMed

Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim

2017-07-26

Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.

A process-based emission model for volatile organic compounds from silage sources on farms

USDA-ARS?s Scientific Manuscript database

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources suc...

Water use on nonirrigated pasture-based dairy farms: Combining detailed monitoring and modeling to set benchmarks.

PubMed

Higham, C D; Horne, D; Singh, R; Kuhn-Sherlock, B; Scarsbrook, M R

2017-01-01

Water use in intensively managed, confinement dairy systems has been widely studied, but few reports exist regarding water use on pasture-based dairy farms. The objective of this study was to quantify the seasonal pattern of water use to develop a prediction model of water use for pasture-based dairy farms. Stock drinking, milking parlor, and total water use was measured on 35 pasture-based, seasonal calving dairy farms in New Zealand over 2 yr. Average stock drinking water was 60 L/cow per day, with peak use in summer. We estimated that, on average, 26% of stock drinking water was lost through leakage from water-distribution systems. Average corrected stock drinking water (equivalent to voluntary water intake) was 36 L/cow per day, and peak water consumption was 72 L/cow per day in summer. Milking parlor water use increased sharply at the start of lactation (July) and plateaued (August) until summer (February), after which it decreased with decreasing milk production. Average milking parlor water use was 58 L/cow per day (between September and February). Water requirements were affected by parlor type, with rotary milking parlor water use greater than herringbone parlor water use. Regression models were developed to predict stock drinking and milking parlor water use. The models included a range of climate, farm, and milk production variables. The main drivers of stock drinking water use were maximum daily temperature, potential evapotranspiration, radiation, and yield of milk and milk components. The main drivers for milking parlor water use were average per cow milk production and milking frequency. These models of water use are similar to those used in confinement dairy systems, where milk yield is commonly used as a variable. The models presented fit the measured data more accurately than other published models and are easier to use on pasture-based dairy farms, as they do not include feed and variables that are difficult to measure on pasture-based farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Integrated Farm System Model: A Tool for Whole Farm Nutrient Management Analysis

USDA-ARS?s Scientific Manuscript database

With tighter profit margins and increasing environmental constraints, strategic planning of farm production systems is becoming both more important and more difficult. This is especially true for integrated crop and animal production systems. Animal production is complex with a number of interacting...

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

NASA Technical Reports Server (NTRS)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Research on evaluating water resource resilience based on projection pursuit classification model

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhao, Dan; Liang, Xu; Wu, Qiuchen

2016-03-01

Water is a fundamental natural resource while agriculture water guarantees the grain output, which shows that the utilization and management of water resource have a significant practical meaning. Regional agricultural water resource system features with unpredictable, self-organization, and non-linear which lays a certain difficulty on the evaluation of regional agriculture water resource resilience. The current research on water resource resilience remains to focus on qualitative analysis and the quantitative analysis is still in the primary stage, thus, according to the above issues, projection pursuit classification model is brought forward. With the help of artificial fish-swarm algorithm (AFSA), it optimizes the projection index function, seeks for the optimal projection direction, and improves AFSA with the application of self-adaptive artificial fish step and crowding factor. Taking Hongxinglong Administration of Heilongjiang as the research base and on the basis of improving AFSA, it established the evaluation of projection pursuit classification model to agriculture water resource system resilience besides the proceeding analysis of projection pursuit classification model on accelerating genetic algorithm. The research shows that the water resource resilience of Hongxinglong is the best than Raohe Farm, and the last 597 Farm. And the further analysis shows that the key driving factors influencing agricultural water resource resilience are precipitation and agriculture water consumption. The research result reveals the restoring situation of the local water resource system, providing foundation for agriculture water resource management.

Use of Bayesian networks in predicting contamination of drinking water with E. coli in rural Vietnam.

PubMed

Hall, David C; Le, Quynh B

2017-06-01

More than 70 million Vietnamese rely on small-scale farming for some form of household income. Water on many of those farms is contaminated with waste, including animal manure, partly due to non-sustainable waste management. This increases the risk of water-related zoonotic disease transmission. The purpose of this research was to examine the impact of various demographic and management factors on the likelihood of finding Escherichia coli in drinking water sourced from wells and rainwater on farms in Vietnam. A Bayesian Belief Network (BBN) was designed to describe association between various deterministic and probabilistic variables gathered from 600 small-scale integrated (SSI) farmers in Vietnam. The variables relate to E. coli content of their drinking water sourced on-farm from wells and rainwater, and stored in on-farm large vessels, including concrete water tanks. The BBN was developed using the Netica software tool; the model was calibrated and goodness of fit examined using concordance of predictability. Sensitivity analysis of the model revealed that choice variables, including engagement in mitigation of water contamination and livestock management activities, were particularly likely to influence endpoint values, reflecting the highly variable and impactful nature of preferences, attitudes and beliefs relating to mitigation strategies. Quantitative variables including numbers of livestock (particularly chickens) and income also had a high impact. The highest concordance (62%) was achieved with the BBN reported in this paper. This BBN model of SSI farming in Vietnam is helpful in understanding the complexity of small-scale agriculture and how various factors work in concert to influence contamination of on-farm drinking water as indicated by the presence of E. coli. The model will also be useful for identifying and estimating the impact of policy options such as improved delivery of clean water management training for rural areas, particularly where such analysis is combined with other analytical and policy tools. With appropriate knowledge translation, the model results will be particularly useful in helping SSI farmers understand their options for engaging in public health mitigation strategies addressing clean water that do not significantly disrupt their agriculture-based livelihoods. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis.

PubMed

Garcia, E; Klaas, I; Amigo, J M; Bro, R; Enevoldsen, C

2014-12-01

Lameness causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods. Eighty variables retrieved from AMS were summarized week-wise and used to predict 2 defined classes: nonlame and clinically lame cows. Variables were represented with 2 transformations of the week summarized variables, using 2-wk data blocks before gait scoring, totaling 320 variables (2 × 2 × 80). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3 or 4/4) or not lame (score 1/4). Both models achieved sensitivity and specificity values around 80%, both in calibration and cross-validation. At the optimum values in the receiver operating characteristic curve, the false-positive rate was 28% in the parity 1 model, whereas in the parity 2 model it was about half (16%), which makes it more suitable for practical application; the model error rates were, 23 and 19%, respectively. Based on data registered automatically from one AMS farm, we were able to discriminate nonlame and lame cows, where partial least squares discriminant analysis achieved similar performance to the reference method. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Mathematical Modeling of Influenza A Virus Dynamics within Swine Farms and the Effects of Vaccination

PubMed Central

Reynolds, Jennifer J. H.; Torremorell, Montserrat; Craft, Meggan E.

2014-01-01

Influenza A virus infections are widespread in swine herds across the world. Influenza negatively affects swine health and production, and represents a significant threat to public health due to the risk of zoonotic infections. Swine herds can act as reservoirs for potentially pandemic influenza strains. In this study, we develop mathematical models based on experimental data, representing typical breeding and wean-to-finish swine farms. These models are used to explore and describe the dynamics of influenza infection at the farm level, which are at present not well understood. In addition, we use the models to assess the effectiveness of vaccination strategies currently employed by swine producers, testing both homologous and heterologous vaccines. An important finding is that following an influenza outbreak in a breeding herd, our model predicts a persistently high level of infectious piglets. Sensitivity analysis indicates that this finding is robust to changes in both transmission rates and farm size. Vaccination does not eliminate influenza throughout the breeding farm population. In the wean-to-finish herd, influenza infection may persist in the population only if recovered individuals become susceptible to infection again. A homologous vaccine administered to the entire wean-to-finish population after the loss of maternal antibodies eliminates influenza, but a vaccine that only induces partial protection (heterologous vaccine) has little effect on influenza infection levels. Our results have important implications for the control of influenza in swine herds, which is crucial in order to reduce both losses for swine producers and the risk to public health. PMID:25162536

Multiperiod planning tool for multisite pig production systems.

PubMed

Nadal-Roig, E; Plà, L M

2014-09-01

This paper presents a multiperiod planning tool for multisite pig production systems based on Linear Programming (LP). The aim of the model is to help pig managers of multisite systems in making short-term decisions (mainly related to pig transfers between farms and batch management in fattening units) and mid-term or long-term decisions (according to company targets and expansion strategy). The model skeleton follows the structure of a three-site system that can be adapted to any multisite system present in the modern pig industry. There are three basic phases, namely, piglet production, rearing pigs, and fattening. Each phase involves a different set of farms; therefore, transportation between farms and delivering of pigs to the abattoir are under consideration. The model maximizes the total gross margin calculated from the income of sales to the abattoir and the production costs over the time horizon considered. Production cost depends on each type of farm involved in the process. Parameters like number of farms per phase and distance, farm capacity, reproduction management policies, feeding and veterinary expenses, and transportation costs are taken into account. The model also provides a schedule of transfers between farms in terms of animals to be transported and number of trucks involved. The use of the model is illustrated with a case study based on a real instance of a company located in Catalonia (Spain).

A time-series approach for clustering farms based on slaughterhouse health aberration data.

PubMed

Hulsegge, B; de Greef, K H

2018-05-01

A large amount of data is collected routinely in meat inspection in pig slaughterhouses. A time series clustering approach is presented and applied that groups farms based on similar statistical characteristics of meat inspection data over time. A three step characteristic-based clustering approach was used from the idea that the data contain more info than the incidence figures. A stratified subset containing 511,645 pigs was derived as a study set from 3.5 years of meat inspection data. The monthly averages of incidence of pleuritis and of pneumonia of 44 Dutch farms (delivering 5149 batches to 2 pig slaughterhouses) were subjected to 1) derivation of farm level data characteristics 2) factor analysis and 3) clustering into groups of farms. The characteristic-based clustering was able to cluster farms for both lung aberrations. Three groups of data characteristics were informative, describing incidence, time pattern and degree of autocorrelation. The consistency of clustering similar farms was confirmed by repetition of the analysis in a larger dataset. The robustness of the clustering was tested on a substantially extended dataset. This confirmed the earlier results, three data distribution aspects make up the majority of distinction between groups of farms and in these groups (clusters) the majority of the farms was allocated comparable to the earlier allocation (75% and 62% for pleuritis and pneumonia, respectively). The difference between pleuritis and pneumonia in their seasonal dependency was confirmed, supporting the biological relevance of the clustering. Comparison of the identified clusters of statistically comparable farms can be used to detect farm level risk factors causing the health aberrations beyond comparison on disease incidence and trend alone. Copyright © 2018 Elsevier B.V. All rights reserved.

Robustness of near-infrared calibration models for the prediction of milk constituents during the milking process.

PubMed

Melfsen, Andreas; Hartung, Eberhard; Haeussermann, Angelika

2013-02-01

The robustness of in-line raw milk analysis with near-infrared spectroscopy (NIRS) was tested with respect to the prediction of the raw milk contents fat, protein and lactose. Near-infrared (NIR) spectra of raw milk (n = 3119) were acquired on three different farms during the milking process of 354 milkings over a period of six months. Calibration models were calculated for: a random data set of each farm (fully random internal calibration); first two thirds of the visits per farm (internal calibration); whole datasets of two of the three farms (external calibration), and combinations of external and internal datasets. Validation was done either on the remaining data set per farm (internal validation) or on data of the remaining farms (external validation). Excellent calibration results were obtained when fully randomised internal calibration sets were used for milk analysis. In this case, RPD values of around ten, five and three for the prediction of fat, protein and lactose content, respectively, were achieved. Farm internal calibrations achieved much poorer prediction results especially for the prediction of protein and lactose with RPD values of around two and one respectively. The prediction accuracy improved when validation was done on spectra of an external farm, mainly due to the higher sample variation in external calibration sets in terms of feeding diets and individual cow effects. The results showed that further improvements were achieved when additional farm information was added to the calibration set. One of the main requirements towards a robust calibration model is the ability to predict milk constituents in unknown future milk samples. The robustness and quality of prediction increases with increasing variation of, e.g., feeding and cow individual milk composition in the calibration model.

Impacts of Wake Effect and Time Delay on the Dynamic Analysis of Wind Farms Models

ERIC Educational Resources Information Center

El-Fouly, Tarek H. M.; El-Saadany, Ehab F.; Salama, Magdy M. A.

2008-01-01

This article investigates the impacts of proper modeling of the wake effects and wind speed delays, between different wind turbines' rows, on the dynamic performance accuracy of the wind farms models. Three different modeling scenarios were compared to highlight the impacts of wake effects and wind speed time-delay models. In the first scenario,…

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

A field and statistical modeling study to estimate irrigation water use at Benchmark Farms study sites in southwestern Georgia, 1995-96

USGS Publications Warehouse

Fanning, Julia L.; Schwarz, Gregory E.; Lewis, William C.

2001-01-01

A benchmark irrigation monitoring network of farms located in a 32-county area in southwestern Georgia was established in 1995 to improve estimates of irrigation water use. A stratified random sample of 500 permitted irrigators was selected from a data base--maintained by the Georgia Department of Natural Resources, Georgia Environmental Protection Division, Water Resources Management Branch--to obtain 180 voluntary participants in the study area. Site-specific irrigation data were collected at each farm using running-time totalizers and noninvasive flowmeters. Data were collected and compiled for 50 farms for 1995 and 130 additional farms for the 1996 growing season--a total of 180 farms. Irrigation data collected during the 1996 growing season were compiled for 180 benchmark farms and used to develop a statistical model to estimate irrigation water use in 32 counties in southwestern Georgia. The estimates derived were developed from using a statistical approach know as "bootstrap analysis" that allows for the estimation of precision. Five model components--whether-to-irrigate, acres irrigated, crop selected, seasonal-irrigation scheduling, and the amount of irrigation applied--compose the irrigation model and were developed to reflect patterns in the data collected at Benchmark Farms Study area sites. The model estimated that peak irrigation for all counties in the study area occurred during July with significant irrigation also occurring during May, June, and August. Irwin and Tift were the most irrigated and Schley and Houston were the least irrigated counties in the study area. High irrigation intensity primarily was located along the eastern border of the study area; whereas, low irrigation intensity was located in the southwestern quadrant where ground water was the dominant irrigation source. Crop-level estimates showed sizable variations across crops and considerable uncertainty for all crops other than peanuts and pecans. Counties having the most irrigated acres showed higher variations in annual irrigation than counties having the least irrigated acres. The Benchmark Farms Study model estimates were higher than previous irrigation estimates, with 20 percent of the bias a result of underestimating irrigation acreage in earlier studies. Model estimates showed evidence of an upward bias of about 15 percent with the likely cause being a misrepresented inches-applied model. A better understanding of the causes of bias in the model could be determined with a larger irrigation sample size and increased substantially by automating the reporting of monthly totalizer amounts.

Productive and Reproductive Work on the Family Farm: Changes Among Ethnic Groups in Ellis County, Kansas.

ERIC Educational Resources Information Center

Flora, Cornelia Butler; Stitz, John

This report is based on data obtained from historical documents, quantitative analysis of state agricultural censuses for 1885, 1895, and 1905, and interviews with farm women of Volga and German heritages, aged 14 to 87. The participation of women in wheat-based farming systems in Ellis County, Kansas, is examined as related to the ethnic…

Relating the carbon footprint of milk from Irish dairy farms to economic performance.

PubMed

O'Brien, D; Hennessy, T; Moran, B; Shalloo, L

2015-10-01

Mitigating greenhouse gas (GHG) emissions per unit of milk or the carbon footprint (CF) of milk is a key issue for the European dairy sector given rising concerns over the potential adverse effects of climate change. Several strategies are available to mitigate GHG emissions, but producing milk with a low CF does not necessarily imply that a dairy farm is economically viable. Therefore, to understand the relationship between the CF of milk and dairy farm economic performance, the farm accountancy network database of a European Union nation (Ireland) was applied to a GHG emission model. The method used to quantify GHG emissions was life cycle assessment (LCA), which was independently certified to comply with the British standard for LCA. The model calculated annual on- and off-farm GHG emissions from imported inputs (e.g., electricity) up to the point milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk based on the economic value of dairy farm products and expressed per kilogram of fat- and protein-corrected milk (FPCM). The results showed for a nationally representative sample of 221 grass-based Irish dairy farms in 2012 that gross profit averaged € 0.18/L of milk and € 1,758/ha and gross income was € 40,899/labor unit. Net profit averaged € 0.08/L of milk and € 750/ha and net income averaged € 18,125/labor unit. However, significant variability was noted in farm performance across each financial output measure. For instance, net margin per hectare of the top one-third of farms was 6.5 times higher than the bottom third. Financial performance measures were inversely correlated with the CF of milk, which averaged 1.20 kg of CO2-eq/kg of FPCM but ranged from 0.60 to 2.13 kg of CO2-eq/kg of FPCM. Partial least squares regression analysis of correlations between financial and environmental performance indicated that extending the length of the grazing season and increasing milk production per hectare or per cow reduced the CF of milk and increased farm profit. However, where higher milk production per hectare was associated with greater concentrate feeding, this adversely affected the CF of milk and economic performance by increasing both costs and off-farm emissions. Therefore, to mitigate the CF of milk and improve economic performance, grass-based dairy farms should not aim to only increase milk output, but instead target increasing milk production per hectare from grazed grass. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Framework for Statewide Analysis of Site Suitability, Energy Estimation, Life Cycle Costs, Financial Feasibility and Environmental Assessment of Wind Farms: A Case Study of Indiana

NASA Astrophysics Data System (ADS)

Kumar, Indraneel

In the last decade, Midwestern states including Indiana have experienced an unprecedented growth in utility scale wind energy farms. For example, by end of 2013, Indiana had 1.5 GW of wind turbines installed, which could provide electrical energy for as many as half-a-million homes. However, there is no statewide systematic framework available for the evaluation of wind farm impacts on endangered species, required necessary setbacks and proximity standards to infrastructure, and life cycle costs. This research is guided to fill that gap and it addresses the following questions. How much land is suitable for wind farm siting in Indiana given the constraints of environmental, ecological, cultural, settlement, physical infrastructure and wind resource parameters? How much wind energy can be obtained? What are the life cycle costs and economic and financial feasibility? Is wind energy production and development in a state an emission free undertaking? The framework developed in the study is applied to a case study of Indiana. A fuzzy logic based AHP (Analytic Hierarchy Process) spatial site suitability analysis for wind energy is formulated. The magnitude of wind energy that could be sited and installed comprises input for economic and financial feasibility analysis for 20-25 years life cycle of wind turbines in Indiana. Monte Carlo simulation is used to account for uncertainty and nonlinearity in various costs and price parameters. Impacts of incentives and cost variables such as production tax credits, costs of capital, and economies of scale are assessed. Further, an economic input-output (IO) based environmental assessment model is developed for wind energy, where costs from financial feasibility analysis constitute the final demand vectors. This customized model for Indiana is used to assess emissions for criteria air pollutants, hazardous air pollutants and greenhouse gases (GHG) across life cycle events of wind turbines. The findings of the case study include that, Indiana has adequate suitable land area available to locate wind farms with installed capacity between 11 and 51 GW if 100 meters high turbines are used. For a 1.5 MW standard wind turbine, financial feasibility analysis shows that production tax credits and property tax abatements are helpful for financial success in Indiana. Also, the wind energy is not entirely emission free if life cycle events of wind turbine manufacturing, production, installation, construction and decommissioning are considered. The research developed a replicable and integrated framework for statewide life cycle analysis of wind energy production accounting for uncertainty into the analyses. Considering the complexity of life cycle analysis and lack of state specific data on performance of wind turbines and wind farms, this study should be considered an intermediate step.

Estimating Phosphorus Loss at the Whole-Farm Scale with User-Friendly Models

NASA Astrophysics Data System (ADS)

Vadas, P.; Powell, M.; Brink, G.; Busch, D.; Good, L.

2014-12-01

Phosphorus (P) loss from agricultural fields and delivery to surface waters persists as a water quality impairment issue. For dairy farms, P can be lost from cropland, pastures, barnyards, and open-air cattle lots; and all these sources must be evaluated to determine which ones are a priority for P loss remediation. We used interview surveys to document land use, cattle herd characteristics, and manure management for four grazing-based dairy farms in Wisconsin, USA. We then used the APLE and Snap-Plus models to estimate annual P loss from all areas on these farms and determine their relative contribution to whole-farm P loss. At the whole-farm level, average annual P loss (kg ha-1) from grazing-based dairy farms was low (0.6 to 1.8 kg ha-1), generally because a significant portion of land was in permanently vegetated pastures or hay and had low erosion. However, there were areas on the farms that represented sources of significant P loss. For cropland, the greatest P loss was from areas with exposed soil, typically for corn production, and especially on steeper sloping land. The farm areas with the greatest P loss had concentrated animal housing, including barnyards, and over-wintering and young-stock lots. These areas can represent from about 5% to almost 30% of total farm P loss, depending on lot management and P loss from other land uses. Our project builds on research to show that producer surveys can provide reliable management information to assess whole-farm P loss. It also shows that we can use models like RUSLE2, Snap-Plus, and APLE to rapidly, reliably, and quantitatively estimate P loss in runoff from all areas on a dairy farm and identify areas in greatest need of alternative management to reduce P loss.

Factors associated with farm-level infection of porcine epidemic diarrhea during the early phase of the epidemic in Japan in 2013 and 2014.

PubMed

Toyomaki, Haruya; Sekiguchi, Satoshi; Sasaki, Yosuke; Sueyoshi, Masuo; Makita, Kohei

2018-02-01

The objective of this study was to investigate factors that caused rapid spread during the early phase of the porcine epidemic diarrhea (PED) epidemic in Japan in 2013 and 2014. Anonymized datasets from all pig farms were provided by Kagoshima (709 farms) and Miyazaki Prefectures (506 farms). Semi-parametric survival analysis was conducted using the first 180 days from the first case on December 3, 2013 in Kagoshima Prefecture. To compare the hazard between different farm management types, univariable survival analysis was conducted. As farm sizes varied among different farm types, bivariable survival analysis was conducted for farm size categories and farm density per km 2 for each management type. A case-control study using a postal questionnaire survey was conducted in September 2014, and risk factor analysis was performed using generalized linear models with binomial errors. The hazard was significantly higher in farrow-to-finish farms than fattening farms [hazard ratio (HR) = 1.6, p < 0.01], but was not significantly different between reproduction and fattening farms (HR = 1.3, p = 0.16). In separate bivariable survival analyses for each farm type, large- and middle-scale farms had higher hazard than small-scale farms in fattening (HR = 5.8 and 2.6, respectively, both p < 0.01) and reproduction farms (HR = 4.0 and 3.6, respectively, both p < 0.01). In farrow-to-finish farms, large-scale farms had higher hazard than small-scale farms (HR = 2.8, p < 0.01), and higher farm density per km 2 was also a risk factor (HR = 7.6, p < 0.01). In the case-control study, questionnaires were returned from 78 PED virus-infected and 91 non-infected farms. The overall response rate was 34%. Risk factors of the final model were occurrence of porcine reproductive and respiratory syndrome in the past 5 years [odds ratio (OR) = 1.97, 95% confidence interval (CI): 0.97-4.00, p = 0.054], use of a common compost station (OR = 2.51, 95%CI: 1.08-5.83, p = 0.03), and use of a pig excrement disposal service (OR = 2.64, 95%CI: 1.05-6.63, p = 0.04). High hazard in farrow-to-finish farms suggested transmission from slaughterhouses to susceptible suckling piglets. Hazard associated with large-scale farms and high density might be due to frequent vehicle entrance and transmission by roads. Improvement of farm hygiene management and avoidance of risky practices associated with contact with pig excrement were keys in preventing invasion of PED virus to a farm. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling space-time correlations of velocity fluctuations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2018-07-01

An analytical model for the streamwise velocity space-time correlations in turbulent flows is derived and applied to the special case of velocity fluctuations in large wind farms. The model is based on the Kraichnan-Tennekes random sweeping hypothesis, capturing the decorrelation in time while including a mean wind velocity in the streamwise direction. In the resulting model, the streamwise velocity space-time correlation is expressed as a convolution of the pure space correlation with an analytical temporal decorrelation kernel. Hence, the spatio-temporal structure of velocity fluctuations in wind farms can be derived from the spatial correlations only. We then explore the applicability of the model to predict spatio-temporal correlations in turbulent flows in wind farms. Comparisons of the model with data from a large eddy simulation of flow in a large, spatially periodic wind farm are performed, where needed model parameters such as spatial and temporal integral scales and spatial correlations are determined from the large eddy simulation. Good agreement is obtained between the model and large eddy simulation data showing that spatial data may be used to model the full temporal structure of fluctuations in wind farms.

Measuring the environmental effects of organic farming: A meta-analysis of structural variables in empirical research.

PubMed

Lee, Ki Song; Choe, Young Chan; Park, Sung Hee

2015-10-01

This study examined the structural variables affecting the environmental effects of organic farming compared to those of conventional farming. A meta-analysis based on 107 studies and 360 observations published from 1977 to 2012 compared energy efficiency (EE) and greenhouse gas emissions (GHGE) for organic and conventional farming. The meta-analysis systematically analyzed the results of earlier comparative studies and used logistic regression to identify the structural variables that contributed to differences in the effects of organic and conventional farming on the environment. The statistical evidence identified characteristics that differentiated the environmental effects of organic and conventional farming, which is controversial. The results indicated that data sources, sample size and product type significantly affected EE, whereas product type, cropping pattern and measurement unit significantly affected the GHGE of organic farming compared to conventional farming. Superior effects of organic farming on the environment were more likely to appear for larger samples, primary data rather than secondary data, monocropping rather than multicropping, and crops other than fruits and vegetables. The environmental effects of organic farming were not affected by the study period, geographic location, farm size, cropping pattern, or measurement method. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessing the impact of marine wind farms on birds through movement modelling.

PubMed

Masden, Elizabeth A; Reeve, Richard; Desholm, Mark; Fox, Anthony D; Furness, Robert W; Haydon, Daniel T

2012-09-07

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage.

Demonstration of FOODIE spcification on Czech pilot implementation

NASA Astrophysics Data System (ADS)

Charvat, Karel; Reznik, Tomas; Lukas, Vojtěch; Charvat, Karel, Jr.; Horakova, Sarka; Mekotova, Jarmila

2016-04-01

The agriculture sector is a unique sector due to its strategic importance around the world. It is crucial for both citizens (consumers) and economy (regional and global) which, ideally, should make the whole sector a network of interacting organizations. Rural areas are of particular importance with respect to the agri-food and environmental sectors and should be specifically addressed within this scope. The different groups of stakeholders involved in the agricultural and environmental activities have to manage many different and heterogeneous sources of information that need to be combined in order to make economically and environmentally sound decisions, which include (among others) the definition of policies (subsidies, standardization and regulation, national strategies for rural development, climate change), development of sustainable agriculture, ensure crop and animal food production, , pests and diseases detection, etc. In this context, future agriculture knowledge management systems have to support not only direct profitability of agriculture or environment protection, but also activities of individuals and groups allowing efficient collaboration among groups in agri-food industry, consumers, public administrations and wider stakeholders communities, especially in rural domain. Nowadays a various data could be obtained by common farm management. Traditionally, in a plant production this such data brings comprises information about fields, soil conditions and crop treatments. Moreover, data for a plant production also includes, but also sensor data are recorded from a variety of stationary and mobile devices such as farm machines, crop sensors, weather stations, etc. A cloud platform for collection, storage, sharing and analysis of large quantities of spatially and non-spatially referenced data is being developed In the European project "Farm-Oriented Open Data in Europe" (FOODIE) is developed a cloud platform for collection, storage, sharing and analysis of large quantities of spatially and non-spatially referenced data. For data integration of agriculture data FOODIE introduced the open data model. The open data model supported the evidence of all treatments that were used in a certain place as well as (where appropriate) to store relevant information on the application of those treatments. The stored data should together answer the questions like "What amount of which treatment was used in a certain place?", "When it will be safe to apply another treatment?" or "Is the treatment registered and allowed in the European Union/Member State?" The FOODIE data model is based on INSPIRE specification for Agricultural and Aquaculture Facilities., The FOODIE data model is based on the Activity Complex model.. Within INSPIRE, "Activity Complex" denotes a generic name agreed across thematic domains trying to avoid specific thematic connotations such as "Plant", "Installation", "Facility", "Establishment" or "Holding". Such scope may be identified for this paper as the Nitrate Directive or Water Framework Directive A Collection of data was verified on within the FOODIE Czech pilot farm with 1'214 ha of arable land to obtain information about farm machinery management and agro-meteorological observation. Selected tractors and implements were equipped by telemetry units to record vehicle trajectory in the fields and a wireless sensor network was established to observe meteorological conditions within a two fields with cereals. For these such purposes, a novel data model was developed to manage both sensor data and farm records within one platform simultaneously with the client application, which allows end-users to make visualization and analysis of farm data. The Czech Pilot is addressed to improve management and logistic of farms and agriculture service companies, introducing new tools and crop management methods for reduction of environmental burden while maintaining production level. In The Czech pilot machinery and meteorological data has been collected almost 7 months and the data collection process continues. As the first part of project is called proof-of concept stage, we have been experimenting with various settings of monitoring units to find the most suitable values of parameters affecting data collecting frequency. At this moment the volume of collected data is sufficient for purposes of testing FOODIE data model, tools and services. We are now starting to use FOODIE data model to connect the collected data with other farm related information and to define analysis focused on evaluation of economic efficiency of crop production on different fields. Results are now available on http://foodie-data.wirelessinfo.cz/

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Simulation of Turbulent Flow Inside and Above Wind Farms: Model Validation and Layout Effects

NASA Astrophysics Data System (ADS)

Wu, Yu-Ting; Porté-Agel, Fernando

2013-02-01

A recently-developed large-eddy simulation framework is validated and used to investigate turbulent flow within and above wind farms under neutral conditions. Two different layouts are considered, consisting of thirty wind turbines occupying the same total area and arranged in aligned and staggered configurations, respectively. The subgrid-scale (SGS) turbulent stress is parametrized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are modelled using two types of actuator-disk models: (a) the `standard' actuator-disk model (ADM-NR), which calculates only the thrust force based on one-dimensional momentum theory and distributes it uniformly over the rotor area; and (b) the actuator-disk model with rotation (ADM-R), which uses blade-element momentum theory to calculate the lift and drag forces (that produce both thrust and rotation), and distributes them over the rotor disk based on the local blade and flow characteristics. Validation is performed by comparing simulation results with turbulence measurements collected with hot-wire anemometry inside and above an aligned model wind farm placed in a boundary-layer wind tunnel. In general, the ADM-R model yields improved predictions compared with the ADM-NR in the wakes of all the wind turbines, where including turbine-induced flow rotation and accounting for the non-uniformity of the turbine-induced forces in the ADM-R appear to be important. Another advantage of the ADM-R model is that, unlike the ADM-NR, it does not require a priori specification of the thrust coefficient (which varies within a wind farm). Finally, comparison of simulations of flow through both aligned and staggered wind farms shows important effects of farm layout on the flow structure and wind-turbine performance. For the limited-size wind farms considered in this study, the lateral interaction between cumulated wakes is stronger in the staggered case, which results in a farm wake that is more homogeneous in the spanwise direction, thus resembling more an internal boundary layer. Inside the staggered farm, the relatively longer separation between consecutive downwind turbines allows the wakes to recover more, exposing the turbines to higher local wind speeds (leading to higher turbine efficiency) and lower turbulence intensity levels (leading to lower fatigue loads), compared with the aligned farm. Above the wind farms, the area-averaged velocity profile is found to be logarithmic, with an effective wind-farm aerodynamic roughness that is larger for the staggered case.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

Transient stability enhancement of wind farms using power electronics and facts controllers

NASA Astrophysics Data System (ADS)

Mohammadpour, Hossein Ali

Nowadays, it is well-understood that the burning of fossil fuels in electric power station has a significant influence on the global climate due to greenhouse gases. In many countries, the use of cost-effective and reliable low-carbon electricity energy sources is becoming an important energy policy. Among different kinds of clean energy resources- such as solar power, hydro-power, ocean wave power and so on, wind power is the fastest-growing form of renewable energy at the present time. Moreover, adjustable speed generator wind turbines (ASGWT) has key advantages over the fixed-speed generator wind turbines (FSGWT) in terms of less mechanical stress, improved power quality, high system efficiency, and reduced acoustic noise. One important class of ASGWT is the doubly-fed induction generator (DFIG), which has gained a significant attention of the electric power industry due to their advantages over the other class of ASGWT, i.e. fully rated converter-based wind turbines. Because of increased integration of DFIG-based wind farms into electric power grids, it is necessary to transmit the generated power from wind farms to the existing grids via transmission networks without congestion. Series capacitive compensation of DFIG-based wind farm is an economical way to increase the power transfer capability of the transmission line connecting wind farm to the grid. For example, a study performed by ABB reveals that increasing the power transfer capability of an existing transmission line from 1300 MW to 2000 MW using series compensation is 90% less than the cost of building a new transmission line. However, a factor hindering the extensive use of series capacitive compensation is the potential risk of sub- synchronous resonance (SSR). The SSR is a condition where the wind farm exchanges energy with the electric network, to which it is connected, at one or more natural frequencies of the electric or mechanical part of the combined system, comprising the wind farm and the network, and the frequency of the exchanged energy is below the fundamental frequency of the system. This phenomenon may cause severe damage in the wind farm, if not prevented. Therefore, this dissertation deals with the SSR phenomena in a capacitive series compensated wind farm. A DFIG-based wind farm, which is connected to a series compensated transmission line, is considered as a case study. The small-signal stability analysis of the system is presented, and the eigenvalues of the system are obtained. Using both modal analysis and time-domain simulation, it is shown that the system is potentially unstable due to the SSR mode. Then, three different possibilities for the addition of SSR damping controller (SSRDC) are investigated. The SSRDC can be added to (1) gate-controlled series capacitor (GCSC), (2) thyristor-controlled series capacitor (TCSC), or (3) DFIG rotor-side converter (RSC) and grid-side converter (GSC) controllers. The first and second cases are related to the series flexible AC transmission systems (FACTS) family, and the third case uses the DFIG back-to-back converters to damp the SSR. The SSRDC is designed using residue-based analysis and root locus diagrams. Using residue-based analysis, the optimal input control signal (ICS) to the SSRDC is identified that can damp the SSR mode without destabilizing other modes, and using root-locus analysis, the required gain for the SSRDC is determined. Moreover, two methods are discussed in order to estimate the optimum input signal to the SSRDC, without measuring it directly. In this dissertation, MATLAB/Simulink is used as a tool for modeling and design of the SSRDC, and PSCAD/EMTDC is used to perform time-domain simulation in order to verify the design process.

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Analysis of economic values of land use and land cover changes in crisis territories by satellite data: models of socio-economy and population dynamics in war

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Yuschenko, Maxim; Movchan, Dmytro; Kopachevsky, Ivan

2017-10-01

Problem of remote sensing data harnessing for decision making in conflict territories is considered. Approach for analysis of socio-economic and demographic parameters with a limited set of data and deep uncertainty is described. Number of interlinked techniques to estimate a population and economy in crisis territories are proposed. Stochastic method to assessment of population dynamics using multi-source data using remote sensing data is proposed. Adaptive Markov's chain based method to study of land-use changes using satellite data is proposed. Proposed approach is applied to analysis of socio-economic situation in Donbas (East Ukraine) territory of conflict in 2014-2015. Land-use and landcover patterns for different periods were analyzed using the Landsat and MODIS data . The land-use classification scheme includes the following categories: (1) urban or built-up land, (2) barren land, (3) cropland, (4) horticulture farms, (5) livestock farms, (6) forest, and (7) water. It was demonstrated, that during the period 2014-2015 was not detected drastic changes in land-use structure of study area. Heterogeneously distributed decreasing of horticulture farms (4-6%), livestock farms (5-6%), croplands (3-4%), and increasing of barren land (6-7%) have been observed. Way to analyze land-cover productivity variations using satellite data is proposed. Algorithm is based on analysis of time-series of NDVI and NDWI distributions. Drastic changes of crop area and its productivity were detected. Set of indirect indicators, such as night light intensity, is also considered. Using the approach proposed, using the data utilized, the local and regional GDP, local population, and its dynamics are estimated.

Identifying, monitoring and implementing "sustainable" agricultural practices for smallholder farmers over large geographic areas in India and Vietnam

NASA Astrophysics Data System (ADS)

Kritee, K.; Ahuja, R.; Nair, D.; Esteves, T.; Rudek, J.; Thu Ha, T.

2015-12-01

Industrial agriculture systems, mostly in developed and some emerging economies, are far different from the small-holder farms (size <1 acre) in Asia and Africa. Along with our partners from non-governmental, corporate, academic and government sectors and tens of thousands of farming families, we have worked actively in five states in India and two provinces in Vietnam for the last five years to understand how sustainable and climate smart farming practices can be monitored at small-holder farms. Here, any approach to monitor farming must begin by accounting for the tremendous management variability from farm to farm and also the current inability to ground-truth remote sensing data due to lack of relaible basic parameters (e.g., yields, N use, farm boundaries) which are necessary for calibrating empirical/biogeochemical models. While we continue to learn from new research, we have found that it is crucial to follow some steps if sustainable farming programs are to succeed at small-holder farms Demographic data collection and GPS plot demarcation to establish farm size and ownership Baseline nutrient, water & energy use and crop yield determination via surveys and self-reporting which are verifiable through farmer networks given the importance of peer to peer learning in the dissemination of new techniques in such landscapes "Sustainable" practice determination in consultation with local universities/NGO experts Measurements on representative plots for 3-4 years to help calibrate biogeochemical models and/or empirical equations and establish which practices are truly "sustainable" (e.g., GHG emission reduction varies from 0-7 tCO2e/acre for different sustainable practices). Propagation of sustainable practices across the landscape via local NGOs/governments after analyzing the replicability of identified farming practices in the light of local financial, cultural or socio-political barriers. We will present results from representative plots (including soil and weather parameters, GHG emissions, yields, inputs, economic and environmental savings), farmer surveys and diary data; and discuss our key conclusions based on our approach and the analysis of the collected data which was enabled by use of a commercially available comprehensive agricultural data collection software.

Quantitative analysis of antimicrobial use on British dairy farms.

PubMed

Hyde, Robert M; Remnant, John G; Bradley, Andrew J; Breen, James E; Hudson, Christopher D; Davies, Peers L; Clarke, Tom; Critchell, Yvonne; Hylands, Matthew; Linton, Emily; Wood, Erika; Green, Martin J

2017-12-23

Antimicrobial resistance has been reported to represent a growing threat to both human and animal health, and concerns have been raised around levels of antimicrobial usage (AMU) within the livestock industry. To provide a benchmark for dairy cattle AMU and identify factors associated with high AMU, data from a convenience sample of 358 dairy farms were analysed using both mass-based and dose-based metrics following standard methodologies proposed by the European Surveillance of Veterinary Antimicrobial Consumption project. Metrics calculated were mass (mg) of antimicrobial active ingredient per population correction unit (mg/PCU), defined daily doses (DDDvet) and defined course doses (DCDvet). AMU on dairy farms ranged from 0.36 to 97.79 mg/PCU, with a median and mean of 15.97 and 20.62 mg/PCU, respectively. Dose-based analysis ranged from 0.05 to 20.29 DDDvet, with a median and mean of 4.03 and 4.60 DDDvet, respectively. Multivariable analysis highlighted that usage of antibiotics via oral and footbath routes increased the odds of a farm being in the top quartile (>27.9 mg/PCU) of antimicrobial users. While dairy cattle farm AMU appeared to be lower than UK livestock average, there were a selection of outlying farms with extremely high AMU, with the top 25 per cent of farms contributing greater than 50 per cent of AMU by mass. Identification of these high use farms may enable targeted AMU reduction strategies and facilitate a significant reduction in overall dairy cattle AMU. © British Veterinary Association (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

From Wake Steering to Flow Control

DOE PAGES

Fleming, Paul A.; Annoni, Jennifer; Churchfield, Matthew J.; ...

2017-11-22

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

NASA Astrophysics Data System (ADS)

Wang, Chenggen; Zhou, Qian; Han, Mingzhe; Lv, Zhan’ao; Hou, Xiao; Zhao, Haoran; Bu, Jing

2018-04-01

Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.

Modeling and simulation of offshore wind farm O&M processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joschko, Philip, E-mail: joschko@informatik.uni-hamburg.de; Widok, Andi H., E-mail: a.widok@htw-berlin.de; Appel, Susanne, E-mail: susanne.appel@hs-bremen.de

2015-04-15

This paper describes a holistic approach to operation and maintenance (O&M) processes in the domain of offshore wind farm power generation. The acquisition and process visualization is followed by a risk analysis of all relevant processes. Hereafter, a tool was designed, which is able to model the defined processes in a BPMN 2.0 notation, as well as connect and simulate them. Furthermore, the notation was enriched with new elements, representing other relevant factors that were, to date, only displayable with much higher effort. In that regard a variety of more complex situations were integrated, such as for example new processmore » interactions depending on different weather influences, in which case a stochastic weather generator was combined with the business simulation or other wind farm aspects important to the smooth running of the offshore wind farms. In addition, the choices for different methodologies, such as the simulation framework or the business process notation will be presented and elaborated depending on the impact they had on the development of the approach and the software solution. - Highlights: • Analysis of operation and maintenance processes of offshore wind farms • Process modeling with BPMN 2.0 • Domain-specific simulation tool.« less

Ammonia emission model for whole farm evaluation of dairy production systems.

PubMed

Rotz, C Alan; Montes, Felipe; Hafner, Sasha D; Heber, Albert J; Grant, Richard H

2014-07-01

Ammonia (NH) emissions vary considerably among farms as influenced by climate and management. Because emission measurement is difficult and expensive, process-based models provide an alternative for estimating whole farm emissions. A model that simulates the processes of NH formation, speciation, aqueous-gas partitioning, and mass transfer was developed and incorporated in a whole farm simulation model (the Integrated Farm System Model). Farm sources included manure on the floor of the housing facility, manure in storage (if used), field-applied manure, and deposits on pasture (if grazing is used). In a comprehensive evaluation of the model, simulated daily, seasonal, and annual emissions compared well with data measured over 2 yr for five free stall barns and two manure storages on dairy farms in the eastern United States. In a further comparison with published data, simulated and measured barn emissions were similar over differing barn designs, protein feeding levels, and seasons of the year. Simulated emissions from manure storage were also highly correlated with published emission data across locations, seasons, and different storage covers. For field applied manure, the range in simulated annual emissions normally bounded reported mean values for different manure dry matter contents and application methods. Emissions from pastures measured in northern Europe across seasons and fertilization levels were also represented well by the model. After this evaluation, simulations of a representative dairy farm in Pennsylvania illustrated the effects of animal housing and manure management on whole farm emissions and their interactions with greenhouse gas emissions, nitrate leaching, production costs, and farm profitability. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Assessing and managing the health risk due to ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas for general Taiwanese.

PubMed

Liang, Ching-Ping; Liu, Chen-Wuing; Jang, Cheng-Shin; Wang, Sheng-Wei; Lee, Jin-Jing

2011-02-15

This paper assesses health risks due to the ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas by general public in Taiwan. The provisional tolerable weekly intake of arsenic set by FAO/WHO and the target cancer risk assessment model proposed by USEPA were integrated to evaluate the acceptable consumption rate. Five aquacultural species, tilapia (Oreochromis mossambicus), milkfish (Chanos chanos), mullet (Mugil cephalus), clam (Meretrix lusoria) and oyster (Crassostrea gigas) were included. Monte Carlo analysis was used to propagate the parameter uncertainty and to probabilistically assess the health risk associated with the daily intake of inorganic As from farmed fish and shellfish. The integrated risk-based analysis indicates that the associated 50th and 95th percentile health risk are 2.06×10(-5) and 8.77×10(-5), respectively. Moreover, the acceptable intakes of inorganic As are defined and illustrated by a two dimensional graphical model. According to the relationship between C(inorg) and IR(f) derived from this study, two risk-based curves are constructed. An acceptable risk zone is determined (risk ranging from 1×10(-5) to 6.07×10(-5)) which is recommended for acceptable consumption rates of fish and shellfish. To manage the health risk due to the ingestion of inorganic As from fish and shellfish in BFD areas, a risk-based management scheme is derived which provide a convenient way for general public to self-determine the acceptable seafood consumption rate. Copyright © 2010 Elsevier B.V. All rights reserved.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2017-12-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2018-04-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Variations in population exposure and evacuation potential to multiple tsunami evacuation phases on Alameda and Bay Farm Islands, California

NASA Astrophysics Data System (ADS)

Peters, J.

2015-12-01

Planning for a tsunami evacuation is challenging for California communities due to the variety of earthquake sources that could generate a tsunami. A maximum tsunami inundation zone is currently the basis for all tsunami evacuations in California, although an Evacuation Playbook consisting of specific event-based evacuation phases relating to flooding severity is in development. We chose to investigate the Evacuation Playbook approach for the island community of Alameda, CA since past reports estimated a significant difference in numbers of residents in the maximum inundation zone when compared to an event-based inundation zone. In order to recognize variations in the types of residents and businesses within each phase, a population exposure analysis was conducted for each of the four Alameda evacuation phases. A pedestrian evacuation analysis using an anisotropic, path distance model was also conducted to understand the time it would take for populations to reach high ground by foot. Initial results suggest that the two islands of the City of Alameda have different situations when it comes to the four tsunami evacuation phases. Pedestrian evacuation results suggest that Bay Farm Island would have more success evacuating by vehicle due to limited nearby high ground for pedestrians to reach safety. Therefore, agent-based traffic simulation software was used to model vehicle evacuation off Bay Farm Island. Initial results show that Alameda Island could face challenges evacuating numerous boat docks and a large beach for phases 1 and 2, whereas Bay Farm Island is unaffected at these phases but might be challenged with evacuating by vehicle for phases 3 and maximum due to congestion on limited egress routes. A better understanding of the population exposure within each tsunami Evacuation Playbook phase and the time it would take to evacuate out of each phase by foot or vehicle will help emergency managers implement the evacuation phases during an actual tsunami event.

Organic farming enhances soil microbial abundance and activity—A meta-analysis and meta-regression

PubMed Central

Symnaczik, Sarah; Mäder, Paul; De Deyn, Gerlinde; Gattinger, Andreas

2017-01-01

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. PMID:28700609

Verification and Calibration of a Reduced Order Wind Farm Model by Wind Tunnel Experiments

NASA Astrophysics Data System (ADS)

Schreiber, J.; Nanos, E. M.; Campagnolo, F.; Bottasso, C. L.

2017-05-01

In this paper an adaptation of the FLORIS approach is considered that models the wind flow and power production within a wind farm. In preparation to the use of this model for wind farm control, this paper considers the problem of its calibration and validation with the use of experimental observations. The model parameters are first identified based on measurements performed on an isolated scaled wind turbine operated in a boundary layer wind tunnel in various wind-misalignment conditions. Next, the wind farm model is verified with results of experimental tests conducted on three interacting scaled wind turbines. Although some differences in the estimated absolute power are observed, the model appears to be capable of identifying with good accuracy the wind turbine misalignment angles that, by deflecting the wake, lead to maximum power for the investigated layouts.

Environmental and economic comparisons of manure application methods in farming systems.

PubMed

Rotz, C A; Kleinman, P J A; Dell, C J; Veith, T L; Beegle, D B

2011-01-01

Alternative methods for applying livestock manure to no-till soils involve environmental and economic trade-offs. A process-level farm simulation model (Integrated Farm System Model) was used to evaluate methods for applying liquid dairy (Bos taurus L.) and swine (Sus scrofa L.) manure, including no application, broadcast spreading with and without incorporation by tillage, band application with soil aeration, and shallow disk injection. The model predicted ammonia emissions, nitrate leaching, and phosphorus (P) runoff losses similar to those measured over 4 yr of field trials. Each application method was simulated over 25 yr of weather on three Pennsylvania farms. On a swine and cow-calf beef operation under grass production, shallow disk injection increased profit by $340 yr(-1) while reducing ammonia nitrogen and soluble P losses by 48 and 70%, respectively. On a corn (Zea mays L.)-and-grass-based grazing dairy farm, shallow disk injection reduced ammonia loss by 21% and soluble P loss by 76% with little impact on farm profit. Incorporation by tillage and band application with aeration provided less environmental benefit with a net decrease in farm profit. On a large corn-and-alfalfa (Medicago sativa L.)-based dairy farm where manure nutrients were available in excess of crop needs, incorporation methods were not economically beneficial, but they provided environmental benefits with relatively low annual net costs ($13 to $18 cow). In all farming systems, shallow disk injection provided the greatest environmental benefit at the least cost or greatest profit for the producer. With these results, producers are better informed when selecting manure application equipment.

Security region-based small signal stability analysis of power systems with FSIG based wind farm

NASA Astrophysics Data System (ADS)

Qin, Chao; Zeng, Yuan; Yang, Yang; Cui, Xiaodan; Xu, Xialing; Li, Yong

2018-02-01

Based on the Security Region approach, the impact of fixed-speed induction generator based wind farm on the small signal stability of power systems is analyzed. Firstly, the key factors of wind farm on the small signal stability of power systems are analyzed and the parameter space for small signal stability region is formed. Secondly, the small signal stability region of power systems with wind power is established. Thirdly, the corresponding relation between the boundary of SSSR and the dominant oscillation mode is further studied. Results show that the integration of fixed-speed induction generator based wind farm will cause the low frequency oscillation stability of the power system deteriorate. When the output of wind power is high, the oscillation stability of the power system is mainly concerned with the inter-area oscillation mode caused by the integration of the wind farm. Both the active power output and the capacity of reactive power compensation of the wind farm have a significant influence on the SSSR. To improve the oscillation stability of power systems with wind power, it is suggested to reasonably set the reactive power compensation capacity for the wind farm through SSSR.

The relation between input-output transformation and gastrointestinal nematode infections on dairy farms.

PubMed

van der Voort, M; Van Meensel, J; Lauwers, L; Van Huylenbroeck, G; Charlier, J

2016-02-01

Efficiency analysis is used for assessing links between technical efficiency (TE) of livestock farms and animal diseases. However, previous studies often do not make the link with the allocation of inputs and mainly present average effects that ignore the often huge differences among farms. In this paper, we studied the relationship between exposure to gastrointestinal (GI) nematode infections, the TE and the input allocation on dairy farms. Although the traditional cost allocative efficiency (CAE) indicator adequately measures how a given input allocation differs from the cost-minimising input allocation, they do not represent the unique input allocation of farms. Similar CAE scores may be obtained for farms with different input allocations. Therefore, we propose an adjusted allocative efficiency index (AAEI) to measure the unique input allocation of farms. Combining this AAEI with the TE score allows determining the unique input-output position of each farm. The method is illustrated by estimating efficiency scores using data envelopment analysis (DEA) on a sample of 152 dairy farms in Flanders for which both accountancy and parasitic monitoring data were available. Three groups of farms with a different input-output position can be distinguished based on cluster analysis: (1) technically inefficient farms, with a relatively low use of concentrates per 100 l milk and a high exposure to infection, (2) farms with an intermediate TE, relatively high use of concentrates per 100 l milk and a low exposure to infection, (3) farms with the highest TE, relatively low roughage use per 100 l milk and a relatively high exposure to infection. Correlation analysis indicates for each group how the level of exposure to GI nematodes is associated or not with improved economic performance. The results suggest that improving both the economic performance and exposure to infection seems only of interest for highly TE farms. The findings indicate that current farm recommendations regarding GI nematode infections could be improved by also accounting for the allocation of inputs on the farm.

Environmental analysis and monitoring for recreational farms in Taiwan

NASA Astrophysics Data System (ADS)

Chang, Wen-Chuan; Lin, Chun-Nan; Wongchai, Anupong

2017-11-01

The rapid growth of recreational farms and leisure industry has fiercely faced competitive in a Taiwan’s market to achieve business development sustainability trends. Effective business development strategy has become a key of the business performance management to help develop and implement growth opportunities. Recreational farms have functional products, culture, and natural resources as essential elements for the business development of local cuisine. The purpose of this study is, based on the SWOT analysis, to understand the current situation of catering business in recreational farms in Taiwan and to analyze the trends in development to discover how to operate local food restaurant business in recreational farms successfully and create long-term value for a business from customers, markets, and related parties. This research collected a total of 300 questionnaires from recreational farm tourists and excellent recreational farm entrepreneurs, as well as on-site staffs in an outstanding recreational farm. The results of this study provided a reference and guidelines of trends in development for the entrepreneurs to create a modern niche market.

Analysing reduced tillage practices within a bio-economic modelling framework.

PubMed

Townsend, Toby J; Ramsden, Stephen J; Wilson, Paul

2016-07-01

Sustainable intensification of agricultural production systems will require changes in farm practice. Within arable cropping systems, reducing the intensity of tillage practices (e.g. reduced tillage) potentially offers one such sustainable intensification approach. Previous researchers have tended to examine the impact of reduced tillage on specific factors such as yield or weed burden, whilst, by definition, sustainable intensification necessitates a system-based analysis approach. Drawing upon a bio-economic optimisation model, 'MEETA', we quantify trade-off implications between potential yield reductions, reduced cultivation costs and increased crop protection costs. We extend the MEETA model to quantify farm-level net margin, in addition to quantifying farm-level gross margin, net energy, and greenhouse gas emissions. For the lowest intensity tillage system, zero tillage, results demonstrate financial benefits over a conventional tillage system even when the zero tillage system includes yield penalties of 0-14.2% (across all crops). Average yield reductions from zero tillage literature range from 0 to 8.5%, demonstrating that reduced tillage offers a realistic and attainable sustainable intensification intervention, given the financial and environmental benefits, albeit that yield reductions will require more land to compensate for loss of calories produced, negating environmental benefits observed at farm-level. However, increasing uptake of reduced tillage from current levels will probably require policy intervention; an extension of the recent changes to the CAP ('Greening') provides an opportunity to do this.

Assessing the impact of marine wind farms on birds through movement modelling

PubMed Central

Masden, Elizabeth A.; Reeve, Richard; Desholm, Mark; Fox, Anthony D.; Furness, Robert W.; Haydon, Daniel T.

2012-01-01

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were  collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage. PMID:22552921

Prediction of penicillin resistance in Staphylococcus aureus isolates from dairy cows with mastitis, based on prior test results.

PubMed

Grinberg, A; Lopez-Villalobos, N; Lawrence, K; Nulsen, M

2005-10-01

To gauge how well prior laboratory test results predict in vitro penicillin resistance of Staphylococcus aureus isolates from dairy cows with mastitis. Population-based data on the farm of origin (n=79), genotype based on pulsed-field gel electrophoresis (PFGE) results, and the penicillin-resistance status of Staph. aureus isolates (n=115) from milk samples collected from dairy cows with mastitis submitted to two diagnostic laboratories over a 6-month period were used. Data were mined stochastically using the all-possible-pairs method, binomial modelling and bootstrap simulation, to test whether prior test results enhance the accuracy of prediction of penicillin resistance on farms. Of all Staph. aureus isolates tested, 38% were penicillin resistant. A significant aggregation of penicillin-resistance status was evident within farms. The probability of random pairs of isolates from the same farm having the same penicillin-resistance status was 76%, compared with 53% for random pairings of samples across all farms. Thus, the resistance status of randomly selected isolates was 1.43 times more likely to correctly predict the status of other isolates from the same farm than the random population pairwise concordance probability (p=0.011). This effect was likely due to the clonal relationship of isolates within farms, as the predictive fraction attributable to prior test results was close to nil when the effect of within-farm clonal infections was withdrawn from the model. Knowledge of the penicillin-resistance status of a prior Staph. aureus isolate significantly enhanced the predictive capability of other isolates from the same farm. In the time and space frame of this study, clinicians using previous information from a farm would have more accurately predicted the penicillin-resistance status of an isolate than they would by chance alone on farms infected with clonal Staph. aureus isolates, but not on farms infected with highly genetically heterogeneous bacterial strains.

Simplified formulae for the estimation of offshore wind turbines clutter on marine radars.

PubMed

Grande, Olatz; Cañizo, Josune; Angulo, Itziar; Jenn, David; Danoon, Laith R; Guerra, David; de la Vega, David

2014-01-01

The potential impact that offshore wind farms may cause on nearby marine radars should be considered before the wind farm is installed. Strong radar echoes from the turbines may degrade radars' detection capability in the area around the wind farm. Although conventional computational methods provide accurate results of scattering by wind turbines, they are not directly implementable in software tools that can be used to conduct the impact studies. This paper proposes a simple model to assess the clutter that wind turbines may generate on marine radars. This method can be easily implemented in the system modeling software tools for the impact analysis of a wind farm in a real scenario.

Simplified Formulae for the Estimation of Offshore Wind Turbines Clutter on Marine Radars

PubMed Central

Grande, Olatz; Cañizo, Josune; Jenn, David; Danoon, Laith R.; Guerra, David

2014-01-01

The potential impact that offshore wind farms may cause on nearby marine radars should be considered before the wind farm is installed. Strong radar echoes from the turbines may degrade radars' detection capability in the area around the wind farm. Although conventional computational methods provide accurate results of scattering by wind turbines, they are not directly implementable in software tools that can be used to conduct the impact studies. This paper proposes a simple model to assess the clutter that wind turbines may generate on marine radars. This method can be easily implemented in the system modeling software tools for the impact analysis of a wind farm in a real scenario. PMID:24782682

Fishing Farmers or Farming Fishers? Fishing Typology of Inland Small-Scale Fishing Households and Fisheries Management in Singkarak Lake, West Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Yuerlita; Perret, Sylvain Roger; Shivakoti, Ganesh P.

2013-07-01

Technical and socio-economic characteristics are known to determine different types of fishers and their livelihood strategies. Faced with declining fish and water resources, small-scale fisheries engage into transformations in livelihood and fishing practices. The paper is an attempt to understand these changes and their socio-economic patterns, in the case of Singkarak Lake in West Sumatra, Indonesia. Based upon the hypothesis that riparian communities have diverse, complex yet structured and dynamic livelihood systems, the paper's main objective is to study, document and model the actual diversity in livelihood, practices and performance of inland small-scale fisheries along the Singkarak Lake, to picture how households are adapted to the situation, and propose an updated, workable model (typology) of those for policy. Principal component analysis and cluster analysis were used to develop a typology of fishing households. The results show that small-scale fishers can be classified into different types characterized by distinct livelihood strategies. Three household types are identified, namely "farming fishers" households (type I, 30 %), "fishing farmers" households (type II, 30 %), and "mainly fishers" households (type III, 40 %). There are significant differences among these groups in the number of boats owned, annual fishing income, agriculture income and farming experience. Type I consists of farming fishers, well equipped, with high fishing costs and income, yet with the lowest return on fishing assets. They are also landowners with farming income, showing the lowest return on land capital. Type II includes poor fishing farmers, landowners with higher farming income; they show the highest return on land asset. They have less fishing equipment, costs and income. Type III (mainly fishers) consists of poorer, younger fishers, with highest return on fishing assets and on fishing costs. They have little land, low farming income, and diversified livelihood sources. The nature of their livelihood strategies is discussed for each identified group. This helps to understand the complexity and diversity of small-scale fishers, particularly in the study area which is still poorly known. This paper concludes with policy implication and possible management initiatives for environmentally prudent policy aiming at improvement of fishers' livelihood.

Fishing farmers or farming fishers? Fishing typology of inland small-scale fishing households and fisheries management in singkarak lake, west sumatra, indonesia.

PubMed

Yuerlita; Perret, Sylvain Roger; Shivakoti, Ganesh P

2013-07-01

Technical and socio-economic characteristics are known to determine different types of fishers and their livelihood strategies. Faced with declining fish and water resources, small-scale fisheries engage into transformations in livelihood and fishing practices. The paper is an attempt to understand these changes and their socio-economic patterns, in the case of Singkarak Lake in West Sumatra, Indonesia. Based upon the hypothesis that riparian communities have diverse, complex yet structured and dynamic livelihood systems, the paper's main objective is to study, document and model the actual diversity in livelihood, practices and performance of inland small-scale fisheries along the Singkarak Lake, to picture how households are adapted to the situation, and propose an updated, workable model (typology) of those for policy. Principal component analysis and cluster analysis were used to develop a typology of fishing households. The results show that small-scale fishers can be classified into different types characterized by distinct livelihood strategies. Three household types are identified, namely "farming fishers" households (type I, 30 %), "fishing farmers" households (type II, 30 %), and "mainly fishers" households (type III, 40 %). There are significant differences among these groups in the number of boats owned, annual fishing income, agriculture income and farming experience. Type I consists of farming fishers, well equipped, with high fishing costs and income, yet with the lowest return on fishing assets. They are also landowners with farming income, showing the lowest return on land capital. Type II includes poor fishing farmers, landowners with higher farming income; they show the highest return on land asset. They have less fishing equipment, costs and income. Type III (mainly fishers) consists of poorer, younger fishers, with highest return on fishing assets and on fishing costs. They have little land, low farming income, and diversified livelihood sources. The nature of their livelihood strategies is discussed for each identified group. This helps to understand the complexity and diversity of small-scale fishers, particularly in the study area which is still poorly known. This paper concludes with policy implication and possible management initiatives for environmentally prudent policy aiming at improvement of fishers' livelihood.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doubrawa Moreira, Paula; Annoni, Jennifer; Jonkman, Jason

FAST.Farm is a medium-delity wind farm modeling tool that can be used to assess power and loads contributions of wind turbines in a wind farm. The objective of this paper is to undertake a calibration procedure to set the user parameters of FAST.Farm to accurately represent results from large-eddy simulations. The results provide an in- depth analysis of the comparison of FAST.Farm and large-eddy simulations before and after calibration. The comparison of FAST.Farm and large-eddy simulation results are presented with respect to streamwise and radial velocity components as well as wake-meandering statistics (mean and standard deviation) in the lateral andmore » vertical directions under different atmospheric and turbine operating conditions.« less

AN EVALUATION OF HANFORD SITE TANK FARM SUBSURFACE CONTAMINATION FY2007

DOE Office of Scientific and Technical Information (OSTI.GOV)

MANN, F.M.

2007-07-10

The Tank Farm Vadose Zone (TFVZ) Project conducts activities to characterize and analyze the long-term environmental and human health impacts from tank waste releases to the vadose zone. The project also implements interim measures to mitigate impacts, and plans the remediation of waste releases from tank farms and associated facilities. The scope of this document is to report data needs that are important to estimating long-term human health and environmental risks. The scope does not include technologies needed to remediate contaminated soils and facilities, technologies needed to close tank farms, or management and regulatory decisions that will impact remediation andmore » closure. This document is an update of ''A Summary and Evaluation of Hanford Site Tank Farm Subsurface Contamination''. That 1998 document summarized knowledge of subsurface contamination beneath the tank farms at the time. It included a preliminary conceptual model for migration of tank wastes through the vadose zone and an assessment of data and analysis gaps needed to update the conceptual model. This document provides a status of the data and analysis gaps previously defined and discussion of the gaps and needs that currently exist to support the stated mission of the TFVZ Project. The first data-gaps document provided the basis for TFVZ Project activities over the previous eight years. Fourteen of the nineteen knowledge gaps identified in the previous document have been investigated to the point that the project defines the current status as acceptable. In the process of filling these gaps, significant accomplishments were made in field work and characterization, laboratory investigations, modeling, and implementation of interim measures. The current data gaps are organized in groups that reflect Components of the tank farm vadose zone conceptual model: inventory, release, recharge, geohydrology, geochemistry, and modeling. The inventory and release components address residual wastes that will remain in the tanks and tank-farm infrastructure after closure and potential losses from leaks during waste retrieval. Recharge addresses the impacts of current conditions in the tank farms (i.e. gravel covers that affect infiltration and recharge) as well as the impacts of surface barriers. The geohydrology and geochemistry components address the extent of the existing subsurface contaminant inventory and drivers and pathways for contaminants to be transported through the vadose zone and groundwater. Geochemistry addresses the mobility of key reactive contaminants such as uranium. Modeling addresses conceptual models and how they are simulated in computers. The data gaps will be used to provide input to planning (including the upcoming C Farm Data Quality Objective meetings scheduled this year).« less

Factors associated with profitability in pasture-based systems of milk production.

PubMed

Hanrahan, L; McHugh, N; Hennessy, T; Moran, B; Kearney, R; Wallace, M; Shalloo, L

2018-06-01

The global dairy industry needs to reappraise the systems of milk production that are operated at farm level with specific focus on enhancing technical efficiency and competitiveness of the sector. The objective of this study was to quantify the factors associated with costs of production, profitability, and pasture use, and the effects of pasture use on financial performance of dairy farms using an internationally recognized representative database over an 8-yr period (2008 to 2015) on pasture-based systems. To examine the associated effects of several farm system and management variables on specific performance measures, a series of multiple regression models were developed. Factors evaluated included pasture use [kg of dry matter/ha and stocking rate (livestock units/ha)], grazing season length, breeding season length, milk recording, herd size, dairy farm size (ha), farmer age, discussion group membership, proportion of purchased feed, protein %, fat %, kg of milk fat and protein per cow, kg of milk fat and protein per hectare, and capital investment in machinery, livestock, and buildings. Multiple regression analysis demonstrated costs of production per hectare differed by year, geographical location, soil type, level of pasture use, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, breeding season length, and capital investment in machinery, livestock, and buildings per cow. The results of the analysis revealed that farm net profit per hectare was associated with pasture use per hectare, year, location, soil type, grazing season length, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, and capital investment in machinery and buildings per cow. Pasture use per hectare was associated with year, location, soil type, stocking rate, dairy farm size, fat %, protein %, kg of fat and protein per cow, farmer age, capital investment in machinery and buildings per cow, breeding season length, and discussion group membership. On average, over the 8-yr period, each additional tonne of pasture dry matter used increased gross profit by €278 and net profit by €173 on dairy farms. Conversely, a 10% increase in the proportion of purchased feed in the diet resulted in a reduction in net profit per hectare by €97 and net profit by €207 per tonne of fat and protein. Results from this study, albeit in a quota limited environment, have demonstrated that the profitability of pasture-based dairy systems is significantly associated with the proportion of pasture used at the farm level, being cognizant of the levels of purchased feed. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Factors Associated with Salmonella Prevalence in U.S. Swine Grower-Finisher Operations, 2012.

PubMed

Bjork, Kathe E; Fields, Victoria; Garber, Lindsey P; Kopral, Christine A

2018-05-15

Nontyphoidal Salmonella is an important foodborne pathogen with diverse serotypes occurring in animal and human populations. The prevalence of the organism on swine farms has been associated with numerous risk factors, and although there are strong veterinary public health controls for preventing Salmonella from entering food, there remains interest in eradicating or controlling the organism in the preharvest environment. In this study, using data collected via the U.S. Department of Agriculture (USDA) National Animal Health Monitoring System Swine 2012 study, we describe nontyphoidal Salmonella and specific serotype prevalence on U.S. grower-finisher swine operations and investigate associations between Salmonella detection and numerous factors via multiple correspondence analysis (MCA) and regression analysis. MCA plots, complementary to univariate analyses, display relationships between covariates and Salmonella detection at the farm level. In the univariate analysis, Salmonella detection varied with feed characteristics and farm management practices, reports of diseases on farms and vaccinations administered, and administration of certain antimicrobials. Results from the univariate analysis reinforce the importance of biosecurity in managing diseases and pathogens such as Salmonella on farms. All multivariable regression models for the likelihood of Salmonella detection were strongly affected by multicollinearity among variables, and only one variable, pelleted feed preparation, remained in the final model. The study was limited by its cross-sectional nature, timelines of data collection, and reliance on operator-reported data via a convenience sample.

Simulation of wake effects between two wind farms

NASA Astrophysics Data System (ADS)

Hansen, K. S.; Réthoré, P.-E.; Palma, J.; Hevia, B. G.; Prospathopoulos, J.; Peña, A.; Ott, S.; Schepers, G.; Palomares, A.; van der Laan, M. P.; Volker, P.

2015-06-01

SCADA data, recorded on the downstream wind farm, has been used to identify flow cases with visible clustering effects. The inflow condition is derived from a partly undisturbed wind turbine, due to lack of mast measurements. The SCADA data analysis concludes that centre of the deficit for the downstream wind farm with disturbed inflow has a distinct visible maximum deficit zone located only 5-10D downstream from the entrance. This zone, representing 20-30% speed reduction, increases and moves downstream for increasing cluster effect and is not visible outside a flow sector of 20-30°. The eight flow models represented in this benchmark include both RANS models, mesoscale models and engineering models. The flow cases, identified according to the wind speed level and inflow sector, have been simulated and validated with the SCADA results. The model validation concludes that all models more or less are able to predict the location and size of the deficit zone inside the downwind wind farm.

Farm-economic analysis of reducing antimicrobial use whilst adopting improved management strategies on farrow-to-finish pig farms.

PubMed

Rojo-Gimeno, Cristina; Postma, Merel; Dewulf, Jeroen; Hogeveen, Henk; Lauwers, Ludwig; Wauters, Erwin

2016-07-01

Due to increasing public health concerns that food animals could be reservoirs for antibiotic resistant organisms, calls for reduced current antibiotic use on farms are growing. Nevertheless, it is challenging for farmers to perform this reduction without negatively affecting technical and economic performance. As an alternative, improved management practices based on biosecurity and vaccinations have been proven useful to reduce antimicrobial use without lowering productivity, but issues with insufficient experimental design possibilities have hindered economic analysis. In the present study a quasi-experimental approach was used for assessing the economic impact of reduction of antimicrobial use coupled with improved management strategies, particularly biosecurity strategies. The research was performed on farrow-to-finish pig farms in Flanders (northern region of Belgium). First, to account for technological progress and to avoid selection bias, propensity score analysis was used to compare data on technical parameters. The treatment group (n=48) participated in an intervention study whose aim was to improve management practices to reduce the need for use of antimicrobials. Before and after the change in management, data were collected on the technical parameters, biosecurity status, antimicrobial use, and vaccinations. Treated farms were matched without replacement with control farms (n=69), obtained from the Farm Accountancy Data Network, to estimate the difference in differences (DID) of the technical parameters. Second, the technical parameters' DID, together with the estimated costs of the management intervention and the price volatility of the feed, meat of the finisher pigs, and piglets served as a basis for modelling the profit of 11 virtual farrow-to-finish pig farms representative of the Flemish sector. Costs incurred by new biosecurity measures (median +€3.96/sow/year), and new vaccinations (median €0.00/sow/year) did not exceed the cost reduction achieved by lowering the use of antimicrobials (median -€7.68/sow/year). No negative effect on technical parameters was observed and mortality of the finishers was significantly reduced by -1.1%. Even after a substantial reduction of the antimicrobial treatments, the difference of the enterprise profit increased by +€2.67/finisher pig/year after implementing the interventions. This result proved to be robust after stochastic modelling of input and output price volatility. The results of this study can be used by veterinarians and other stakeholders to incentivise managers of farrow-to-finish operations to use biosecurity practices as a cost-effective way to reduce antimicrobial use. Copyright © 2016 Elsevier B.V. All rights reserved.

Cluster Analysis of Campylobacter jejuni Genotypes Isolated from Small and Medium-Sized Mammalian Wildlife and Bovine Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M

2017-05-01

Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Toxicokinetics/toxicodynamics of arsenic for farmed juvenile milkfish Chanos chanos and human consumption risk in BFD-endemic area of Taiwan.

PubMed

Chou, Berry Yun-Hua; Liao, Chung-Min; Lin, Ming-Chao; Cheng, Hsu-Hui

2006-05-01

This paper presents a toxicokinetic/toxicodynamic analysis to appraise arsenic (As) bioaccumulation in farmed juvenile milkfish Chanos chanos at blackfoot disease (BFD)-endemic area in Taiwan, whereas probabilistic incremental lifetime cancer risk (ILCR) and hazard quotient (HQ) models are also employed to assess the range of exposures for the fishers and non-fishers who eat the contaminated fish. We conducted a 7-day exposure experiment to obtain toxicokinetic parameters, whereas a simple critical body burden toxicity model was verified with LC50(t) data obtained from a 7-day acute toxicity bioassay. Acute toxicity bioassay indicates that 96-h LC50 for juvenile milkfish exposed to As is 7.29 (95% CI: 3.10-10.47) mg l(-1). Our risk analysis for milkfish reared in BFD-endemic area indicates a low likelihood that survival is being affected by waterborne As. Human risk analysis demonstrates that 90%-tile probability exposure ILCRs for fishers in BFD-endemic area have orders of magnitude of 10(-3), indicating a high potential carcinogenic risk, whereas there is no significant cancer risk for non-fishers (ILCRs around 10(-5)). All predicted 90%-tiles of HQ are less than 1 for non-fishers, yet larger than 10 for fishers which indicate larger contributions from farmed milkfish consumptions. Sensitivity analysis indicates that to increase the accuracy of the results, efforts should focus on a better definition of probability distributions for milkfish daily consumption rate and As level in milkfish. Here we show that theoretical human health risks for consuming As-contaminated milkfish in the BFD-endemic area are alarming under a conservative condition based on a probabilistic risk assessment model.

Regenerative agriculture: merging farming and natural resource conservation profitably.

PubMed

LaCanne, Claire E; Lundgren, Jonathan G

2018-01-01

Most cropland in the United States is characterized by large monocultures, whose productivity is maintained through a strong reliance on costly tillage, external fertilizers, and pesticides (Schipanski et al., 2016). Despite this, farmers have developed a regenerative model of farm production that promotes soil health and biodiversity, while producing nutrient-dense farm products profitably. Little work has focused on the relative costs and benefits of novel regenerative farming operations, which necessitates studying in situ , farmer-defined best management practices. Here, we evaluate the relative effects of regenerative and conventional corn production systems on pest management services, soil conservation, and farmer profitability and productivity throughout the Northern Plains of the United States. Regenerative farming systems provided greater ecosystem services and profitability for farmers than an input-intensive model of corn production. Pests were 10-fold more abundant in insecticide-treated corn fields than on insecticide-free regenerative farms, indicating that farmers who proactively design pest-resilient food systems outperform farmers that react to pests chemically. Regenerative fields had 29% lower grain production but 78% higher profits over traditional corn production systems. Profit was positively correlated with the particulate organic matter of the soil, not yield. These results provide the basis for dialogue on ecologically based farming systems that could be used to simultaneously produce food while conserving our natural resource base: two factors that are pitted against one another in simplified food production systems. To attain this requires a systems-level shift on the farm; simply applying individual regenerative practices within the current production model will not likely produce the documented results.

Estimating the effect of mastitis on the profitability of Irish dairy farms.

PubMed

Geary, U; Lopez-Villalobos, N; Begley, N; McCoy, F; O'Brien, B; O'Grady, L; Shalloo, L

2012-07-01

The objective of this paper was to estimate the effect of the costs of mastitis on the profitability of Irish dairy farms as indicated by various ranges of bulk milk somatic cell count (BMSCC). Data were collected from 4 sources and included milk production losses, cases treated, and on-farm practices around mastitis management. The Moorepark Dairy Systems Model, which simulates dairying systems inside the farm gate, was used to carry out the analysis. The cost components of mastitis that affect farm profitability and that were included in the model were milk losses, culling, diagnostic testing, treatment, veterinary attention, discarded milk, and penalties. Farms were grouped by 5 BMSCC thresholds of ≤ 100,000, 100,001-200,000, 200,001-300,000, 300,001-400,000, and > 400,000 cells/mL. The ≤ 100,000 cells/mL threshold was taken as the baseline and the other 4 thresholds were compared relative to this baseline. For a 40-ha farm, the analysis found that as BMSCC increased, milk receipts decreased from €148,843 at a BMSCC <100,000 cells/mL to €138,573 at a BMSCC > 400,000 cells/mL. In addition, as BMSCC increased, livestock receipts increased by 17%, from €43,304 at a BMSCC <100,000 cells/mL to €50,519 at a BMSCC > 400,000 cells/mL. This reflected the higher replacement rates as BMSCC increased and the associated cull cow value. Total farm receipts decreased from €192,147 at the baseline (< 100,000 cells/mL) to €189,091 at a BMSCC > 400,000 cells/mL. Total farm costs increased as BMSCC increased, reflecting treatment, veterinary, diagnostic testing, and replacement heifer costs. At the baseline, total farm costs were €161,085, increasing to €177,343 at a BMSCC > 400,000 cells/mL. Net farm profit decreased as BMSCC increased, from €31,252/yr at the baseline to €11,748/yr at a BMSCC > 400,000 cells/mL. This analysis highlights the impact that mastitis has on the profitability of Irish dairy farms. The analysis presented here can be used to develop a "cost of mastitis" tool for use on Irish dairy farms to motivate farmers to acknowledge the scale of the problem, realize the value of improving mastitis control, and implement effective mastitis control practices. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Benthic processes and coastal aquaculture: merging models and field data at a local scale

NASA Astrophysics Data System (ADS)

Brigolin, Daniele; Rabouille, Christophe; Bombled, Bruno; Colla, Silvia; Pastres, Roberto; Pranovi, Fabio

2016-04-01

Shellfish farming is regarded as an organic extractive aquaculture activity. However, the production of faeces and pseudofaeces, in fact, leads to a net transfer of organic matter from the water column to the surface sediment. This process, which is expected to locally affect the sediment biogeochemistry, may also cause relevant changes in coastal areas characterized by a high density of farms. In this paper, we present the result of a study recently carried out in the Gulf of Venice (northern Adriatic sea), combining mathematical modelling and field sampling efforts. The work aimed at using a longline mussel farm as an in-situ test-case for modelling the differences in soft sediments biogeochemical processes along a gradient of organic deposition. We used an existing integrated model, allowing to describe biogeochemical fluxes towards the mussel farm and to predict the extent of the deposition area underneath it. The model framework includes an individual-based population dynamic model of the Mediterranean mussel coupled with a Lagrangian deposition model and a 1D benthic model of early diagenesis. The work was articulated in 3 steps: 1) the integrated model allowed to simulate the downward fluxes of organic matter originated by the farm, and the extent of its deposition area; 2) based on the first model application, two stations were localized, at which sediment cores were collected during a field campaign, carried out in June 2015. Measurements included O2 and pH microprofiling, porosity and micro-porosity, Total Organic Carbon, and pore waters NH4, PO4, SO4, Alkalinity, and Dissolved Inorganic Carbon; 3) two distinct early diagenesis models were set-up, reproducing observed field data in the sampled cores. Observed oxygen microprofiles showed a different behavior underneath the farm with respect to the outside reference station. In particular, a remarkable decrease in the oxygen penetration depth, and an increase in the O2 influx calculated from the concentration gradients were observed. The integrated model described above allowed to extend the simulation over the entire farmed area, and to explore the response of the prediction to changes in water temperature.

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew; ...

2018-05-14

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

Implementation and validation of an economic module in the Be-FAST model to predict costs generated by livestock disease epidemics: Application to classical swine fever epidemics in Spain.

PubMed

Fernández-Carrión, E; Ivorra, B; Martínez-López, B; Ramos, A M; Sánchez-Vizcaíno, J M

2016-04-01

Be-FAST is a computer program based on a time-spatial stochastic spread mathematical model for studying the transmission of infectious livestock diseases within and between farms. The present work describes a new module integrated into Be-FAST to model the economic consequences of the spreading of classical swine fever (CSF) and other infectious livestock diseases within and between farms. CSF is financially one of the most damaging diseases in the swine industry worldwide. Specifically in Spain, the economic costs in the two last CSF epidemics (1997 and 2001) reached jointly more than 108 million euros. The present analysis suggests that severe CSF epidemics are associated with significant economic costs, approximately 80% of which are related to animal culling. Direct costs associated with control measures are strongly associated with the number of infected farms, while indirect costs are more strongly associated with epidemic duration. The economic model has been validated with economic information around the last outbreaks in Spain. These results suggest that our economic module may be useful for analysing and predicting economic consequences of livestock disease epidemics. Copyright © 2016 Elsevier B.V. All rights reserved.

Antimicrobial Resistance of Faecal Escherichia coli Isolates from Pig Farms with Different Durations of In-feed Antimicrobial Use.

PubMed

Gibbons, J F; Boland, F; Egan, J; Fanning, S; Markey, B K; Leonard, F C

2016-05-01

Antimicrobial use and resistance in animal and food production are of concern to public health. The primary aims of this study were to determine the frequency of resistance to 12 antimicrobials in Escherichia coli isolates from 39 pig farms and to identify patterns of antimicrobial use on these farms. Further aims were to determine whether a categorization of farms based on the duration of in-feed antimicrobial use (long-term versus short-term) could predict the occurrence of resistance on these farms and to identify the usage of specific antimicrobial drugs associated with the occurrence of resistance. Escherichia coli were isolated from all production stages on these farms; susceptibility testing was carried out against a panel of antimicrobials. Antimicrobial prescribing data were collected, and farms were categorized as long term or short term based on these. Resistance frequencies and antimicrobial use were tabulated. Logistic regression models of resistance to each antimicrobial were constructed with stage of production, duration of antimicrobial use and the use of 5 antimicrobial classes included as explanatory variables in each model. The greatest frequencies of resistance were observed to tetracycline, trimethoprim/sulphamethoxazole and streptomycin with the highest levels of resistance observed in isolates from first-stage weaned pigs. Differences in the types of antimicrobial drugs used were noted between long-term and short-term use farms. Categorization of farms as long- or short-term use was sufficient to predict the likely occurrence of resistance to 3 antimicrobial classes and could provide an aid in the control of resistance in the food chain. Stage of production was a significant predictor variable in all models of resistance constructed and did not solely reflect antimicrobial use at each stage. Cross-selection and co-selection for resistance was evident in the models constructed, and the use of trimethoprim/sulphonamide drugs in particular was associated with the occurrence of resistance to other antimicrobials. © 2015 Blackwell Verlag GmbH.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Data Farming and Defense Applications

NASA Technical Reports Server (NTRS)

Horne, Gary; Meyer, Ted

2011-01-01

.Data farm,ing uses simulation modeling, high performance computing, experimental design and analysis to examine questions of interest with large possibility spaces. This methodology allows for the examination of whole landscapes of potential outcomes and provides the capability of executing enough experiments so that outliers might be captured and examined for insights. It can be used to conduct sensitivity studies, to support validation and verification of models, to iteratively optimize outputs using heuristic search and discovery, and as an aid to decision-makers in understanding complex relationships of factors. In this paper we describe efforts at the Naval Postgraduate School in developing these new and emerging tools. We also discuss data farming in the context of application to questions inherent in military decision-making. The particular application we illustrate here is social network modeling to support the countering of improvised explosive devices.

Maximum capacity model of grid-connected multi-wind farms considering static security constraints in electrical grids

NASA Astrophysics Data System (ADS)

Zhou, W.; Qiu, G. Y.; Oodo, S. O.; He, H.

2013-03-01

An increasing interest in wind energy and the advance of related technologies have increased the connection of wind power generation into electrical grids. This paper proposes an optimization model for determining the maximum capacity of wind farms in a power system. In this model, generator power output limits, voltage limits and thermal limits of branches in the grid system were considered in order to limit the steady-state security influence of wind generators on the power system. The optimization model was solved by a nonlinear primal-dual interior-point method. An IEEE-30 bus system with two wind farms was tested through simulation studies, plus an analysis conducted to verify the effectiveness of the proposed model. The results indicated that the model is efficient and reasonable.

Farm systems assessment of bioenergy feedstock production: Integrating bio-economic models and life cycle analysis approaches

PubMed Central

Glithero, N.J.; Ramsden, S.J.; Wilson, P.

2012-01-01

Climate change and energy security concerns have driven the development of policies that encourage bioenergy production. Meeting EU targets for the consumption of transport fuels from bioenergy by 2020 will require a large increase in the production of bioenergy feedstock. Initially an increase in ‘first generation’ biofuels was observed, however ‘food competition’ concerns have generated interest in second generation biofuels (SGBs). These SGBs can be produced from co-products (e.g. cereal straw) or energy crops (e.g. miscanthus), with the former largely negating food competition concerns. In order to assess the sustainability of feedstock supply for SGBs, the financial, environmental and energy costs and benefits of the farm system must be quantified. Previous research has captured financial costs and benefits through linear programming (LP) approaches, whilst environmental and energy metrics have been largely been undertaken within life cycle analysis (LCA) frameworks. Assessing aspects of the financial, environmental and energy sustainability of supplying co-product second generation biofuel (CPSGB) feedstocks at the farm level requires a framework that permits the trade-offs between these objectives to be quantified and understood. The development of a modelling framework for Managing Energy and Emissions Trade-Offs in Agriculture (MEETA Model) that combines bio-economic process modelling and LCA is presented together with input data parameters obtained from literature and industry sources. The MEETA model quantifies arable farm inputs and outputs in terms of financial, energy and emissions results. The model explicitly captures fertiliser: crop-yield relationships, plus the incorporation of straw or removal for sale, with associated nutrient impacts of incorporation/removal on the following crop in the rotation. Key results of crop-mix, machinery use, greenhouse gas (GHG) emissions per kg of crop product and energy use per hectare are in line with previous research and industry survey findings. Results show that the gross margin – energy trade-off is £36 GJ−1, representing the gross margin forgone by maximising net farm energy cf. maximising farm gross margin. The gross margin–GHG emission trade-off is £0.15 kg−1 CO2 eq, representing the gross margin forgone per kg of CO2 eq reduced when GHG emissions are minimised cf. maximising farm gross margin. The energy–GHG emission trade-off is 0.03 GJ kg−1 CO2 eq quantifying the reduction in net energy from the farm system per kg of CO2 eq reduced when minimising GHG emissions cf. maximising net farm energy. When both farm gross margin and net farm energy are maximised all the cereal straw is baled for sale. Sensitivity analysis of the model in relation to different prices of cereal straw shows that it becomes financially optimal to incorporate wheat straw at price of £11 t−1 for this co-product. Local market conditions for straw and farmer attitudes towards incorporation or sale of straw will impact on the straw price at which farmers will supply this potential bioenergy feedstock and represent important areas for future research. PMID:25540473

A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

PubMed

Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

2017-08-01

The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Developing web-based data analysis tools for precision farming using R and Shiny

NASA Astrophysics Data System (ADS)

Jahanshiri, Ebrahim; Mohd Shariff, Abdul Rashid

2014-06-01

Technologies that are set to increase the productivity of agricultural practices require more and more data. Nevertheless, farming data is also being increasingly cheap to collect and maintain. Bulk of data that are collected by the sensors and samples need to be analysed in an efficient and transparent manner. Web technologies have long being used to develop applications that can assist the farmers and managers. However until recently, analysing the data in an online environment has not been an easy task especially in the eyes of data analysts. This barrier is now overcome by the availability of new application programming interfaces that can provide real-time web based data analysis. In this paper developing a prototype web based application for data analysis using new facilities in R statistical package and its web development facility, Shiny is explored. The pros and cons of this type of data analysis environment for precision farming are enumerated and future directions in web application development for agricultural data are discussed.

Modeling greenhouse gas emissions from dairy farms.

PubMed

Rotz, C Alan

2017-11-15

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric CH 4 from the animals, CH 4 and N 2 O from manure in housing facilities during long-term storage and during field application, and N 2 O from nitrification and denitrification processes in the soil used to produce feed crops and pasture. Models using a wide range in level of detail have been developed to represent or predict these emissions. They include constant emission factors, variable process-related emission factors, empirical or statistical models, mechanistic process simulations, and life cycle assessment. To fully represent farm emissions, models representing the various emission sources must be integrated to capture the combined effects and interactions of all important components. Farm models have been developed using relationships across the full scale of detail, from constant emission factors to detailed mechanistic simulations. Simpler models, based upon emission factors and empirical relationships, tend to provide better tools for decision support, whereas more complex farm simulations provide better tools for research and education. To look beyond the farm boundaries, life cycle assessment provides an environmental accounting tool for quantifying and evaluating emissions over the full cycle, from producing the resources used on the farm through processing, distribution, consumption, and waste handling of the milk and dairy products produced. Models are useful for improving our understanding of farm processes and their interacting effects on greenhouse gas emissions. Through better understanding, they assist in the development and evaluation of mitigation strategies for reducing emissions and improving overall sustainability of dairy farms. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Applying additive logistic regression to data derived from sensors monitoring behavioral and physiological characteristics of dairy cows to detect lameness.

PubMed

Kamphuis, C; Frank, E; Burke, J K; Verkerk, G A; Jago, J G

2013-01-01

The hypothesis was that sensors currently available on farm that monitor behavioral and physiological characteristics have potential for the detection of lameness in dairy cows. This was tested by applying additive logistic regression to variables derived from sensor data. Data were collected between November 2010 and June 2012 on 5 commercial pasture-based dairy farms. Sensor data from weigh scales (liveweight), pedometers (activity), and milk meters (milking order, unadjusted and adjusted milk yield in the first 2 min of milking, total milk yield, and milking duration) were collected at every milking from 4,904 cows. Lameness events were recorded by farmers who were trained in detecting lameness before the study commenced. A total of 318 lameness events affecting 292 cows were available for statistical analyses. For each lameness event, the lame cow's sensor data for a time period of 14 d before observation date were randomly matched by farm and date to 10 healthy cows (i.e., cows that were not lame and had no other health event recorded for the matched time period). Sensor data relating to the 14-d time periods were used for developing univariable (using one source of sensor data) and multivariable (using multiple sources of sensor data) models. Model development involved the use of additive logistic regression by applying the LogitBoost algorithm with a regression tree as base learner. The model's output was a probability estimate for lameness, given the sensor data collected during the 14-d time period. Models were validated using leave-one-farm-out cross-validation and, as a result of this validation, each cow in the data set (318 lame and 3,180 nonlame cows) received a probability estimate for lameness. Based on the area under the curve (AUC), results indicated that univariable models had low predictive potential, with the highest AUC values found for liveweight (AUC=0.66), activity (AUC=0.60), and milking order (AUC=0.65). Combining these 3 sensors improved AUC to 0.74. Detection performance of this combined model varied between farms but it consistently and significantly outperformed univariable models across farms at a fixed specificity of 80%. Still, detection performance was not high enough to be implemented in practice on large, pasture-based dairy farms. Future research may improve performance by developing variables based on sensor data of liveweight, activity, and milking order, but that better describe changes in sensor data patterns when cows go lame. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya.

PubMed Central

Kadohira, M.; McDermott, J. J.; Shoukri, M. M.; Kyule, M. N.

1997-01-01

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data. PMID:9042033

Integrative modeling and novel particle swarm-based optimal design of wind farms

NASA Astrophysics Data System (ADS)

Chowdhury, Souma

To meet the energy needs of the future, while seeking to decrease our carbon footprint, a greater penetration of sustainable energy resources such as wind energy is necessary. However, a consistent growth of wind energy (especially in the wake of unfortunate policy changes and reported under-performance of existing projects) calls for a paradigm shift in wind power generation technologies. This dissertation develops a comprehensive methodology to explore, analyze and define the interactions between the key elements of wind farm development, and establish the foundation for designing high-performing wind farms. The primary contribution of this research is the effective quantification of the complex combined influence of wind turbine features, turbine placement, farm-land configuration, nameplate capacity, and wind resource variations on the energy output of the wind farm. A new Particle Swarm Optimization (PSO) algorithm, uniquely capable of preserving population diversity while addressing discrete variables, is also developed to provide powerful solutions towards optimizing wind farm configurations. In conventional wind farm design, the major elements that influence the farm performance are often addressed individually. The failure to fully capture the critical interactions among these factors introduces important inaccuracies in the projected farm performance and leads to suboptimal wind farm planning. In this dissertation, we develop the Unrestricted Wind Farm Layout Optimization (UWFLO) methodology to model and optimize the performance of wind farms. The UWFLO method obviates traditional assumptions regarding (i) turbine placement, (ii) turbine-wind flow interactions, (iii) variation of wind conditions, and (iv) types of turbines (single/multiple) to be installed. The allowance of multiple turbines, which demands complex modeling, is rare in the existing literature. The UWFLO method also significantly advances the state of the art in wind farm optimization by allowing simultaneous optimization of the type and the location of the turbines. Layout optimization (using UWFLO) of a hypothetical 25-turbine commercial-scale wind farm provides a remarkable 4.4% increase in capacity factor compared to a conventional array layout. A further 2% increase in capacity factor is accomplished when the types of turbines are also optimally selected. The scope of turbine selection and placement however depends on the land configuration and the nameplate capacity of the farm. Such dependencies are not clearly defined in the existing literature. We develop response surface-based models, which implicitly employ UWFLO, to quantify and analyze the roles of these other crucial design factors in optimal wind farm planning. The wind pattern at a site can vary significantly from year to year, which is not adequately captured by conventional wind distribution models. The resulting ill-predictability of the annual distribution of wind conditions introduces significant uncertainties in the estimated energy output of the wind farm. A new method is developed to characterize these wind resource uncertainties and model the propagation of these uncertainties into the estimated farm output. The overall wind pattern/regime also varies from one region to another, which demands turbines with capabilities uniquely suited for different wind regimes. Using the UWFLO method, we model the performance potential of currently available turbines for different wind regimes, and quantify their feature-based expected market suitability. Such models can initiate an understanding of the product variation that current turbine manufacturers should pursue, to adequately satisfy the needs of the naturally diverse wind energy market. The wind farm design problems formulated in this dissertation involve highly multimodal objective and constraint functions and a large number of continuous and discrete variables. An effective modification of the PSO algorithm is developed to address such challenging problems. Continuous search, as in conventional PSO, is implemented as the primary search strategy; discrete variables are then updated using a nearest-allowed-discrete-point criterion. Premature stagnation of particles due to loss of population diversity is one of the primary drawbacks of the basic PSO dynamics. A new measure of population diversity is formulated, which unlike existing metrics capture both the overall spread and the distribution of particles in the variable space. This diversity metric is then used to apply (i) an adaptive repulsion away from the best global solution in the case of continuous variables, and (ii) a stochastic update of the discrete variables. The new PSO algorithm provides competitive performance compared to a popular genetic algorithm, when applied to solve a comprehensive set of 98 mixed-integer nonlinear programming problems.

Copula-based models of systemic risk in U.S

Treesearch

Barry K. Goodwin; Ashley Hungerford Hungerford

2015-01-01

The federal crop insurance program has been a major fixture of U.S. agricultural policy since the 1930s, and continues to grow in size and importance. Indeed, it now represents the most prominent farm policy instrument, accounting for more government spending than any other farm commodity program. The 2014 Farm Bill further expanded the crop insurance program and...

Stability analysis of offshore wind farm and marine current farm

NASA Astrophysics Data System (ADS)

Shawon, Mohammad Hasanuzzaman

Renewable energy has been playing an important role to meet power demand and 'Green Energy' market is getting bigger platform all over the world in the last few years. Due to massive increase in the prices of fossil fuels along with global warming issues, energy harvesting from renewable energy sources has received considerable interest, nowadays, where extensive researches are going on to ensure optimum use of renewable sources. In order to meet the increasing demand of electricity and power, integration of renewable energy is getting highest priorities around the world. Wind is one of the most top growing renewable energy resources and wind power market penetration is expected to reach 3.35 percent by 2013 from its present market of about 240 GW. A wind energy system is the most environmental friendly, cost effective and safe among all renewable energy resources available. Another promising form of renewable energy is ocean energy which covers 70 % of the earth. Ocean energy can be tapped from waves, tides and thermal elements. Offshore Wind farm (OWF) has already become very popular for large scale wind power integration with the onshore grid. Recently, marine current farm (MCF) is also showing good potential to become mainstream energy sources and already successfully commissioned in United Kingdom. However, squirrel cage induction generator (SCIG) has the stability problem similar to synchronous generator especially during fault location to restore the electromagnetic torque. Series dynamic braking resistor (SDBR) has been known as a useful mean to stabilize fixed speed wind generator system. On the other hand, doubly fed induction generator (DFIG) has the capability of coupling the control of active and reactive power and to provide necessary reactive power demand during grid fault conditions. Series dynamic braking resistor (SDBR) can also be employed with DFIG to limit the rotor over current. An integration of wind and tidal energy represents a new-trend for large electric energy production using offshore wind generators and marine current generators, respectively. Thus DFIG based offshore wind farm can be an economic solution to stabilize squirrel cage induction generator based marine current farm without installing any addition FACTS devices. This thesis first focuses on the stabilization of fixed speed IG based marine current farm using SDBR. Also stabilization of DFIG based variable speed wind farm utilizing SDBR is studied in this work. Finally a co-operative control strategy is proposed where DFIG is controlled in such a way that it can even provide necessary reactive power demand of induction generator, so that additional cost of FACTS devices can be avoided. In that way, the DFIGs of the offshore wind farm (OWF) will actively compensate the reactive power demand of adjacent IGs of the marine current farm (MCF) during grid fault. Detailed modeling and control scheme for the proposed system are demonstrated considering some realistic scenarios. The power system small signal stability analysis is also carried out by eigenvalue analysis for marine current generator topology, wind turbine generator topology and integrated topology. The relation between the modes and state variables are discussed in light of modal and sensitivity analyses. The results of theoretical analyses are verified by MATLAB/SIMULINK and laboratory standard power system simulator PSCAD/EMTDC.

Efficiency of dairy farms participating and not participating in veterinary herd health management programs.

PubMed

Derks, Marjolein; Hogeveen, Henk; Kooistra, Sake R; van Werven, Tine; Tauer, Loren W

2014-12-01

This paper compares farm efficiencies between dairies who were participating in a veterinary herd health management (VHHM) program with dairies not participating in such a program, to determine whether participation has an association with farm efficiency. In 2011, 572 dairy farmers received a questionnaire concerning the participation and execution of a VHHM program on their farms. Data from the questionnaire were combined with farm accountancy data from 2008 through 2012 from farms that used calendar year accounting periods, and were analyzed using Stochastic Frontier Analysis (SFA). Two separate models were specified: model 1 was the basic stochastic frontier model (output: total revenue; input: feed costs, land costs, cattle costs, non-operational costs), without explanatory variables embedded into the efficiency component of the error term. Model 2 was an expansion of model 1 which included explanatory variables (number of FTE; total kg milk delivered; price of concentrate; milk per hectare; cows per FTE; nutritional yield per hectare) inserted into the efficiency component of the joint error term. Both models were estimated with the financial parameters expressed per 100 kg fat and protein corrected milk and per cow. Land costs, cattle costs, feed costs and non-operational costs were statistically significant and positive in all models (P<0.01). Frequency distributions of the efficiency scores for the VHHM dairies and the non-VHHM dairies were plotted in a kernel density plot, and differences were tested using the Kolmogorov-Smirnov two-sample test. VHHM dairies had higher total revenue per cow, but not per 100 kg milk. For all SFA models, the difference in distribution was not statistically different between VHHM dairies and non-VHHM dairies (P values 0.94, 0.35, 0.95 and 0.89 for the basic and complete model per 100 kg fat and protein corrected milk and per cow respectively). Therefore we conclude that with our data farm participation in VHHM is not related to overall farm efficiency. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial Numeric Classification Model Suitability with Landuse Change in Sustainable Food Agriculture Zone in Kediri Sub-district, Tabanan Regency, Indonesia

NASA Astrophysics Data System (ADS)

Trigunasih, N. M.; Lanya, I.; Hutauruk, J.; Arthagama, I. D. M.

2017-12-01

The development of rapid population will make the availability and utilization of land resources is increasingly shrinking in number, especially occurs in rice field. Since the last 5 years the numbers of farmland is decrasing by industry, infrastructure development, tourism development and other services. The agricultural problems facing at the moment is the occurrence of a change of use of agricultural land into farming now is not more popular is called over the function of agricultural land into non-farming. According to the Central Bureau of statistics (BPS) of the province of Bali (2013) within a period of 14 years (1999-2013), there has been a change of use of agricultural land be not agriculture/wetland functions over the 4,906 hectares. When averaged over the function flatten paddy fields per year occurred in Bali approximately 350 ha (0.41%). The highest paddy fields over the function during a period of fourteen years there is in Tabanan area of 1,230 ha. To maintain the existence of the rice fields or subak in Bali in particular, need to be done protection against agricultural lands sustainable. Ninth District/Town in Bali today, haven’t had a Perda on protection of agricultural land sustainable food that is mandated by law 41 Year 2009. This will have an impact on food security of the region, and the world’s cultural heritage as the water will lose its existence as a system of irrigation organization in Bali. The purpose of this research was done to (1) determine the numerical classification of spatial parameters of sustainable food farm in Tabanan Regency Kediri Subdistrict, (2) determine the model of the zoning of agricultural land area of sustainable food that fits on Years 2020, 2030, 2040, and in district of Kediri, Tabanan Regency. The method used is the kuantitaif method includes the focus group discussion, the development of spatial data, analysis geoprosessing (spatial analysis and analysis of proximity), and statistical analysis, interpolation of digital elevation model raster data, and visualization (cartography) and qualitative methods include the study of the literature (introduction). The research results obtained by as much as 23 rice fields mapped in spatial control system based on its geographical location. The parameters in the classification of sustainable food farming in district of Kediri consists of (1) the suitability of the location of a rice field with spatial Plan area of Tabanan Regency years 2012-2032, (2) land use, (3) Watershed morphology, (4) the type of irrigation, (5) rainfall, (6) the form region, (7) the high place, (8) the suitability of the agroecosystem paddy fields, (9) productivity, (10) the distance from the center of town, (11) minimum area. Spatial numerical classification produces a wide variety of modeling (5 models) and is associated with the projected changes in rice fields by the year 2020, 2030, and 2040. In the year 2020 using model 4 due to sustainable subak in model 4 of 2682.71 ha, approached the farm field area by the year in 2020 of 2684 ha. In the year 2030 using model 3 due to sustainable subak on the model is 1651.37 ha 3 plus ¾ buffer subak of 773.51 ha be 2424.88 ha approached the farm field by the year in 2030 of 2364 ha. In the year 2040 using model 2 due to sustainable subak on the model of 307,99 ha 3 plus ¾ buffer subak of 1781,04 ha be 2089,33 ha approached the farm field by the year in 2040 of 2033 ha.

The profitability of automatic milking on Dutch dairy farms.

PubMed

Bijl, R; Kooistra, S R; Hogeveen, H

2007-01-01

Several studies have reported on the profitability of automatic milking based on different simulation models, but a data-based study using actual farm data has been lacking. The objective of this study was to analyze the profitability of dairy farms having an automatic milking system (AMS) compared with farms using a conventional milking system (CMS) based on real accounting data. In total, 62 farms (31 using an AMS and 31 using a CMS) were analyzed for the year 2003 in a case control study. Differences between the years 2002 and 2003 also were analyzed by comparing a subgroup of 16 farms with an AMS and 16 farms with a CMS. Matching was based on the time of investment in a milking system (same year), the total milk production per year, and intensity of land use (kg/ha). Results from 2003 showed that the farms with an AMS used, on average, 29% less labor than farms with a CMS. In contrast, farms using a CMS grew faster (37,132 kg of milk quota and 5 dairy cows) than farms with an AMS (-3,756 kg milk quota and 0.5 dairy cows) between 2002 and 2003. Dairy farmers with a CMS had larger (euro7,899) revenues than those with an AMS. However, no difference in the margin on dairy production was detected, partly because of numerically greater (euro6,822) variable costs on CMS farms. Dairy farms were compared financially based on the amount of money that was available for rent, depreciation, interest, labor, and profit (RDILP). The CMS farms had more money (euro15,566) available for RDILP than the AMS farms. This difference was caused by larger fixed costs (excluding labor) for the AMS farms, larger contractor costs (euro6,422), and larger costs for gas, water, and electricity (euro1,549). Differences in costs for contractors and for gas, water, and electricity were statistically significant. When expressed per full-time employee, AMS farms had greater revenues, margins, and gross margins per full-time employee than did CMS farms. This resulted in a substantially greater (but not statistically significant) RDILP per full-time employee (euro12,953) for AMS farms compared with CMS farms. Depreciation and interest costs for automatic milking were not available but were calculated based on several assumptions. Assuming larger purchase costs and a shorter depreciation time for AMS than for CMS, costs for depreciation and interest were larger for AMS farms than for CMS farms. Larger fixed costs should be compensated for by the amount of labor that has become available after introducing the milking robot. Therefore, farm managers should decide whether the extra time acquired by automatic milking balances against the extra costs associated with an AMS.

Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution

NASA Astrophysics Data System (ADS)

Bithell, M.; Brasington, J.

2004-12-01

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.

Wake characteristics of wind turbines in utility-scale wind farms

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Foti, Daniel; Sotiropoulos, Fotis

2017-11-01

The dynamics of turbine wakes is affected by turbine operating conditions, ambient atmospheric turbulent flows, and wakes from upwind turbines. Investigations of the wake from a single turbine have been extensively carried out in the literature. Studies on the wake dynamics in utility-scale wind farms are relatively limited. In this work, we employ large-eddy simulation with an actuator surface or actuator line model for turbine blades to investigate the wake dynamics in utility-scale wind farms. Simulations of three wind farms, i.e., the Horns Rev wind farm in Denmark, Pleasant Valley wind farm in Minnesota, and the Vantage wind farm in Washington are carried out. The computed power shows a good agreement with measurements. Analysis of the wake dynamics in the three wind farms is underway and will be presented in the conference. This work was support by Xcel Energy (RD4-13). The computational resources were provided by National Renewable Energy Laboratory.

Simulation of Intra- or transboundary surface-water-rights hierarchies using the farm process for MODFLOW-2000

USGS Publications Warehouse

Schmid, W.; Hanson, R.T.

2007-01-01

Water-rights driven surface-water allocations for irrigated agriculture can be simulated using the farm process for MODFLOW-2000. This paper describes and develops a model, which simulates routed surface-water deliveries to farms limited by streamflow, equal-appropriation allotments, or a ranked prior-appropriation system. Simulated diversions account for deliveries to all farms along a canal according to their water-rights ranking and for conveyance losses and gains. Simulated minimum streamflow requirements on diversions help guarantee supplies to senior farms located on downstream diverting canals. Prior appropriation can be applied to individual farms or to groups of farms modeled as "virtual farms" representing irrigation districts, irrigated regions in transboundary settings, or natural vegetation habitats. The integrated approach of jointly simulating canal diversions, surface-water deliveries subject to water-rights constraints, and groundwater allocations is verified on numerical experiments based on a realistic, but hypothetical, system of ranked virtual farms. Results are discussed in light of transboundary water appropriation and demonstrate the approach's suitability for simulating effects of water-rights hierarchies represented by international treaties, interstate stream compacts, intrastate water rights, or ecological requirements. ?? 2007 ASCE.

Analytical Model for Mean Flow and Fluxes of Momentum and Energy in Very Large Wind Farms

NASA Astrophysics Data System (ADS)

Markfort, Corey D.; Zhang, Wei; Porté-Agel, Fernando

2018-01-01

As wind-turbine arrays continue to be installed and the array size continues to grow, there is an increasing need to represent very large wind-turbine arrays in numerical weather prediction models, for wind-farm optimization, and for environmental assessment. We propose a simple analytical model for boundary-layer flow in fully-developed wind-turbine arrays, based on the concept of sparsely-obstructed shear flows. In describing the vertical distribution of the mean wind speed and shear stress within wind farms, our model estimates the mean kinetic energy harvested from the atmospheric boundary layer, and determines the partitioning between the wind power captured by the wind turbines and that absorbed by the underlying land or water. A length scale based on the turbine geometry, spacing, and performance characteristics, is able to estimate the asymptotic limit for the fully-developed flow through wind-turbine arrays, and thereby determine if the wind-farm flow is fully developed for very large turbine arrays. Our model is validated using data collected in controlled wind-tunnel experiments, and its usefulness for the prediction of wind-farm performance and optimization of turbine-array spacing are described. Our model may also be useful for assessing the extent to which the extraction of wind power affects the land-atmosphere coupling or air-water exchange of momentum, with implications for the transport of heat, moisture, trace gases such as carbon dioxide, methane, and nitrous oxide, and ecologically important oxygen.

Results of an online questionnaire to survey calf management practices on dairy cattle breeding farms in Austria and to estimate differences in disease incidences depending on farm structure and management practices.

PubMed

Klein-Jöbstl, Daniela; Arnholdt, Tim; Sturmlechner, Franz; Iwersen, Michael; Drillich, Marc

2015-08-19

Calf disease may result in great economic losses. To implement prevention strategies it is important to gain information on management and to point out risk factors. The objective of this internet based survey was to describe calf management practices on registered dairy breeding farms in Austria and to estimate differences in calf disease incidences depending on farm structure and management practices. A total of 1287 questionnaires were finally analysed (response rate 12.2 %). Herd characteristics and regional distribution of farms indicated that this survey gives a good overview on calf management practices on registered dairy farms in Austria. The median number of cows per farm was 20 (interquartile range 13-30). Significant differences regarding farm characteristics and calf management between small and large farms (≤20 vs >20 cows) were present. Only 2.8 % of farmers tested first colostrum quality by use of a hydrometer. Storing frozen colostrum was more prevalent on large farms (80.8 vs 64.2 %). On 85.1 % of the farms, whole milk, including waste milk, was fed to the calves. Milk replacer and waste milk were more often used on large farms. In accordance with similar studies from other countries, calf diarrhoea was indicated as the most prevalent disease. Multivariable logistic regression analysis revealed that herd size was associated with calf diarrhoea and calf respiratory tract disease, with higher risk of disease on large farms. Furthermore, feeding waste milk to the calves was associated with increasing calf diarrhoea incidence on farm. In the final model with calf respiratory tract disease as outcome, respondents from organic farms reported less often a respiratory tract disease incidence of over 10 % compared with conventional farms [odds ratio (OR) 0.40, 95 % confidence interval (CI) 0.21-0.75] and farmers that housed calves individually or in groups after birth significantly reported more often to have an incidence of respiratory tract disease >10 % compared with farms where all calves were housed individually (OR 2.28, 95 % CI 1.16-4.48). The results obtained in this study provide an overview on calf management on dairy breeding farms in Austria and may help to further point out areas to be improved on farm.

Mixed crop-livestock systems: an economic and environmental-friendly way of farming?

PubMed

Ryschawy, J; Choisis, N; Choisis, J P; Joannon, A; Gibon, A

2012-10-01

Intensification and specialisation of agriculture in developed countries enabled productivity to be improved but had detrimental impacts on the environment and threatened the economic viability of a huge number of farms. The combination of livestock and crops, which was very common in the past, is assumed to be a viable alternative to specialised livestock or cropping systems. Mixed crop-livestock systems can improve nutrient cycling while reducing chemical inputs and generate economies of scope at farm level. Most assumptions underlying these views are based on theoretical and experimental evidence. Very few assessments of their environmental and economic advantages have nevertheless been undertaken in real-world farming conditions. In this paper, we present a comparative assessment of the environmental and economic performances of mixed crop-livestock farms v. specialised farms among the farm population of the French 'Coteaux de Gascogne'. In this hilly region, half of the farms currently use a mixed crop-livestock system including beef cattle and cash crops, the remaining farms being specialised in either crops or cattle. Data were collected through an exhaustive survey of farms located in our study area. The economic performances of farming systems were assessed on 48 farms on the basis of (i) overall gross margin, (ii) production costs and (iii) analysis of the sensitivity of gross margins to fluctuations in the price of inputs and outputs. The environmental dimension was analysed through (i) characterisation of farmers' crop management practices, (ii) analysis of farm land use diversity and (iii) nitrogen farm-gate balance. Local mixed crop-livestock farms did not have significantly higher overall gross margins than specialised farms but were less sensitive than dairy and crop farms to fluctuations in the price of inputs and outputs considered. Mixed crop-livestock farms had lower costs than crop farms, while beef farms had the lowest costs as they are grass-based systems. Concerning crop management practices, our results revealed an intensification gradient from low to high input farming systems. Beyond some general trends, a wide range of management practices and levels of intensification were observed among farms with a similar production system. Mixed crop-livestock farms were very heterogeneous with respect to the use of inputs. Nevertheless, our study revealed a lower potential for nitrogen pollution in mixed crop-livestock and beef production systems than in dairy and crop farming systems. Even if a wide variability exists within system, mixed crop-livestock systems appear to be a way for an environmental and economical sustainable agriculture.

Wind farm density and harvested power in very large wind farms: A low-order model

NASA Astrophysics Data System (ADS)

Cortina, G.; Sharma, V.; Calaf, M.

2017-07-01

In this work we create new understanding of wind turbine wakes recovery process as a function of wind farm density using large-eddy simulations of an atmospheric boundary layer diurnal cycle. Simulations are forced with a constant geostrophic wind and a time varying surface temperature extracted from a selected period of the Cooperative Atmospheric Surface Exchange Study field experiment. Wind turbines are represented using the actuator disk model with rotation and yaw alignment. A control volume analysis around each turbine has been used to evaluate wind turbine wake recovery and corresponding harvested power. Results confirm the existence of two dominant recovery mechanisms, advection and flux of mean kinetic energy, which are modulated by the background thermal stratification. For the low-density arrangements advection dominates, while for the highly loaded wind farms the mean kinetic energy recovers through fluxes of mean kinetic energy. For those cases in between, a smooth balance of both mechanisms exists. From the results, a low-order model for the wind farms' harvested power as a function of thermal stratification and wind farm density has been developed, which has the potential to be used as an order-of-magnitude assessment tool.

High-resolution computational algorithms for simulating offshore wind turbines and farms: Model development and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calderer, Antoni; Yang, Xiaolei; Angelidis, Dionysios

2015-10-30

The present project involves the development of modeling and analysis design tools for assessing offshore wind turbine technologies. The computational tools developed herein are able to resolve the effects of the coupled interaction of atmospheric turbulence and ocean waves on aerodynamic performance and structural stability and reliability of offshore wind turbines and farms. Laboratory scale experiments have been carried out to derive data sets for validating the computational models.

Analysis of winter weather conditions and their potential impact on wind farm operations

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Treinish, L. A.; Praino, A.

2009-12-01

Severe weather conditions have two primary impacts on wind farm operations. The first relates to understanding potential damage to the turbines themselves and what actions are required to mitigate the effects. The second is recognizing what conditions may lead to a full or partial shutdown of the wind farm with sufficient lead time to determine the likely inability to meet energy generation committments. Ideally, wind forecasting suitable for wind farm operations should be of sufficient fidelity to resolve features within the boundary layer that lead to either damaging conditions or useful power generation. Given the complexity of the site-specific factors that effect the boundary layer at the scale of typical land-based wind farm locations such as topography, vegetation, land use, soil conditions, etc., which may vary with turbine design and layout within the farm, enabling reliable forecasts of too little or too much wind is challenging. A potential solution should involve continuous updates of alert triggering criteria through analysis of local wind patterns and probabilistic risk assessment for each location. To evaluate this idea, we utilize our operational mesoscale prediction system, dubbed “Deep Thunder”, developed at the IBM Thomas J. Watson Research Center. In particular, we analyze winter-time near-surface winds in upstate New York, where four similar winds farms are located. Each of these farms were built at roughly the same time and utilize similar turbines. Given the relative uncertainty associated with numerical weather prediction at this scale, and the difference in risk assessment due to the two primary impacts of severe weather, probabilistic forecasts are a prerequisite. Hence, we have employed ensembles of weather scenarios, which are based on the NCAR WRF-ARW modelling system. The set of ensemble members was composed with variations in the choices of physics and parameterization schemes, and source of background fields for initial conditions with horizontal grid resolutions in the one to two km range. In addition, the vertical grid structure was defined to ensure at least ten levels within the boundary layer and two from the bottom to the top of the turbine. This approach enables us to estimate the variability of winds at the farms and how it is distributed over the region. Further, we analyze the potential differences in structural risks at these farms during the 2009 winter season, and whether such differences in wind and weather patterns should be considered in choice of turbine design, installation and operations. We believe that this methodology can be extended to provide an estimate for mean annual energy production at a wind farm with the potential to improve the quality of siting and layout.

Process audits versus product quality monitoring of bulk milk.

PubMed

Velthuis, A G J; van Asseldonk, M A P M

2011-01-01

Assessment of milk quality is based on bulk milk testing and farm certification on process quality audits. It is unknown to what extent dairy farm audits improve milk quality. A statistical analysis was conducted to quantify possible associations between bulk milk testing and dairy farm audits. The analysis comprised 64.373 audit outcomes on 26,953 dairy farms, which were merged with all conducted laboratory tests of bulk milk samples 12 mo before the audit. Each farm audit record included 271 binary checklist items and 52 attention point variables (given to farmers if serious deviations were observed), both indicating possible deviations from the desired farm situation. Test results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acid (FFA), and milk sediment (SED). Results show that numerous audit variables were related to bulk milk test results, although the goodness of fit of the models was generally low. Cow hygiene, clean cubicles, hygiene of milking parlor, and utility room were positively correlated with superior product quality, mainly with respect to SCC, TBC, BAB, FPD, FFA, and SED. Animal health or veterinary drugs management (i.e., drug treatment recording, marking of treated animals, and storage of veterinary drugs) related to SCC, FPD, FFA, and SED. The availability of drinking water was related to TBC, BAB, FFA, and SED, whereas maintenance of the milking equipment was related mainly to SCC, FPD, and FFA. In summary, bulk milk quality and farm audit outcomes are, to some degree, associated: if dairy farms are assessed negatively on specific audit aspects, the bulk milk quality is more likely to be inferior. However, the proportion of the total variance in milk test results explained by audits ranged between 4 and 13% (depending on the specific bulk milk test), showing that auditing dairy farms provides additional information but has a limited association with the outcome of a product quality control program. This study suggests that farm audits could be streamlined to include only relevant checklist items and that bulk milk quality monitoring could be used as a basis of selecting farms for more or less frequent audits. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Organic dairy production systems in Pennsylvania: a case study evaluation.

PubMed

Rotz, C A; Kamphuis, G H; Karsten, H D; Weaver, R D

2007-08-01

The current market demand and price for organic milk is encouraging dairy producers, particularly those on smaller farms, to consider organic production as a means for improving the economic viability of their operations. Organic production systems vary widely in scale, in practices, and across agroclimatic settings. Within this context, case studies of 4 actual organic dairy farms were used to characterize existing systems in Pennsylvania. Based on data from these farms, a whole-farm simulation model (Integrated Farm System Model) was used to compare 4 production systems representing organic grass, organic crop, conventional crop with grazing, and conventional confinement production. The performance of each of these systems was simulated over each year of 25 yr of central Pennsylvania weather data. Simulation results indicated that farm level accumulation of soil P and K may be a concern on organic farms that use poultry manure as a primary crop nutrient source, and that erosion and runoff loss of P may be of concern on organic farms producing annual crops because more tillage is required for weed control. Whole-farm budgets with prices that reflect recent conditions showed an economic advantage for organic over conventional production. A sensitivity analysis showed that this economic advantage depended on a higher milk price for producers of organic milk and was influenced by the difference in milk production maintained by herds using organic and conventional systems. Factors found to have little effect on the relative profitability of organic over conventional production included the differences between organic and conventional prices for seed, chemicals, forage, and animals and the overall costs or prices assumed for organic certification, machinery, pasture fencing, fuel, and labor. Thus, at the current organic milk price, relative to other prices, the case study organic production systems seem to provide an option for improving the economic viability of dairy operations of the scale considered in Pennsylvania. To motivate transition to organic systems, the economic advantage found requires the persistence of a substantial difference between conventional and organic raw milk prices.

Modeling Hydrological Services in Shade Grown Coffee Systems: Case Study of the Pico Duarte Region of the Dominican Republic

NASA Astrophysics Data System (ADS)

Erickson, J. D.; Gross, L.; Agosto Filion, N.; Bagstad, K.; Voigt, B. G.; Johnson, G.

2010-12-01

The modification of hydrologic systems in coffee-dominated landscapes varies widely according to the degree of shade trees incorporated in coffee farms. Compared to mono-cropping systems, shade coffee can produce both on- and off-farm benefits in the form of soil retention, moderation of sediment transport, and lower hydropower generating costs. The Pico Duarte Coffee Region and surrounding Madres de Las Aguas (Mother of Waters) Conservation Area in the Dominican Republic is emblematic of the challenges and opportunities of ecosystem service management in coffee landscapes. Shade coffee poly-cultures in the region play an essential role in ensuring ecosystem function to conserve water resources, as well as provide habitat for birds, sequester carbon, and provide consumptive resources to households. To model the provision, use, and flow of ecosystem services from coffee farms in the region, an application of the Artificial Intelligence for Ecosystem Services (ARIES) model was developed with particular focus on sediment regulation. ARIES incorporates an array of techniques from data mining, image analysis, neural networks, Bayesian statistics, information theory, and expert systems to model the production, delivery, and demand for ecosystem services. Geospatial data on slope, soils, and vegetation cover is combined with on-farm data collection of coffee production, tree diversity, and intercropping of household food. Given hydropower production and river recreation in the region, the management of sedimentation through on-farm practices has substantial, currently uncompensated value that has received recent attention as the foundation for a payment for ecosystem services system. Scenario analysis of the implications of agro-forestry management choices on farmer livelihoods and the multiple beneficiaries of farm-provided hydrological services provide a foundation for ongoing discussions in the region between local, national, and international interests.

Patterns of ecosystem services supply across farm properties: Implications for ecosystem services-based policy incentives.

PubMed

Nahuelhual, Laura; Benra, Felipe; Laterra, Pedro; Marin, Sandra; Arriagada, Rodrigo; Jullian, Cristobal

2018-09-01

In developing countries, the protection of biodiversity and ecosystem services (ES) rests on the hands of millions of small landowners that coexist with large properties, in a reality of highly unequal land distribution. Guiding the effective allocation of ES-based incentives in such contexts requires researchers and practitioners to tackle a largely overlooked question: for a given targeted area, will single large farms or several small ones provide the most ES supply? The answer to this question has important implications for conservation planning and rural development alike, which transcend efficiency to involve equity issues. We address this question by proposing and testing ES supply-area relations (ESSARs) around three basic hypothesized models, characterized by constant (model 1), increasing (model 2), and decreasing increments (model 3) of ES supply per unit of area or ES "productivity". Data to explore ESSARs came from 3384 private landholdings located in southern Chile ranging from 0.5ha to over 30,000ha and indicators of four ES (forage, timber, recreation opportunities, and water supply). Forage provision best fit model 3, which suggests that targeting several small farms to provide this ES should be a preferred choice, as compared to a single large farm. Timber provision best fit model 2, suggesting that in this case targeting a single large farm would be a more effective choice. Recreation opportunities best fit model 1, which indicates that several small or a single large farm of a comparable size would be equally effective in delivering this ES. Water provision fit model 1 or model 2 depending on the study site. The results corroborate that ES provision is not independent from property area and therefore understanding ESSARs is a necessary condition for setting conservation incentives that are both efficient (deliver the highest conservation outcome at the least cost) and fair for landowners. Copyright © 2018 Elsevier B.V. All rights reserved.

Risk-Based Consumption Advice for Farmed Atlantic and Wild Pacific Salmon Contaminated with Dioxins and Dioxin-like Compounds

PubMed Central

Foran, Jeffery A.; Carpenter, David O.; Hamilton, M. Coreen; Knuth, Barbara A.; Schwager, Steven J.

2005-01-01

We reported recently that several organic contaminants occurred at elevated concentrations in farmed Atlantic salmon compared with concentrations of the same contaminants in wild Pacific salmon [Hites et al. Science 303:226–229 (2004)]. We also found that polychlorinated biphenyls (PCBs), toxaphene, dieldrin, dioxins, and polybrominated diphenyl ethers occurred at higher concentrations in European farm-raised salmon than in farmed salmon from North and South America. Health risks (based on a quantitative cancer risk assessment) associated with consumption of farmed salmon contaminated with PCBs, toxaphene, and dieldrin were higher than risks associated with exposure to the same contaminants in wild salmon. Here we present information on cancer and noncancer health risks of exposure to dioxins in farmed and wild salmon. The analysis is based on a tolerable intake level for dioxin-like compounds established by the World Health Organization and on risk estimates for human exposure to dioxins developed by the U.S. Environmental Protection Agency. Consumption of farmed salmon at relatively low frequencies results in elevated exposure to dioxins and dioxin-like compounds with commensurate elevation in estimates of health risk. PMID:15866762

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

NASA Technical Reports Server (NTRS)

Walker, R. A.; Drzyzga, S. A.; Li, Y. L.; Wi, J. G.; Caldas, M.; Arima, E.; Vergara, D.

2004-01-01

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

Environmental impacts of organic and conventional agricultural products--are the differences captured by life cycle assessment?

PubMed

Meier, Matthias S; Stoessel, Franziska; Jungbluth, Niels; Juraske, Ronnie; Schader, Christian; Stolze, Matthias

2015-02-01

Comprehensive assessment tools are needed that reliably describe environmental impacts of different agricultural systems in order to develop sustainable high yielding agricultural production systems with minimal impacts on the environment. Today, Life Cycle Assessment (LCA) is increasingly used to assess and compare the environmental sustainability of agricultural products from conventional and organic agriculture. However, LCA studies comparing agricultural products from conventional and organic farming systems report a wide variation in the resource efficiency of products from these systems. The studies show that impacts per area farmed land are usually less in organic systems, but related to the quantity produced impacts are often higher. We reviewed 34 comparative LCA studies of organic and conventional agricultural products to analyze whether this result is solely due to the usually lower yields in organic systems or also due to inaccurate modeling within LCA. Comparative LCAs on agricultural products from organic and conventional farming systems often do not adequately differentiate the specific characteristics of the respective farming system in the goal and scope definition and in the inventory analysis. Further, often only a limited number of impact categories are assessed within the impact assessment not allowing for a comprehensive environmental assessment. The most critical points we identified relate to the nitrogen (N) fluxes influencing acidification, eutrophication, and global warming potential, and biodiversity. Usually, N-emissions in LCA inventories of agricultural products are based on model calculations. Modeled N-emissions often do not correspond with the actual amount of N left in the system that may result in potential emissions. Reasons for this may be that N-models are not well adapted to the mode of action of organic fertilizers and that N-emission models often are built on assumptions from conventional agriculture leading to even greater deviances for organic systems between the amount of N calculated by emission models and the actual amount of N available for emissions. Improvements are needed regarding a more precise differentiation between farming systems and regarding the development of N emission models that better represent actual N-fluxes within different systems. We recommend adjusting N- and C-emissions during farmyard manure management and farmyard manure fertilization in plant production to the feed ration provided in the animal production of the respective farming system leading to different N- and C-compositions within the excrement. In the future, more representative background data on organic farming systems (e.g. N content of farmyard manure) should be generated and compiled so as to be available for use within LCA inventories. Finally, we recommend conducting consequential LCA - if possible - when using LCA for policy-making or strategic environmental planning to account for different functions of the analyzed farming systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rice production model based on the concept of ecological footprint

NASA Astrophysics Data System (ADS)

Faiz, S. A.; Wicaksono, A. D.; Dinanti, D.

2017-06-01

Pursuant to what had been stated in Region Spatial Planning (RTRW) of Malang Regency for period 2010-2030, Malang Regency was considered as the center of agricultural development, including districts bordered with Malang City. To protect the region functioning as the provider of rice production, then the policy of sustainable food farming-land (LP2B) was made which its implementation aims to protect rice-land. In the existing condition, LP2B system was not maximally executed, and it caused a limited extend of rice-land to deliver rice production output. One cause related with the development of settlements and industries due to the effect of Malang City that converted land-function. Location of research focused on 30 villages with direct border with Malang City. Review was conducted to develop a model of relation between farming production output and ecological footprint variables. These variables include rice-land area (X1), built land percentage (X2), and number of farmers (X3). Analysis technique was regression. Result of regression indicated that the model of rice production output Y=-207,983 + 10.246X1. Rice-land area (X1) was the most influential independent variable. It was concluded that of villages directly bordered with Malang City, there were 11 villages with higher production potential because their rice production yield was more than 1,000 tons/year, while 12 villages were threatened with low production output because its rice production yield only attained 500 tons/year. Based on the model and the spatial direction of RTRW, it can be said that the direction for the farming development policy must be redesigned to maintain rice-land area on the regions on which agricultural activity was still dominant. Because rice-land area was the most influential factor to farming production. Therefore, the wider the rice-land is, the higher rice production output is on each village.

Exploration of Force Transition in Stability Operations Using Multi-Agent Simulation

DTIC Science & Technology

2006-09-01

risk, mission failure risk, and time in the context of the operational threat environment. The Pythagoras Multi-Agent Simulation and Data Farming...NUMBER OF PAGES 173 14. SUBJECT TERMS Stability Operations, Peace Operations, Data Farming, Pythagoras , Agent- Based Model, Multi-Agent Simulation...the operational threat environment. The Pythagoras Multi-Agent Simulation and Data Farming techniques are used to investigate force-level

Economic modelling of grazing management against gastrointestinal nematodes in dairy cattle.

PubMed

van der Voort, M; Van Meensel, J; Lauwers, L; de Haan, M H A; Evers, A G; Van Huylenbroeck, G; Charlier, J

2017-03-15

Grazing management (GM) interventions, such as reducing the grazing time or mowing pasture before grazing, have been proposed to limit the exposure to gastrointestinal (GI) nematode infections in grazed livestock. However, the farm-level economic effects of these interventions have not yet been assessed. In this paper, the economic effects of three GM interventions in adult dairy cattle were modelled for a set of Flemish farms: later turnout on pasture (GM1), earlier housing near the end of the grazing season (GM2), and reducing the daily grazing time (GM3). Farm accountancy data were linked to Ostertagia ostertagi bulk tank milk ELISA results and GM data for 137 farms. The economic effects of the GM interventions were investigated through a combination of efficiency analysis and a whole-farm simulation model. Modelling of GM1, GM2 and GM3 resulted in a marginal economic effect of € 8.36, € -9.05 and € -53.37 per cow per year, respectively. The results suggest that the dairy farms can improve their economic performance by postponing the turnout date, but that advancing the housing date or reducing daily grazing time mostly leads to a lower net economic farm performance. Overall, the GM interventions resulted in a higher technical efficiency and milk production but these benefits were offset by increased feed costs as a result of higher maintenance and cultivation costs. Because the results differed highly between farms, GM interventions need to be evaluated at the individual level for appropriate decision support. Copyright © 2017 Elsevier B.V. All rights reserved.

A stochastic frontier approach to study the relationship between gastrointestinal nematode infections and technical efficiency of dairy farms.

PubMed

van der Voort, Mariska; Van Meensel, Jef; Lauwers, Ludwig; Vercruysse, Jozef; Van Huylenbroeck, Guido; Charlier, Johannes

2014-01-01

The impact of gastrointestinal (GI) nematode infections in dairy farming has traditionally been assessed using partial productivity indicators. But such approaches ignore the impact of infection on the performance of the whole farm. In this study, efficiency analysis was used to study the association of the GI nematode Ostertagia ostertagi on the technical efficiency of dairy farms. Five years of accountancy data were linked to GI nematode infection data gained from a longitudinal parasitic monitoring campaign. The level of exposure to GI nematodes was based on bulk-tank milk ELISA tests, which measure the antibodies to O. ostertagi and was expressed as an optical density ratio (ODR). Two unbalanced data panels were created for the period 2006 to 2010. The first data panel contained 198 observations from the Belgian Farm Accountancy Data Network (Brussels, Belgium) and the second contained 622 observations from the Boerenbond Flemish farmers' union (Leuven, Belgium) accountancy system (Tiber Farm Accounting System). We used the stochastic frontier analysis approach and defined inefficiency effect models specified with the Cobb-Douglas and transcendental logarithmic (Translog) functional form. To assess the efficiency scores, milk production was considered as the main output variable. Six input variables were used: concentrates, roughage, pasture, number of dairy cows, animal health costs, and labor. The ODR of each individual farm served as an explanatory variable of inefficiency. An increase in the level of exposure to GI nematodes was associated with a decrease in technical efficiency. Exposure to GI nematodes constrains the productivity of pasture, health, and labor but does not cause inefficiency in the use of concentrates, roughage, and dairy cows. Lowering the level of infection in the interquartile range (0.271 ODR) was associated with an average milk production increase of 27, 19, and 9L/cow per year for Farm Accountancy Data Network farms and 63, 49, and 23L/cow per year for Tiber Farm Accounting System farms in the low- (0-90), medium- (90-95), and high- (95-99) efficiency score groups, respectively. The potential milk increase associated with reducing the level of infection was higher for highly efficient farms (6.7% of the total possible milk increase when becoming fully technically efficient) than for less efficient farms (3.8% of the total possible milk increase when becoming fully technically efficient). Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A systems approach to assess farm-scale nutrient and trace element dynamics: a case study at the Ojebyn dairy farm.

PubMed

Oborn, Ingrid; Modin-Edman, Anna-Karin; Bengtsson, Helena; Gustafson, Gunnela M; Salomon, Eva; Nilsson, S Ingvar; Holmqvist, Johan; Jonsson, Simon; Sverdrup, Harald

2005-06-01

A systems analysis approach was used to assess farmscale nutrient and trace element sustainability by combining full-scale field experiments with specific studies of nutrient release from mineral weathering and trace-element cycling. At the Ojebyn dairy farm in northern Sweden, a farm-scale case study including phosphorus (P), potassium (K), and zinc (Zn) was run to compare organic and conventional agricultural management practices. By combining different element-balance approaches (at farmgate, barn, and field scales) and further adapting these to the FARMFLOW model, we were able to combine mass flows and pools within the subsystems and establish links between subsystems in order to make farm-scale predictions. It was found that internal element flows on the farm are large and that there are farm internal sources (Zn) and loss terms (K). The approaches developed and tested at the Ojebyn farm are promising and considered generally adaptable to any farm.

Farm level risk factors for fluoroquinolone resistance in E. coli and thermophilic Campylobacter spp. on poultry farms.

PubMed

Taylor, N M; Wales, A D; Ridley, A M; Davies, R H

2016-10-01

Data on husbandry practices, performance, disease and drug use were collected during a cross-sectional survey of 89 poultry meat farms in England and Wales to provide information on possible risk factors for the occurrence of fluoroquinolone (FQ)-resistant bacteria. Faeces samples were used to classify farms as "affected" or "not affected" by FQ-resistant (FQr) Escherichia coli or Campylobacter spp. Risk factor analysis identified the use of FQ on the farms as having by far the strongest association, among the factors considered, with the occurrence of FQr bacteria. Resistant E. coli and/or Campylobacter spp. were found on 86% of the farms with a history of FQ use. However, a substantial proportion of farms with no history of FQ use also yielded FQr organisms, suggesting that resistant bacteria may transfer between farms. Further analysis suggested that for Campylobacter spp., on-farm hygiene, cleaning and disinfection between batches of birds and wildlife control were of most significance. By contrast, for E. coli biosecurity from external contamination was of particular importance, although the modelling indicated that other factors were likely to be involved. Detailed studies on a small number of sites showed that FQr E. coli can survive routine cleaning and disinfection. It appears difficult to avoid the occurrence of resistant bacteria when FQ are used on a farm, but the present findings provide evidence to support recommendations to reduce the substantial risk of the incidental acquisition of such resistance by farms where FQ are not used.

Microclimatic temperatures at Danish cattle farms, 2000-2016: quantifying the temporal and spatial variation in the transmission potential of Schmallenberg virus.

PubMed

Haider, Najmul; Cuellar, Ana Carolina; Kjær, Lene Jung; Sørensen, Jens Havskov; Bødker, Rene

2018-03-05

Microclimatic temperatures provide better estimates of vector-borne disease transmission parameters than standard meteorological temperatures, as the microclimate represent the actual temperatures to which the vectors are exposed. The objectives of this study were to quantify farm-level geographic variations and temporal patterns in the extrinsic incubation period (EIP) of Schmallenberg virus transmitted by Culicoides in Denmark through generation of microclimatic temperatures surrounding all Danish cattle farms. We calculated the hourly microclimatic temperatures at potential vector-resting sites within a 500 m radius of 22,004 Danish cattle farms for the months April to November from 2000 to 2016. We then modeled the daily EIP of Schmallenberg virus at each farm, assuming vectors choose resting sites either randomly or based on temperatures (warmest or coolest available) every hour. The results of the model output are presented as 17-year averages. The difference between the warmest and coolest microhabitats at the same farm was on average 3.7 °C (5th and 95th percentiles: 1.0 °C to 7.8 °C). The mean EIP of Schmallenberg virus (5th and 95th percentiles) for all cattle farms during spring, summer, and autumn was: 23 (18-33), 14 (12-18) and 51 (48-55) days, respectively, assuming Culicoides select resting sites randomly. These estimated EIP values were considerably shorter than those estimated using standard meteorological temperatures obtained from a numerical weather prediction model for the same periods: 43 (39-52), 21 (17-24) and 57 (55-58) days, respectively. When assuming that vectors actively select the coolest resting sites at a farm, the EIP was 2.3 (range: 1.1 to 4.1) times longer compared to that of the warmest sites at the same farm. We estimated a wide range of EIP in different microclimatic habitats surrounding Danish cattle farms, stressing the importance of identifying the specific resting sites of vectors when modeling vector-borne disease transmission. We found a large variation in the EIP among different farms, suggesting disease transmission may vary substantially between regions, even within a small country. Our findings could be useful for designing risk-based surveillance, and in the control and prevention of emerging and re-emerging vector-borne diseases.

Coupling the Weather Research and Forecasting (WRF) model and Large Eddy Simulations with Actuator Disk Model: predictions of wind farm power production

NASA Astrophysics Data System (ADS)

Garcia Cartagena, Edgardo Javier; Santoni, Christian; Ciri, Umberto; Iungo, Giacomo Valerio; Leonardi, Stefano

2015-11-01

A large-scale wind farm operating under realistic atmospheric conditions is studied by coupling a meso-scale and micro-scale models. For this purpose, the Weather Research and Forecasting model (WRF) is coupled with an in-house LES solver for wind farms. The code is based on a finite difference scheme, with a Runge-Kutta, fractional step and the Actuator Disk Model. The WRF model has been configured using seven one-way nested domains where the child domain has a mesh size one third of its parent domain. A horizontal resolution of 70 m is used in the innermost domain. A section from the smallest and finest nested domain, 7.5 diameters upwind of the wind farm is used as inlet boundary condition for the LES code. The wind farm consists in six-turbines aligned with the mean wind direction and streamwise spacing of 10 rotor diameters, (D), and 2.75D in the spanwise direction. Three simulations were performed by varying the velocity fluctuations at the inlet: random perturbations, precursor simulation, and recycling perturbation method. Results are compared with a simulation on the same wind farm with an ideal uniform wind speed to assess the importance of the time varying incoming wind velocity. Numerical simulations were performed at TACC (Grant CTS070066). This work was supported by NSF, (Grant IIA-1243482 WINDINSPIRE).

Modelling Farm Animal Welfare

PubMed Central

Collins, Lisa M.; Part, Chérie E.

2013-01-01

Simple Summary In this review paper we discuss the different modeling techniques that have been used in animal welfare research to date. We look at what questions they have been used to answer, the advantages and pitfalls of the methods, and how future research can best use these approaches to answer some of the most important upcoming questions in farm animal welfare. Abstract The use of models in the life sciences has greatly expanded in scope and advanced in technique in recent decades. However, the range, type and complexity of models used in farm animal welfare is comparatively poor, despite the great scope for use of modeling in this field of research. In this paper, we review the different modeling approaches used in farm animal welfare science to date, discussing the types of questions they have been used to answer, the merits and problems associated with the method, and possible future applications of each technique. We find that the most frequently published types of model used in farm animal welfare are conceptual and assessment models; two types of model that are frequently (though not exclusively) based on expert opinion. Simulation, optimization, scenario, and systems modeling approaches are rarer in animal welfare, despite being commonly used in other related fields. Finally, common issues such as a lack of quantitative data to parameterize models, and model selection and validation are discussed throughout the review, with possible solutions and alternative approaches suggested. PMID:26487411

Drivers of land use change and household determinants of sustainability in smallholder farming systems of Eastern Uganda.

PubMed

Ebanyat, Peter; de Ridder, Nico; de Jager, Andre; Delve, Robert J; Bekunda, Mateete A; Giller, Ken E

2010-07-01

Smallholder farming systems in sub-Saharan Africa have undergone changes in land use, productivity and sustainability. Understanding of the drivers that have led to changes in land use in these systems and factors that influence the systems' sustainability is useful to guide appropriate targeting of intervention strategies for improvement. We studied low input Teso farming systems in eastern Uganda from 1960 to 2001 in a place-based analysis combined with a comparative analysis of similar low input systems in southern Mali. This study showed that policy-institutional factors next to population growth have driven land use changes in the Teso systems, and that nutrient balances of farm households are useful indicators to identify their sustainability. During the period of analysis, the fraction of land under cultivation increased from 46 to 78%, and communal grazing lands nearly completely disappeared. Cropping diversified over time; cassava overtook cotton and millet in importance, and rice emerged as an alternative cash crop. Impacts of political instability, such as the collapse of cotton marketing and land management institutions, of communal labour arrangements and aggravation of cattle rustling were linked to the changes. Crop productivity in the farming systems is poor and nutrient balances differed between farm types. Balances of N, P and K were all positive for larger farms (LF) that had more cattle and derived a larger proportion of their income from off-farm activities, whereas on the medium farms (MF), small farms with cattle (SF1) and without cattle (SF2) balances were mostly negative. Sustainability of the farming system is driven by livestock, crop production, labour and access to off-farm income. Building private public partnerships around market-oriented crops can be an entry point for encouraging investment in use of external nutrient inputs to boost productivity in such African farming systems. However, intervention strategies should recognise the diversity and heterogeneity between farms to ensure efficient use of these external inputs.

Drivers of land use change and household determinants of sustainability in smallholder farming systems of Eastern Uganda

PubMed Central

de Ridder, Nico; de Jager, Andre; Delve, Robert J.; Bekunda, Mateete A.; Giller, Ken E.

2010-01-01

Smallholder farming systems in sub-Saharan Africa have undergone changes in land use, productivity and sustainability. Understanding of the drivers that have led to changes in land use in these systems and factors that influence the systems’ sustainability is useful to guide appropriate targeting of intervention strategies for improvement. We studied low input Teso farming systems in eastern Uganda from 1960 to 2001 in a place-based analysis combined with a comparative analysis of similar low input systems in southern Mali. This study showed that policy-institutional factors next to population growth have driven land use changes in the Teso systems, and that nutrient balances of farm households are useful indicators to identify their sustainability. During the period of analysis, the fraction of land under cultivation increased from 46 to 78%, and communal grazing lands nearly completely disappeared. Cropping diversified over time; cassava overtook cotton and millet in importance, and rice emerged as an alternative cash crop. Impacts of political instability, such as the collapse of cotton marketing and land management institutions, of communal labour arrangements and aggravation of cattle rustling were linked to the changes. Crop productivity in the farming systems is poor and nutrient balances differed between farm types. Balances of N, P and K were all positive for larger farms (LF) that had more cattle and derived a larger proportion of their income from off-farm activities, whereas on the medium farms (MF), small farms with cattle (SF1) and without cattle (SF2) balances were mostly negative. Sustainability of the farming system is driven by livestock, crop production, labour and access to off-farm income. Building private public partnerships around market-oriented crops can be an entry point for encouraging investment in use of external nutrient inputs to boost productivity in such African farming systems. However, intervention strategies should recognise the diversity and heterogeneity between farms to ensure efficient use of these external inputs. PMID:20628448

An application of ensemble/multi model approach for wind power production forecast.

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

2010-09-01

The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic model) seems to reach similar level of accuracy of those of the mesocale models (LAMI and RAMS). Finally we have focused on the possibility of using the ensemble model (ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first day ahead period. In fact low spreads often correspond to low forecast error. For longer forecast horizon the correlation between RMSE and ensemble spread decrease becoming too low to be used for this purpose.

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants.

PubMed

McEwan, Gregor F; Groner, Maya L; Fast, Mark D; Gettinby, George; Revie, Crawford W

2015-01-01

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments.

A cross-sectional study for predicting tail biting risk in pig farms using classification and regression tree analysis.

PubMed

Scollo, Annalisa; Gottardo, Flaviana; Contiero, Barbara; Edwards, Sandra A

2017-10-01

Tail biting in pigs has been an identified behavioural, welfare and economic problem for decades, and requires appropriate but sometimes difficult on-farm interventions. The aim of the paper is to introduce the Classification and Regression Tree (CRT) methodologies to develop a tool for prevention of acute tail biting lesions in pigs on-farm. A sample of 60 commercial farms rearing heavy pigs were involved; an on-farm visit and an interview with the farmer collected data on general management, herd health, disease prevention, climate control, feeding and production traits. Results suggest a value for the CRT analysis in managing the risk factors behind tail biting on a farm-specific level, showing 86.7% sensitivity for the Classification Tree and a correlation of 0.7 between observed and predicted prevalence of tail biting obtained with the Regression Tree. CRT analysis showed five main variables (stocking density, ammonia levels, number of pigs per stockman, type of floor and timeliness in feed supply) as critical predictors of acute tail biting lesions, which demonstrate different importance in different farms subgroups. The model might have reliable and practical applications for the support and implementation of tail biting prevention interventions, especially in case of subgroups of pigs with higher risk, helping farmers and veterinarians to assess the risk in their own farm and to manage their predisposing variables in order to reduce acute tail biting lesions. Copyright © 2017 Elsevier B.V. All rights reserved.

SWAT Model Application to Assess the Impact of Intensive Corn‐farming on Runoff, Sediments and Phosphorous loss from an Agricultural Watershed in Wisconsin

EPA Science Inventory

The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used the SWAT model to assess the impact of continuous-corn farming o...

The effect of stocking rate on soil solution nitrate concentrations beneath a free-draining dairy production system in Ireland.

PubMed

McCarthy, J; Delaby, L; Hennessy, D; McCarthy, B; Ryan, W; Pierce, K M; Brennan, A; Horan, B

2015-06-01

Economically viable and productive farming systems are required to meet the growing worldwide need for agricultural produce while at the same time reducing environmental impact. Within grazing systems of animal production, increasing concern exists as to the effect of intensive farming on potential N losses to ground and surface waters, which demands an appraisal of N flows within complete grass-based dairy farming systems. A 3-yr (2011 to 2013) whole-farm system study was conducted on a free-draining soil type that is highly susceptible to N loss under temperate maritime conditions. Soil solution concentrations of N from 3 spring-calving, grass-based systems designed to represent 3 alternative whole-farm stocking rate (SR) treatments in a post-milk quota situation in the European Union were compared: low (2.51 cows/ha), medium (2.92 cows/ha), and high SR (3.28 cows/ha). Each SR had its own farmlet containing 18 paddocks and 23 cows. Nitrogen loss from each treatment was measured using ceramic cups installed to a depth of 1m to sample the soil water. The annual and monthly average nitrate, nitrite, ammonia, and total N concentrations in soil solution collected were analyzed for each year using a repeated measures analysis. Subsequently, and based on the biological data collated from each farm system treatment within each year, the efficiency of N use was evaluated using an N balance model. Based on similar N inputs, increasing SR resulted in increased grazing efficiency and milk production per hectare. Stocking rate had no significant effect on soil solution concentrations of nitrate, nitrite, ammonia, or total N (26.0, 0.2, 2.4, and 32.3 mg/L, respectively). An N balance model evaluation of each treatment incorporating input and output data indicated that the increased grass utilization and milk production per hectare at higher SR resulted in a reduction in N surplus and increased N use efficiency. The results highlight the possibility for the sustainable intensification of grass-based dairy systems and suggest that, at the same level of N inputs, increasing SR has little effect on N loss in pastoral systems with limited imported feed. These results suggest that greater emphasis should be attributed to increased grass production and utilization under grazing to further improve the environmental impact of grazing systems. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

Model for wind resource analysis and for wind farm planning

NASA Astrophysics Data System (ADS)

Rozsavolgyi, K.

2008-12-01

Due to the ever increasing anthropogenic environmental pollution and the worldwide energy demand, the research and exploitation of environment-friendly renewable energy sources like wind, solar, geothermal, biomass become more and more important. During the last decade wind energy utilization has developed dynamically with big steps. Over just the past seven years, annual worldwide growth in installed wind capacity is near 30 %. Over 94 000 MW installed currently all over the world. Besides important economic incentives, the most extensive and most accurate scientific results are required in order to provide beneficial help for regional planning of wind farms to find appropriate sites for optimal exploitation of this renewable energy source. This research is on the spatial allocation of possible wind energy usage for wind farms. In order to carry this out a new model (CMPAM = Complex Multifactoral Polygenetic Adaptive Model) is being developed, which basically is a wind climate-oriented system, but other kind of factors are also considered. With this model those areas and terrains can be located where construction of large wind farms would be reasonable under the given conditions. This model consist of different sub- modules such as wind field modeling sub module (CMPAM/W) that is in high focus in this model development procedure. The wind field modeling core of CMPAM is mainly based on sGs (sequential Gaussian simulation) hence geostatistics, but atmospheric physics and GIS are used as well. For the application developed for the test area (Hungary) WAsP visualization results were used from 10 m height as input data. This data was geocorrected (GIS geometric correction) before it was used for further calculations. Using optimized variography and sequential Gaussian simulation, results were applied for the test area (Hungary) at different heights. Simulation results were produced and summarized for different heights. Furthermore an exponential regressive function describing the vertical wind profile was also established. The following altitudes were examined: 10 m, 30 m, 60 m, 80 m, 100 m, 120 m and 140 m. By the help of the complex analyses of CMPAM, where not just mere wind climatic and meteorological factors are considered, detailed results have been produced to 100 m height. Results at this altitude were analyzed and explained in a more detailed way because this altitude proved to be the first height that can ensure adequate wind speed for larger wind farms for wind energy exploitation in the test area. Keywords: wind site assessment, wind field modeling, complex modeling for planning of wind farm, sequential Gaussian simulation, GIS, wind profile

A multivariate and stochastic approach to identify key variables to rank dairy farms on profitability.

PubMed

Atzori, A S; Tedeschi, L O; Cannas, A

2013-05-01

The economic efficiency of dairy farms is the main goal of farmers. The objective of this work was to use routinely available information at the dairy farm level to develop an index of profitability to rank dairy farms and to assist the decision-making process of farmers to increase the economic efficiency of the entire system. A stochastic modeling approach was used to study the relationships between inputs and profitability (i.e., income over feed cost; IOFC) of dairy cattle farms. The IOFC was calculated as: milk revenue + value of male calves + culling revenue - herd feed costs. Two databases were created. The first one was a development database, which was created from technical and economic variables collected in 135 dairy farms. The second one was a synthetic database (sDB) created from 5,000 synthetic dairy farms using the Monte Carlo technique and based on the characteristics of the development database data. The sDB was used to develop a ranking index as follows: (1) principal component analysis (PCA), excluding IOFC, was used to identify principal components (sPC); and (2) coefficient estimates of a multiple regression of the IOFC on the sPC were obtained. Then, the eigenvectors of the sPC were used to compute the principal component values for the original 135 dairy farms that were used with the multiple regression coefficient estimates to predict IOFC (dRI; ranking index from development database). The dRI was used to rank the original 135 dairy farms. The PCA explained 77.6% of the sDB variability and 4 sPC were selected. The sPC were associated with herd profile, milk quality and payment, poor management, and reproduction based on the significant variables of the sPC. The mean IOFC in the sDB was 0.1377 ± 0.0162 euros per liter of milk (€/L). The dRI explained 81% of the variability of the IOFC calculated for the 135 original farms. When the number of farms below and above 1 standard deviation (SD) of the dRI were calculated, we found that 21 farms had dRI<-1 SD, 32 farms were between -1 SD and 0, 67 farms were between 0 and +1 SD, and 15 farms had dRI>+1 SD. The top 10% of the farms had a dRI greater than 0.170 €/L, whereas the bottom 10% farms had a dRI lower than 0.116 €/L. This stochastic approach allowed us to understand the relationships among the inputs of the studied dairy farms and to develop a ranking index for comparison purposes. The developed methodology may be improved by using more inputs at the dairy farm level and considering the actual cost to measure profitability. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Structural equation modeling of the relationships between pesticide poisoning, depressive symptoms and safety behaviors among Colorado farm residents.

PubMed

Beseler, Cheryl Lynn; Stallones, Lorann

2006-01-01

To use structural equation modeling (SEM) to test the theory that a past pesticide poisoning may act as a mediator in the relationship between depression and safety practices. Depression has been associated with pesticide poisoning and was more strongly associated with safety behaviors than workload, social support or health status of farm residents in a previously published report. A cross-sectional survey of farmers and their spouses was conducted in eight counties in northeastern Colorado. Depressive symptoms were assessed using the Center for Epidemiologic Studies-Depression (CES-D) scale. Exploratory and confirmatory factor analyses were used to identify symptoms most correlated with risk factors for depression and safety practices. SEM was used to examine theoretical causal models of the relationship between depression and poor health, financial difficulties, a history of pesticide poisoning, and safety practices. Exploratory factor analysis identified three factors in the CES-D scale. The SEM showed that poor health, financial difficulties and a history of pesticide poisoning significantly explained the depressive symptoms. Models with an excellent fit for the safety behaviors resulted when modeling the probability that the pesticide poisoning preceded depression, but no fit was possible when reversing the direction and modeling depression preceding pesticide poisoning. Specific depressive symptoms appeared to be significantly associated with primarily animal handling and farm machinery. The order of events, based on SEM results, was a pesticide poisoning preceding depressed mood in relation to safety behaviors.

CAP payments and agricultural GHG emissions in Italy. A farm-level assessment.

PubMed

Coderoni, Silvia; Esposti, Roberto

2018-06-15

The Common Agricultural Policy (CAP) is an important external driver of European agricultural production. Nowadays and in its envisioned future structure post-2020, the CAP has among its major objectives tackling climate change, for what concerns both adaptation and mitigation strategies. However, little is known about the link between past CAP reforms and agricultural greenhouse gases (GHG) emissions. This paper investigates the possible role played by the Fischler Reform (FR) on the agricultural GHG emissions at the farm level. The FR represents a major CAP reform for which data availability allows an ex-post analysis about its actual impacts. The empirical analysis concerns a balanced panel of 6542 Italian Farm Accountancy Data Network observed over years the 2003-2007. Multinomial Logit models are estimated in sequence to express how the farm-level production choices, and the respective emissions, vary over time also in response to CAP expenditure. Results suggest that CAP expenditure had a role in the evolution of the farm-level emissions, though the direction of this effect may differ across farms and deserves further investigation. Copyright © 2018 Elsevier B.V. All rights reserved.

The effect of feed demand on greenhouse gas emissions and farm profitability for organic and conventional dairy farms.

PubMed

Kiefer, Lukas; Menzel, Friederike; Bahrs, Enno

2014-12-01

The reduction of product-related greenhouse gas (GHG) emissions in milk production appears to be necessary. The reduction of emissions on an individual farm might be highly accepted by farm owners if it were accompanied by an increase in profitability. Using life cycle assessments to determine the product carbon footprints (PCF) and farm-level evaluations to record profitability, we explored opportunities for optimization based on analysis of 81 organic and conventional pasture-based dairy farms in southern Germany. The objective of the present study was to detect common determining factors for low PCF and high management incomes (MI) to achieve GHG reductions at the lowest possible operational cost. In our sample, organic farms, which performed economically better than conventional farms, produced PCF that were significantly higher than those produced by conventional farms [1.61 ± 0.29 vs. 1.45 ± 0.28 kg of CO₂ equivalents (CO₂eq) per kg of milk; means ± SD)]. A multiple linear regression analysis of the sample demonstrated that low feed demand per kilogram of milk, high grassland yield, and low forage area requirements per cow are the main factors that decrease PCF. These factors are also useful for improving a farm's profitability in principle. For organic farms, a reduction of feed demand of 100 g/kg of milk resulted in a PCF reduction of 105 g of CO₂eq/kg of milk and an increase in MI of approximately 2.1 euro cents (c)/kg of milk. For conventional farms, a decrease of feed demand of 100 g/kg of milk corresponded to a reduction in PCF of 117 g of CO₂eq/kg of milk and an increase in MI of approximately 3.1 c/kg of milk. Accordingly, farmers could achieve higher profits while reducing GHG emissions. Improved education and training of farmers and consultants regarding GHG mitigation and farm profitability appear to be the best methods of improving efficiency under traditional and organic farming practices.

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

The use of a geographic information system to identify a dairy goat farm as the most likely source of an urban Q-fever outbreak.

PubMed

Schimmer, Barbara; Ter Schegget, Ronald; Wegdam, Marjolijn; Züchner, Lothar; de Bruin, Arnout; Schneeberger, Peter M; Veenstra, Thijs; Vellema, Piet; van der Hoek, Wim

2010-03-16

A Q-fever outbreak occurred in an urban area in the south of the Netherlands in May 2008. The distribution and timing of cases suggested a common source. We studied the spatial relationship between the residence locations of human cases and nearby small ruminant farms, of which one dairy goat farm had experienced abortions due to Q-fever since mid April 2008. A generic geographic information system (GIS) was used to develop a method for source detection in the still evolving major epidemic of Q-fever in the Netherlands. All notified Q-fever cases in the area were interviewed. Postal codes of cases and of small ruminant farms (size >40 animals) located within 5 kilometres of the cluster area were geo-referenced as point locations in a GIS-model. For each farm, attack rates and relative risks were calculated for 5 concentric zones adding 1 kilometre at a time, using the 5-10 kilometres zone as reference. These data were linked to the results of veterinary investigations. Persons living within 2 kilometres of an affected dairy goat farm (>400 animals) had a much higher risk for Q-fever than those living more than 5 kilometres away (Relative risk 31.1 [95% CI 16.4-59.1]). The study supported the hypothesis that a single dairy goat farm was the source of the human outbreak. GIS-based attack rate analysis is a promising tool for source detection in outbreaks of human Q-fever.

SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.

PubMed

Del Prado, A; Misselbrook, T; Chadwick, D; Hopkins, A; Dewhurst, R J; Davison, P; Butler, A; Schröder, J; Scholefield, D

2011-09-01

Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too). Copyright © 2011 Elsevier B.V. All rights reserved.

Modelling impacts of offshore wind farms on trophic web: the Courseulles-sur-Mer case study

NASA Astrophysics Data System (ADS)

Raoux, Aurore; Pezy, Jean-Philippe; Dauvin, Jean-Claude; Tecchio, samuele; Degraer, Steven; Wilhelmsson, Dan; Niquil, Nathalie

2016-04-01

The French government is planning the construction of three offshore wind farms in Normandy. These offshore wind farms will integrate into an ecosystem already subject to a growing number of anthropogenic disturbances such as transportation, fishing, sediment deposit, and sediment extraction. The possible effects of this cumulative stressors on ecosystem functioning are still unknown, but they could impact their resilience, making them susceptible to changes from one stable state to another. Understanding the behaviour of these marine coastal complex systems is essential in order to anticipate potential state changes, and to implement conservation actions in a sustainable manner. Currently, there are no global and integrated studies on the effects of construction and exploitation of offshore wind farms. Moreover, approaches are generally focused on the conservation of some species or groups of species. Here, we develop a holistic and integrated view of ecosystem impacts through the use of trophic webs modelling tools. Trophic models describe the interaction between biological compartments at different trophic levels and are based on the quantification of flow of energy and matter in ecosystems. They allow the application of numerical methods for the characterization of emergent properties of the ecosystem, also called Ecological Network Analysis (ENA). These indices have been proposed as ecosystem health indicators as they have been demonstrated to be sensitive to different impacts on marine ecosystems. We present here in detail the strategy for analysing the potential environmental impacts of the construction of the Courseulles-sur-Mer offshore wind farm (Bay of Seine) such as the reef effect through the use of the Ecopath with Ecosim software. Similar Ecopath simulations will be made in the future on the Le Tréport offshore wind farm site. Results will contribute to a better knowledge of the impacts of the offshore wind farms on ecosystems. They also allow to define recommendations for environmental managers and industry in terms of monitoring the effects of Marine Renewable Energy, not only locally, but also on other sites, national and European levels. Finally, this approach could contribute to a better social acceptability of Marine Renewable Energy projects allowing a holistic vision of all pressures on ecosystems. Keywords: Marine Renewable Energies, trophic model Contact author: Aurore Raoux, UNICAEN, raoux.aurore@gmail.com

Centralization of dairy farming facilities for improved economics and environmental quality.

PubMed

Inaba, Rokuta; Furuichi, Tohru; Komatsu, Toshihiro; Tanikawa, Noboru; Ishii, Kazuei

2009-01-01

In Japan, most farm animal excreta has been stored directly on farmland. Runoff from this storage has often caused water pollution. Biogasification is anticipated as an important technology to manage excreta properly, but complex problems hinder its introduction. Economic aspects of management have been especially difficult for dairy farmers. For this study, structural problems regarding introduction of biogasification into dairy farming were identified. Subsequently, a desirable system of dairy farming including biogasification was suggested, and an evaluation model of the financial balance was constructed. A case study using current financial balances of several systems of dairy farming was evaluated using the constructed model and actual data. The systems were based on several policy alternatives including the suggested system mentioned above. Results show that a farmer can obtain sufficient income from a system featuring centralization of dairy housing and biogasification facilities and coordinated management by over six farmers.

Low Pathogenic Avian Influenza Exposure Risk Assessment in Australian Commercial Chicken Farms.

PubMed

Scott, Angela Bullanday; Toribio, Jenny-Ann; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study investigated the pathways of exposure to low pathogenic avian influenza (LPAI) virus among Australian commercial chicken farms and estimated the likelihood of this exposure occurring using scenario trees and a stochastic modeling approach following the World Organization for Animal Health methodology for risk assessment. Input values for the models were sourced from scientific literature and an on-farm survey conducted during 2015 and 2016 among Australian commercial chicken farms located in New South Wales and Queensland. Outputs from the models revealed that the probability of a first LPAI virus exposure to a chicken in an Australian commercial chicken farms from one wild bird at any point in time is extremely low. A comparative assessment revealed that across the five farm types (non-free-range meat chicken, free-range meat chicken, cage layer, barn layer, and free range layer farms), free-range layer farms had the highest probability of exposure (7.5 × 10 -4 ; 5% and 95%, 5.7 × 10 -4 -0.001). The results indicate that the presence of a large number of wild birds on farm is required for exposure to occur across all farm types. The median probability of direct exposure was highest in free-range farm types (5.6 × 10 -4 and 1.6 × 10 -4 for free-range layer and free-range meat chicken farms, respectively) and indirect exposure was highest in non-free-range farm types (2.7 × 10 -4 , 2.0 × 10 -4 , and 1.9 × 10 -4 for non-free-range meat chicken, cage layer, and barn layer farms, respectively). The probability of exposure was found to be lowest in summer for all farm types. Sensitivity analysis revealed that the proportion of waterfowl among wild birds on the farm, the presence of waterfowl in the range and feed storage areas, and the prevalence of LPAI in wild birds are the most influential parameters for the probability of Australian commercial chicken farms being exposed to avian influenza (AI) virus. These results highlight the importance of ensuring good biosecurity on farms to minimize the risk of exposure to AI virus and the importance of continuous surveillance of LPAI prevalence including subtypes in wild bird populations.

Low Pathogenic Avian Influenza Exposure Risk Assessment in Australian Commercial Chicken Farms

PubMed Central

Scott, Angela Bullanday; Toribio, Jenny-Ann; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study investigated the pathways of exposure to low pathogenic avian influenza (LPAI) virus among Australian commercial chicken farms and estimated the likelihood of this exposure occurring using scenario trees and a stochastic modeling approach following the World Organization for Animal Health methodology for risk assessment. Input values for the models were sourced from scientific literature and an on-farm survey conducted during 2015 and 2016 among Australian commercial chicken farms located in New South Wales and Queensland. Outputs from the models revealed that the probability of a first LPAI virus exposure to a chicken in an Australian commercial chicken farms from one wild bird at any point in time is extremely low. A comparative assessment revealed that across the five farm types (non-free-range meat chicken, free-range meat chicken, cage layer, barn layer, and free range layer farms), free-range layer farms had the highest probability of exposure (7.5 × 10−4; 5% and 95%, 5.7 × 10−4—0.001). The results indicate that the presence of a large number of wild birds on farm is required for exposure to occur across all farm types. The median probability of direct exposure was highest in free-range farm types (5.6 × 10−4 and 1.6 × 10−4 for free-range layer and free-range meat chicken farms, respectively) and indirect exposure was highest in non-free-range farm types (2.7 × 10−4, 2.0 × 10−4, and 1.9 × 10−4 for non-free-range meat chicken, cage layer, and barn layer farms, respectively). The probability of exposure was found to be lowest in summer for all farm types. Sensitivity analysis revealed that the proportion of waterfowl among wild birds on the farm, the presence of waterfowl in the range and feed storage areas, and the prevalence of LPAI in wild birds are the most influential parameters for the probability of Australian commercial chicken farms being exposed to avian influenza (AI) virus. These results highlight the importance of ensuring good biosecurity on farms to minimize the risk of exposure to AI virus and the importance of continuous surveillance of LPAI prevalence including subtypes in wild bird populations. PMID:29755987

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Effects of stored feed cropping systems and farm size on the profitability of Maine organic dairy farm simulations.

PubMed

Hoshide, A K; Halloran, J M; Kersbergen, R J; Griffin, T S; DeFauw, S L; LaGasse, B J; Jain, S

2011-11-01

United States organic dairy production has increased to meet the growing demand for organic milk. Despite higher prices received for milk, organic dairy farmers have come under increasing financial stress due to increases in concentrated feed prices over the past few years, which can make up one-third of variable costs. Market demand for milk has also leveled in the last year, resulting in some downward pressure on prices paid to dairy farmers. Organic dairy farmers in the Northeast United States have experimented with growing different forage and grain crops to maximize on-farm production of protein and energy to improve profitability. Three representative organic feed systems were simulated using the integrated farm system model for farms with 30, 120, and 220 milk cows. Increasing intensity of equipment use was represented by organic dairy farms growing only perennial sod (low) to those with corn-based forage systems, which purchase supplemental grain (medium) or which produce and feed soybeans (high). The relative profitability of these 3 organic feed systems was strongly dependent on dairy farm size. From results, we suggest smaller organic dairy farms can be more profitable with perennial sod-based rather than corn-based forage systems due to lower fixed costs from using only equipment associated with perennial forage harvest and storage. The largest farm size was more profitable using a corn-based system due to greater economies of scale for growing soybeans, corn grain, winter cereals, and corn silages. At an intermediate farm size of 120 cows, corn-based forage systems were more profitable if perennial sod was not harvested at optimum quality, corn was grown on better soils, or if milk yield was 10% higher. Delayed harvest decreased the protein and energy content of perennial sod crops, requiring more purchased grain to balance the ration and resulting in lower profits. Corn-based systems were less affected by lower perennial forage quality, as corn silage is part of the forage base. Growing on better soils increased corn yields more than perennial forage yields. Large corn-based organic dairy farms that produced and fed soybeans minimized off-farm grain purchases and were the most profitable among large farms. Although perennial sod-based systems purchased more grain, these organic systems were more profitable under timely forage harvest, decreased soil quality, and relatively lower purchased energy prices and higher protein supplement prices. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Including spatial data in nutrient balance modelling on dairy farms

NASA Astrophysics Data System (ADS)

van Leeuwen, Maricke; van Middelaar, Corina; Stoof, Cathelijne; Oenema, Jouke; Stoorvogel, Jetse; de Boer, Imke

2017-04-01

The Annual Nutrient Cycle Assessment (ANCA) calculates the nitrogen (N) and phosphorus (P) balance at a dairy farm, while taking into account the subsequent nutrient cycles of the herd, manure, soil and crop components. Since January 2016, Dutch dairy farmers are required to use ANCA in order to increase understanding of nutrient flows and to minimize nutrient losses to the environment. A nutrient balance calculates the difference between nutrient inputs and outputs. Nutrients enter the farm via purchased feed, fertilizers, deposition and fixation by legumes (nitrogen), and leave the farm via milk, livestock, manure, and roughages. A positive balance indicates to which extent N and/or P are lost to the environment via gaseous emissions (N), leaching, run-off and accumulation in soil. A negative balance indicates that N and/or P are depleted from soil. ANCA was designed to calculate average nutrient flows on farm level (for the herd, manure, soil and crop components). ANCA was not designed to perform calculations of nutrient flows at the field level, as it uses averaged nutrient inputs and outputs across all fields, and it does not include field specific soil characteristics. Land management decisions, however, such as the level of N and P application, are typically taken at the field level given the specific crop and soil characteristics. Therefore the information that ANCA provides is likely not sufficient to support farmers' decisions on land management to minimize nutrient losses to the environment. This is particularly a problem when land management and soils vary between fields. For an accurate estimate of nutrient flows in a given farming system that can be used to optimize land management, the spatial scale of nutrient inputs and outputs (and thus the effect of land management and soil variation) could be essential. Our aim was to determine the effect of the spatial scale of nutrient inputs and outputs on modelled nutrient flows and nutrient use efficiencies at Dutch dairy farms. We selected two dairy farms located on cover sands in the Netherlands. One farm was located on relatively homogeneous soil type, and one on many different soil types within the sandy soils. A full year of data of N and P inputs and outputs on farm and field level were provided by the farmers, including field level yields, yield composition, manure composition, degree of grazing and degree of mowing. Soil heterogeneity was defined as the number of soil units within the farm corrected for surface area, and quantified from the Dutch 1:50.000 soil map. N and P balances at farm and field level were determined, as well as differences in nutrient use efficiency, leaching, and N emission. We will present the effect of the spatial scale on nutrient balance analysis and discuss to which degree any differences are caused by within-farm land management and soil variation. This study highlights to which extent within-farm land management and soil variation should be taken into account when modelling nutrient flows and nutrient use efficiencies at farm level, to contribute to field-based decision making for improved land management.

An economic analysis of hyperketonemia testing and propylene glycol treatment strategies in early lactation dairy cattle.

PubMed

McArt, J A A; Nydam, D V; Oetzel, G R; Guard, C L

2014-11-01

The purpose was to develop stochastic economic models which address variation in disease risks and costs in order to evaluate different simulated on-farm testing and propylene glycol (PG) treatment strategies based on herd hyperketonemia (HYK) incidence during the first 30 DIM. Data used in model development concerning the difference in health and production consequences between HYK and non-ketotic cows were based on results from 10 studies representing over 13,000 cows from 833 dairy farms in North America, Canada, and Europe. Inputs for PG associated variables were based on a large field trial using cows from 4 free-stall dairy herds (2 in New York and 2 in Wisconsin). Four simulated on-farm testing and treatment strategies were analyzed at herd HYK incidences ranging from 5% to 80% and included: 1) treating all cows with 5d of PG starting at 5 DIM, 2) testing all cows for HYK 1 day per week (e.g. Mondays) from 3 to 16 DIM and treating all positive cows with 5d of oral PG, 3) testing all cows for HYK 2 days per week (e.g. Mondays and Thursdays) from 3 to 9 DIM and treating all positive cows with 5d of oral PG, and 4) testing all cows for HYK 3 days per week (e.g. Mondays, Wednesdays, and Fridays) from 3 to 16 DIM and treating all positive cows with 5d of oral PG. Cost-benefit analysis included the costs associated with labor to test cows, β-hydroxybutyrate test strips, labor to treat cows, PG, and the associated gain in milk production, decrease in DA and early removal risks of PG treated HYK positive cows compared to non-treated HYK positive cows. Stochastic models were developed to account for variability in the distribution of input variables. Per 100 fresh cows in a herd with an HYK incidence of 40%, the mean economic benefits of the 4 different strategies were $1088, $744, $1166, and $760, respectively. Testing cows 2 days per week from 3 to 9 DIM was the most cost-effective strategy for herds with HYK incidences between 15% and 50%; above 50%, treating all fresh cows with 5d of PG was the most cost-effective strategy. These results show that for herds similar to those used in model, when herd HYK incidences rise above 25%, almost any HYK testing and treatment protocol will be economically beneficial for the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Object view in spatial system dynamics: a grassland farming example

PubMed Central

Neuwirth, Christian; Hofer, Barbara; Schaumberger, Andreas

2016-01-01

Abstract Spatial system dynamics (SSD) models are typically implemented by linking stock variables to raster grids while the use of object representations of human artefacts such as buildings or ownership has been limited. This limitation is addressed by this article, which demonstrates the use of object representations in SSD. The objects are parcels of land that are attributed to grassland farms. The model simulates structural change in agriculture, i.e., change in the size of farms. The aim of the model is to reveal relations between structural change, farmland fragmentation and variable farmland quality. Results show that fragmented farms tend to become consolidated by structural change, whereas consolidated initial conditions result in a significant increase of fragmentation. Consolidation is reinforced by a dynamic land market and high transportation costs. The example demonstrates the capabilities of the object-based approach for integrating object geometries (parcel shapes) and relations between objects (distances between parcels) dynamically in SSD. PMID:28190972

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jannik, Tim; Hartman, Larry

During the operational history of Savannah River Site, many different radionuclides have been released from site facilities. However, as shown in this analysis, only a relatively small number of the released radionuclides have been significant contributors to doses to the offsite public. This report is an update to the 2011 analysis, Critical Radionuclide and Pathway Analysis for the Savannah River Site. SRS-based Performance Assessments for E-Area, Saltstone, F-Tank Farm, H-Tank Farm, and a Comprehensive SRS Composite Analysis have been completed. The critical radionuclides and pathways identified in those extensive reports are also detailed and included in this analysis.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

Using a rule-based envelope model to predict the expansion of habitat suitability within New Zealand for the tick Haemaphysalis longicornis, with future projections based on two climate change scenarios.

PubMed

Lawrence, K E; Summers, S R; Heath, A C G; McFadden, A M J; Pulford, D J; Tait, A B; Pomroy, W E

2017-08-30

Haemaphysalis longicornis is the only species of tick present in New Zealand which infests livestock and is also the only competent vector for Theileria orientalis. Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis, an obligate intracellular protozoan parasite of cattle and buffaloes. The aim of this study was to predict the spatial distribution of habitat suitability of New Zealand for the tick H. longicornis using a simple rule-based climate envelope model, to validate the model against published data and use the validated model to project an expansion in habitat suitability for H. longicornis under two alternative climate change scenarios for the periods 2046-2065 and 2081-2100, relative to the climate of 1981-2010. A rule-based climate envelope model was developed based on the environmental requirements for off-host tick survival. The resulting model was validated against a maximum entropy environmental niche model of environmental suitability for T. orientalis transmission and against a H. longicornis occurrence map. Validation was completed using the I-similarity statistic and by linear regression. The H. longicornis climate envelope model predicted that 75% of cattle farms in the North Island, 3% of cattle farms in the South Island and 54% of cattle farms in New Zealand overall have habitats potentially suitable for the establishment of H. longicornis. The validation methods showed an acceptable level of agreement between the envelope model and published data. Both of the climate change scenarios, for each of the time periods, projected only slight to moderate increases in the average farm habitat suitability scores for all the South Island regions. However, only for the West Coast, Marlborough, Tasman, and Nelson regions did these increases in environmental suitability translate into an increased proportion of cattle farms with low or high H. longicornis habitat suitability. These results will have important implications for the geographical progression of Theileria-associated bovine anaemia (TABA) in New Zealand and will also be of interest to Haemaphysalis longicornis researchers in Australia, Japan, Korea and New Zealand. Copyright © 2017 Elsevier B.V. All rights reserved.

Culturally relevant model program to prevent and reduce agricultural injuries.

PubMed

Helitzer, D L; Hathorn, G; Benally, J; Ortega, C

2014-07-01

Limited research has explored pesticide injury prevention among American Indian farmers. In a five-year agricultural intervention, a university-community partnership, including the University of New Mexico School of Medicine, New Mexico State University, Shiprock Area Cooperative Extension Service, and Navajo Nation communities, used a culturally relevant model to introduce and maintain safe use of integrated pest management techniques. We applied the Diffusion of Innovations theory and community-based approaches to tailor health promotion strategies for our intervention. In a longitudinal study with repeated measures, we trained six "model farmers" to be crop management experts in pesticide safety, application, and control. Subsequently, these model farmers worked with 120 farm families randomized into two groups: intervention (Group 1) and delayed intervention (Group 2). Measurements included a walk-through analysis, test of knowledge and attitudes, and yield analysis. Both groups demonstrated improvements in pesticide storage behaviors after training. Test scores regarding safety practices improved significantly: from 57.3 to 72.4 for Group 1 and from 52.6 to 76.3 for Group 2. Group 1 maintained their knowledge and safety practices after the intervention. Attitudes about pesticides and communication of viewpoints changed across the study years. With pesticides and fertilizer, the number of corn ears increased by 56.3% and yield (kg m(-2)) of alfalfa increased by 41.2%. The study combined traditional farming practices with culturally relevant approaches and behavior change theory to affect knowledge, safety practices, attitudes, communication channels, and crop yield. Storage behaviors, use of pesticides and safety and application equipment, and safety practice knowledge changed significantly, as did attitudes about social networking, social support, and the compatibility and relative advantage of pesticides for farms.

ANEMOS: Development of a next generation wind power forecasting system for the large-scale integration of onshore and offshore wind farms.

NASA Astrophysics Data System (ADS)

Kariniotakis, G.; Anemos Team

2003-04-01

Objectives: Accurate forecasting of the wind energy production up to two days ahead is recognized as a major contribution for reliable large-scale wind power integration. Especially, in a liberalized electricity market, prediction tools enhance the position of wind energy compared to other forms of dispatchable generation. ANEMOS, is a new 3.5 years R&D project supported by the European Commission, that resembles research organizations and end-users with an important experience on the domain. The project aims to develop advanced forecasting models that will substantially outperform current methods. Emphasis is given to situations like complex terrain, extreme weather conditions, as well as to offshore prediction for which no specific tools currently exist. The prediction models will be implemented in a software platform and installed for online operation at onshore and offshore wind farms by the end-users participating in the project. Approach: The paper presents the methodology of the project. Initially, the prediction requirements are identified according to the profiles of the end-users. The project develops prediction models based on both a physical and an alternative statistical approach. Research on physical models gives emphasis to techniques for use in complex terrain and the development of prediction tools based on CFD techniques, advanced model output statistics or high-resolution meteorological information. Statistical models (i.e. based on artificial intelligence) are developed for downscaling, power curve representation, upscaling for prediction at regional or national level, etc. A benchmarking process is set-up to evaluate the performance of the developed models and to compare them with existing ones using a number of case studies. The synergy between statistical and physical approaches is examined to identify promising areas for further improvement of forecasting accuracy. Appropriate physical and statistical prediction models are also developed for offshore wind farms taking into account advances in marine meteorology (interaction between wind and waves, coastal effects). The benefits from the use of satellite radar images for modeling local weather patterns are investigated. A next generation forecasting software, ANEMOS, will be developed to integrate the various models. The tool is enhanced by advanced Information Communication Technology (ICT) functionality and can operate both in stand alone, or remote mode, or be interfaced with standard Energy or Distribution Management Systems (EMS/DMS) systems. Contribution: The project provides an advanced technology for wind resource forecasting applicable in a large scale: at a single wind farm, regional or national level and for both interconnected and island systems. A major milestone is the on-line operation of the developed software by the participating utilities for onshore and offshore wind farms and the demonstration of the economic benefits. The outcome of the ANEMOS project will help consistently the increase of wind integration in two levels; in an operational level due to better management of wind farms, but also, it will contribute to increasing the installed capacity of wind farms. This is because accurate prediction of the resource reduces the risk of wind farm developers, who are then more willing to undertake new wind farm installations especially in a liberalized electricity market environment.

Cost-effectiveness analysis of policy instruments for greenhouse gas emission mitigation in the agricultural sector.

PubMed

Bakam, Innocent; Balana, Bedru Babulo; Matthews, Robin

2012-12-15

Market-based policy instruments to reduce greenhouse gas (GHG) emissions are generally considered more appropriate than command and control tools. However, the omission of transaction costs from policy evaluations and decision-making processes may result in inefficiency in public resource allocation and sub-optimal policy choices and outcomes. This paper aims to assess the relative cost-effectiveness of market-based GHG mitigation policy instruments in the agricultural sector by incorporating transaction costs. Assuming that farmers' responses to mitigation policies are economically rationale, an individual-based model is developed to study the relative performances of an emission tax, a nitrogen fertilizer tax, and a carbon trading scheme using farm data from the Scottish farm account survey (FAS) and emissions and transaction cost data from literature metadata survey. Model simulations show that none of the three schemes could be considered the most cost effective in all circumstances. The cost effectiveness depends both on the tax rate and the amount of free permits allocated to farmers. However, the emissions trading scheme appears to outperform both other policies in realistic scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

PubMed

Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

2014-01-01

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Defining "Sector 3" Poultry Layer Farms in Relation to H5N1-HPAI-An Example from Java, Indonesia.

PubMed

Durr, Peter A; Wibowo, Michael Haryadi; Tarigan, Simson; Artanto, Sidna; Rosyid, Murni Nurhasanah; Ignjatovic, Jagoda

2016-05-01

To help guide surveillance and control of highly pathogenic avian influenza subtype H5N1 (H5N1-HPAI), the Food and Agriculture Organization of the United Nations in 2004 devised a poultry farm classification system based on a combination of production and biosecurity practices. Four "Sectors" were defined, and this scheme has been widely adopted within Indonesia to guide national surveillance and control strategies. Nevertheless, little detailed research into the robustness of this classification system has been conducted, particularly as it relates to independent, small to medium-sized commercial poultry farms (Sector 3). Through an analysis of questionnaire data collected as part of a survey of layer farms in western and central Java, all of which were classified as Sector 3 by local veterinarians, we provide benchmark data on what defines this sector. A multivariate analysis of the dataset, using hierarchical cluster analysis, identified three groupings of the farms, which were defined by a combination of production-and biosecurity-related variables, particularly those related to farm size and (the lack of) washing and disinfection practices. Nevertheless, the relationship between production-related variables and positive biosecurity practices was poor, and larger farms did not have an overall higher total biosecurity score than small or medium-sized ones. Further research is required to define the properties of poultry farms in Indonesia that are most closely related to effective biosecurity and the prevention of H5N1-HPAI.

Turbulent kinetics of a large wind farm and their impact in the neutral boundary layer

DOE PAGES

Na, Ji Sung; Koo, Eunmo; Munoz-Esparza, Domingo; ...

2015-12-28

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines createsmore » the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.« less

Sustainable management of agriculture activity on areas with soil vulnerability to compaction trough a developed decision support system (DSS)

NASA Astrophysics Data System (ADS)

Moretto, Johnny; Fantinato, Luciano; Rasera, Roberto

2017-04-01

One of the main environmental effects of agriculture is the negative impacts on areas with soil vulnerability to compaction and undersurface water derived from inputs and treatment distributions. A solution may represented from the "Precision Farming". Precision Farming refers to a management concept focusing on (near-real time) observation, measurement and responses to inter- and intra-variability in crops, fields and animals. Potential benefits may include increasing crop yields and animal performance, cost and labour reduction and optimisation of process inputs, all of which would increase profitability. At the same time, Precision Farming should increase work safety and reduce the environmental impacts of agriculture and farming practices, thus contributing to the sustainability of agricultural production. The concept has been made possible by the rapid development of ICT-based sensor technologies and procedures along with dedicated software that, in the case of arable farming, provides the link between spatially-distributed variables and appropriate farming practices such as tillage, seeding, fertilisation, herbicide and pesticide application, and harvesting. Much progress has been made in terms of technical solutions, but major steps are still required for the introduction of this approach over the common agricultural practices. There are currently a large number of sensors capable of collecting data for various applications (e.g. Index of vegetation vigor, soil moisture, Digital Elevation Models, meteorology, etc.). The resulting large volumes of data need to be standardised, processed and integrated using metadata analysis of spatial information, to generate useful input for decision-support systems. In this context, a user-friendly IT applications has been developed, for organizing and processing large volumes of data from different types of remote sensing and meteorological sensors, and for integrating these data into user-friendly farm management support systems able to support the farm manager. In this applications will be possible to implement numerical models to support the farm manager on the best time to work in field and/or the best trajectory to follow with a GPS navigation system on soil vulnerability to compaction. In addition to provide "as applied map" to indicate in each part of the field the exact needed quantity of inputs and treatments. This new working models for data management will allow to a most efficient resource usage contributing in a more sustainable agriculture both for a more economic benefits for the farmers and for reduction of environmental soil and undersurface water impacts.

Estimating occupational illness, injury, and mortality in food production in the United States: A farm-to-table analysis

PubMed Central

Leon, Juan S.; Newman, Lee S.

2015-01-01

Objectives The study provides a novel model and more comprehensive estimates of the burden of occupational morbidity and mortality in food-related industries, using a farm-to-table approach. Methods The authors analyzed 2008–2010 US Bureau of Labor Statistics data for private industries in the different stages of the farm-to-table model (production; processing; distribution and storage; retail and preparation). Results The morbidity rate for food system industries were significantly higher than the morbidity rate for non-food system industries (Rate Ratio (RR)=1.62, 95% Confidence Interval (CI): 1.30–2.01). Furthermore, the occupational mortality rate for food system industries was significantly higher than the national non-food occupational mortality rate (RR=9.51, 95% CI: 2.47–36.58). Conclusions This is the first use of the farm-to-table model to assess occupational morbidity and mortality, and these findings highlighting specific workplace hazards across food system industries. PMID:25970031

A game theory based framework for assessing incentives for local area collaboration with an application to Scottish salmon farming.

PubMed

Murray, Alexander G

2014-08-01

Movements of water that transport pathogens mean that in net-pen aquaculture diseases are often most effectively managed collaboratively among neighbours. Such area management is widely and explicitly applied for pathogen management in marine salmon farms. Effective area management requires the active support of farm managers and a simple game-theory based framework was developed to identify the conditions required under which collaboration is perceived to be in their own best interest. The model applied is based on area management as practiced for Scottish salmon farms, but its simplicity allows it to be generalised to other area-managed net-pen aquaculture systems. In this model managers choose between purchasing tested pathogen-free fish or cheaper, untested fish that might carry pathogens. Perceived pay-off depends on degree of confidence that neighbours will not buy untested fish, risking input of pathogens that spread between farms. For a given level of risk, confidence in neighbours is most important in control of moderate-impact moderate-probability diseases. Common low-impact diseases require high confidence since there is a high probability a neighbour will import, while testing for rare high-impact diseases may be cost-effective regardless of neighbours actions. In some cases testing may be beneficial at an area level, even if all individual farms are better off not testing. Higher confidence is required for areas with many farms and so focusing management on smaller, epidemiologically imperfect, areas may be more effective. The confidence required for collaboration can be enhanced by the development of formal agreements and the involvement of outside disinterested parties such as trade bodies or government. Copyright © 2014. Published by Elsevier B.V.

An empirical analysis of farm vehicle crash injury severities on Iowa's public road system.

PubMed

Gkritza, Konstantina; Kinzenbaw, Caroline R; Hallmark, Shauna; Hawkins, Neal

2010-07-01

Farm vehicle crashes are a major safety concern for farmers as well as all other users of the public road system in agricultural states. Using data on farm vehicle crashes that occurred on Iowa's public roads between 2004 and 2006, we estimate a multinomial logit model to identify crash-, farm vehicle-, and driver-specific factors that determine farm vehicle crash injury severity outcomes. Estimation findings indicate that there are crash patterns (rear-end manner of collision; single-vehicle crash; farm vehicle crossed the centerline or median) and conditions (obstructed vision and crash in rural area; dry road, dark lighting, speed limit 55 mph or higher, and harvesting season), as well as farm vehicle and driver-contributing characteristics (old farm vehicle, young farm vehicle driver), where targeted intervention can help reduce the severity of crash outcomes. Determining these contributing factors and their effect is the first step to identifying countermeasures and safety strategies in a bid to improve transportation safety for all users on the public road system in Iowa as well as other agricultural states. Copyright 2010 Elsevier Ltd. All rights reserved.

The interrelationship of households economics activities of upland rice farmers in rain-fed farming in Ponjong Sub-district, Gunungkidul District, Indonesia

NASA Astrophysics Data System (ADS)

Rini, W. D. E.; Harisudin, M.; Supriyadi; Rahayu, E. S.

2018-03-01

Gunungkidul is one of the regencies at Yogyakarta, Indonesia which is 90% occupied by dry land, and thus vulnerable to climate change impact. Since dryland relies on water only from rain to meet crop water requirement, part of land management is rainfed. This condition encourages farmers to make the right decision regarding their additional income to meet household needs. Under the limited land resources, farmers decided to plant upland rice once or twice a year. The aim of the study is to analyze the interrelationship of households economics activities of upland rice farmers in rain-fed farming based on production, labor allocation, and consumption. The research method is descriptive analysis, with research site Ponjong sub-district, determined by the purposive method. Sampling method using proportional random sampling. Economics model was determined by using simultaneous equation model, with 2 SLS estimation method. The results showed that the household economics model of upland rice farmers in the rainfed land can be explained by using farmers household model and there is a linkage between production, labor allocation, and consumption.

Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

PubMed

Woodward, S J

2001-09-01

The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.

Landscape structure and management alter the outcome of a pesticide ERA: Evaluating impacts of endocrine disruption using the ALMaSS European Brown Hare model.

PubMed

Topping, Chris J; Dalby, Lars; Skov, Flemming

2016-01-15

There is a gradual change towards explicitly considering landscapes in regulatory risk assessment. To realise the objective of developing representative scenarios for risk assessment it is necessary to know how detailed a landscape representation is needed to generate a realistic risk assessment, and indeed how to generate such landscapes. This paper evaluates the contribution of landscape and farming components to a model based risk assessment of a fictitious endocrine disruptor on hares. In addition, we present methods and code examples for generation of landscape structures and farming simulation from data collected primarily for EU agricultural subsidy support and GIS map data. Ten different Danish landscapes were generated and the ERA carried out for each landscape using two different assumed toxicities. The results showed negative impacts in all cases, but the extent and form in terms of impacts on abundance or occupancy differed greatly between landscapes. A meta-model was created, predicting impact from landscape and farming characteristics. Scenarios based on all combinations of farming and landscape for five landscapes representing extreme and middle impacts were created. The meta-models developed from the 10 real landscapes failed to predict impacts for these 25 scenarios. Landscape, farming, and the emergent density of hares all influenced the results of the risk assessment considerably. The study indicates that prediction of a reasonable worst case scenario is difficult from structural, farming or population metrics; rather the emergent properties generated from interactions between landscape, management and ecology are needed. Meta-modelling may also fail to predict impacts, even when restricting inputs to combinations of those used to create the model. Future ERA may therefore need to make use of multiple scenarios representing a wide range of conditions to avoid locally unacceptable risks. This approach could now be feasible Europe wide given the landscape generation methods presented.

Modeling the Transmission of Piscirickettsia salmonis in Farmed Salmon

NASA Astrophysics Data System (ADS)

Cisternas, Jaime; Moreno, Adolfo

2007-05-01

Farming Atlantic salmon is an economic activity of growing relevance in the southern regions of Chile. The need to increase efficiency and reach production goals, as well as restrictions on the use of water resources, had led in recent years to certain practices that proved prone to bacterial infections among the fish. Our study focuses on the impact of rickettsial bacteria in farmed salmon, and the possibility of controlling its incidence once it is established along the salmon life cicle. We used compartmental models to separate fish in their maturation stages and health status. The mathematical analysis will involve differential equations with and without delays, and linear stability principles. Our goal was to build a simple model that explains the basic mechanisms at work and provides predictions on the outcome of different control strategies.

AGRO-2014: A time dependent model for assessing the fate and food-web bioaccumulation of organic pesticides in farm ponds: Model testing and performance analysis.

PubMed

Gobas, Frank A P C; Lai, Hao-Feng; Mackay, Donald; Padilla, Lauren E; Goetz, Andy; Jackson, Scott H

2018-10-15

A time-dependent environmental fate and food-web bioaccumulation model is developed to improve the evaluation of the behaviour of non-ionic hydrophobic organic pesticides in farm ponds. The performance of the model was tested by simulating the behaviour of 3 hydrophobic organic pesticides, i.e., metaflumizone (CAS Number: 139968-49-3), kresoxim-methyl (CAS Number: 144167-04-4) and pyraclostrobin (CAS Number: 175013-18-0), in microcosm studies and a Bluegill bioconcentration study for metaflumizone. In general, model-calculated concentrations of the pesticides were in reasonable agreement with the observed concentrations. Also, calculated bioaccumulation metrics were in good agreement with observed values. The model's application to simulate concentrations of organic pesticides in water, sediment and biota of farm ponds after episodic pesticide applications is illustrated. It is further shown that the time dependent model has substantially better accuracy in simulating the concentrations of pesticides in farm ponds resulting from episodic pesticide application than corresponding steady-state models. The time dependent model is particularly useful in describing the behaviour of highly hydrophobic pesticides that have a potential to biomagnify in aquatic food-webs. Copyright © 2018 Elsevier B.V. All rights reserved.

Leininger's model for discoveries at The Farm and midwifery services to the Amish.

PubMed

Finn, J

1995-01-01

This paper is a descriptive report and analysis of a transcultural nurse's experiences immersed in a hippie subculture at The Farm near Summertown, Tennessee. This subcultural group initially was established over 20 years ago as a community with a unique worldview which included pacifistic, vegetarian, and collective values and beliefs. This community prefers health care provided by their own community members who serve as generic care providers and also as folk midwives for home births. Leininger's (1991) Theory of Culture Care Diversity and Universality and her Sunrise Model provided the framework for discovering and understanding this unique subcultural group. The major components of Leininger's Sunrise Model including worldview, cultural values, and lifeways were used in the analysis. The important social structure factors discovered included environmental context, technological factors, religious and philosophical factors, political and legal factors, economic factors, and educational factors. The Farm community's culture care expressions, patterns and practices for health and well being were discovered including generic and folk systems of care. The farm midwives provide primary care and home birthing care to a nearby Old Order Amish community. The Amish culture and health care seeking patterns are discussed including their selective use of generic, folk, and professional care systems. The discoveries that resulted from the application of Leininger's Sunrise Model are presented including implications for transcultural nurse caregiving.

Impact of a diversion of sewage effluent on a seaweed farm in the Seto Inland Sea, Japan

NASA Astrophysics Data System (ADS)

Zhang, X.; Uchiyama, Y.; Suzue, Y.

2016-12-01

The Seto Inland Sea (SIS), Japan, is a partially stratified, tidally driven estuary, comprising several semi-enclosed basins with complex coastlines and thousands of islands as well as substantial influences from the Kuroshio. Even though water pollution has been improved adequately because of related policies enacted, Osaka Bay (OB), a part of SIS, still suffers mostly due to sewage effluent resulted from the densely populated hinterland. Tarumi Sewage Treatment Plant (TSTP) is one of the largest wastewater treatment plants in OB, located near Akashi Strait (AS) where energetic and complex tidal flow occurs. The surrounding area is famous for a seaweed farming industry, while the local fishermen keep claiming possible impacts of TSTP effluent on a farm. Thus a new outfall was constructed away from the farm as a remedy, although its effect has not been extensively investigated yet. Therefore, a numerical modeling is required to assess the present situation and to further utilize it for improvement of the outfall design. In the present study, we develop a quadruple-nested high-resolution ocean model based on ROMS. The sewage effluent capability is implemented into the innermost ROMS-L4 model with horizontal grid spacing of 20 m as an additional Eulerian passive tracer model based on Uchiyama et al. (2014). Non-dimensional concentration of sewage effluent is applied at the locations of the two existing outfalls as a bottom-released freshwater plume at a constant volume rate of 180,000 m3/day. The normal sewage discharge results in eastward transport with frequent intrusions into the seaweed farm to the east of TSTP. The diversion discharge from the new outfall evidently alters salinity and tracer concentration in the farm owing to counter-clockwise residual circulation formed near AS that promotes southward (offshore) transport. The eastward effluent transport is reduced significantly by about 50 % on and around the eastern shore including the farm.

Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model.

PubMed

Yuan, Chengcheng; Liu, Liming; Qi, Xiaoxing; Fu, Yonghu; Ye, Jinwei

2017-07-01

Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., "sharply increasing" (SI), "no-increase" (NI), "adjusted-method" (AM), and "trend" (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from -20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

PubMed

Fenlon, Caroline; O'Grady, Luke; Butler, Stephen; Doherty, Michael L; Dunnion, John

2017-01-01

Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants

PubMed Central

McEwan, Gregor F.; Groner, Maya L.; Fast, Mark D.; Revie, Crawford W.

2015-01-01

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments. PMID:26485023

Farm Work-Related Injuries and Risk Factors in South Korean Agriculture.

PubMed

Kim, Hyocher; Räsänen, Kimmo; Chae, Hyeseon; Kim, Kyungsu; Kim, Kyungran; Lee, Kyungsuk

2016-01-01

Agriculture is known to be a risk-filled industry in South Korea, as it is worldwide. The aims of this study were to identify the magnitude of farm work-related injuries and evaluate the association between injury and possible risk factors. Farmers, including farm members (N = 16,160), were surveyed. After excluding 7 subjects with missing data in questions about injury, 16,153 farmer responses were used for the analysis. Of the 16,153 farmers, 3.6% answered having at least one farm work-related injury requiring outpatient treatment or hospitalization during 2012. The proportion of injured men (4.3%) was 1.5 times higher than women (2.9%). From an age perspective, the proportion was 1.3% of those aged 49 or below, 2.7% of those aged 50-59, 4.2% of those aged 60-69, 4.2% of those aged 70-79, and 3.1% of those aged 80 or above. We used a multivariate logistic regression analysis with a stepwise model (forward) for risk factors (gender, age, farm ownership, farm type, work years in agriculture, work months during 2012, night work experience, and work experience under the influence of alcohol). The increased risk of farm work-related injuries significantly remained associated with age, farm ownership, and experience of night work. Further studies should be conducted to consistently identify injury characteristics, especially for old farmers, considering the crop cultivation in Asian countries.

A Case-Control Study to Identify Risk Factors Associated with Avian Influenza Subtype H9N2 on Commercial Poultry Farms in Pakistan

PubMed Central

Chaudhry, Mamoona; Rashid, Hamad B.; Thrusfield, Michael; Welburn, Sue; Bronsvoort, Barend MdeC.

2015-01-01

A 1:1 matched case-control study was conducted to identify risk factors for avian influenza subtype H9N2 infection on commercial poultry farms in 16 districts of Punjab, and 1 administrative unit of Pakistan. One hundred and thirty-three laboratory confirmed positive case farms were matched on the date of sample submission with 133 negative control farms. The association between a series of farm-level characteristics and the presence or absence of H9N2 was assessed by univariable analysis. Characteristics associated with H9N2 risk that passed the initial screening were included in a multivariable conditional logistic regression model. Manual and automated approaches were used, which produced similar models. Key risk factors from all approaches included selling of eggs/birds directly to live bird retail stalls, being near case/infected farms, a previous history of infectious bursal disease (IBD) on the farm and having cover on the water storage tanks. The findings of current study are in line with results of many other studies conducted in various countries to identify similar risk factors for AI subtype H9N2 infection. Enhancing protective measures and controlling risks identified in this study could reduce spread of AI subtype H9N2 and other AI viruses between poultry farms in Pakistan. PMID:25774768

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

NASA Astrophysics Data System (ADS)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

Development of an active risk-based surveillance strategy for avian influenza in Cuba.

PubMed

Ferrer, E; Alfonso, P; Ippoliti, C; Abeledo, M; Calistri, P; Blanco, P; Conte, A; Sánchez, B; Fonseca, O; Percedo, M; Pérez, A; Fernández, O; Giovannini, A

2014-09-01

The authors designed a risk-based approach to the selection of poultry flocks to be sampled in order to further improve the sensitivity of avian influenza (AI) active surveillance programme in Cuba. The study focused on the western region of Cuba, which harbours nearly 70% of national poultry holdings and comprise several wetlands where migratory waterfowl settle (migratory waterfowl settlements - MWS). The model took into account the potential risk of commercial poultry farms in western Cuba contracting from migratory waterfowl of the orders Anseriformes and Charadriiformes through dispersion for pasturing of migratory birds around the MWS. We computed spatial risk index by geographical analysis with Python scripts in ESRI(®) ArcGIS 10 on data projected in the reference system NAD 1927-UTM17. Farms located closer to MWS had the highest values for the risk indicator pj and in total 31 farms were chosen for targeted surveillance during the risk period. The authors proposed to start active surveillance in the study area 3 weeks after the onset of Anseriformes migration, with additional sampling repeated twice in the same selected poultry farms at 15 days interval (Comin et al., 2012; EFSA, 2008) to cover the whole migration season. In this way, the antibody detectability would be favoured in case of either a posterior AI introduction or enhancement of a previous seroprevalence under the sensitivity level. The model identified the areas with higher risk for AIV introduction from MW, aiming at selecting poultry premises for the application of risk-based surveillance. Given the infrequency of HPAI introduction into domestic poultry populations and the relative paucity of occurrences of LPAI epidemics, the evaluation of the effectiveness of this approach would require its application for several migration seasons to allow the collection of sufficient reliable data. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Tree-based modeling of complex interactions of phosphorus loadings and environmental factors.

PubMed

Grunwald, S; Daroub, S H; Lang, T A; Diaz, O A

2009-06-01

Phosphorus (P) enrichment has been observed in the historic oligotrophic Greater Everglades in Florida mainly due to P influx from upstream, agriculturally dominated, low relief drainage basins of the Everglades Agricultural Area (EAA). Our specific objectives were to: (1) investigate relationships between various environmental factors and P loads in 10 farm basins within the EAA, (2) identify those environmental factors that impart major effects on P loads using three different tree-based modeling approaches, and (3) evaluate predictive models to assess P loads. We assembled thirteen environmental variable sets for all 10 sub-basins characterizing water level management, cropping practices, soils, hydrology, and farm-specific properties. Drainage flow and P concentrations were measured at each sub-basin outlet from 1992-2002 and aggregated to derive monthly P loads. We used three different tree-based models including single regression trees (ST), committee trees in Bagging (CTb) and ARCing (CTa) modes and ten-fold cross-validation to test prediction performances. The monthly P loads (MPL) during the monitoring period showed a maximum of 2528 kg (mean: 103 kg) and maximum monthly unit area P loads (UAL) of 4.88 kg P ha(-1) (mean: 0.16 kg P ha(-1)). Our results suggest that hydrologic/water management properties are the major controlling variables to predict MPL and UAL in the EAA. Tree-based modeling was successful in identifying relationships between P loads and environmental predictor variables on 10 farms in the EAA indicated by high R(2) (>0.80) and low prediction errors. Committee trees in ARCing mode generated the best performing models to predict P loads and P loads per unit area. Tree-based models had the ability to analyze complex, non-linear relationships between P loads and multiple variables describing hydrologic/water management, cropping practices, soil and farm-specific properties within the EAA.

Effect of wind turbine generator model and siting on wind power changes out of large WECS arrays

NASA Technical Reports Server (NTRS)

Schleuter, R. A.; Park, G. L.; Lotfalian, M.; Dorsey, J.; Shayanfar, H.

1981-01-01

Methods of reducing the WECS generation change through selection of the wind turbine model for each site, selection of an appropriate siting configuration, and wind array controls are discussed. An analysis of wind generation change from an echelon and a farm for passage of a thunderstorm is presented. Reduction of the wind generation change over ten minutes is shown to reduce the increase in spinning reserve, unloadable generation and load following requirements on unit commitment when significant WECS generation is present and the farm penetration constraint is satisfied. Controls on the blade pitch angle of all wind turbines in an array or a battery control are shown to reduce both the wind generation change out of an array and the effective farm penetration in anticipation of a storm so that the farm penetration constraint may be satisfied.

Simulation of a 7.7 MW onshore wind farm with the Actuator Line Model

NASA Astrophysics Data System (ADS)

Guggeri, A.; Draper, M.; Usera, G.

2017-05-01

Recently, the Actuator Line Model (ALM) has been evaluated with coarser resolution and larger time steps than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition. The aim of the present paper is to continue these studies, assessing the capability of the ALM to represent the wind turbines’ interactions in an onshore wind farm. The ‘Libertad’ wind farm, which consists of four 1.9MW Vestas V100 wind turbines, was simulated considering different wind directions, and the results were compared with the wind farm SCADA data, finding good agreement between them. A sensitivity analysis was performed to evaluate the influence of the spatial resolution, finding acceptable agreement, although some differences were found. It is believed that these differences are due to the characteristics of the different Atmospheric Boundary Layer (ABL) simulations taken as inflow condition (precursor simulations).

Gis-Based Wind Farm Site Selection Model Offshore Abu Dhabi Emirate, Uae

NASA Astrophysics Data System (ADS)

Saleous, N.; Issa, S.; Mazrouei, J. Al

2016-06-01

The United Arab Emirates (UAE) government has declared the increased use of alternative energy a strategic goal and has invested in identifying and developing various sources of such energy. This study aimed at assessing the viability of establishing wind farms offshore the Emirate of Abu Dhabi, UAE and to identify favourable sites for such farms using Geographic Information Systems (GIS) procedures and algorithms. Based on previous studies and on local requirements, a set of suitability criteria was developed including ocean currents, reserved areas, seabed topography, and wind speed. GIS layers were created and a weighted overlay GIS model based on the above mentioned criteria was built to identify suitable sites for hosting a new offshore wind energy farm. Results showed that most of Abu Dhabi offshore areas were unsuitable, largely due to the presence of restricted zones (marine protected areas, oil extraction platforms and oil pipelines in particular). However, some suitable sites could be identified, especially around Delma Island and North of Jabal Barakah in the Western Region. The environmental impact of potential wind farm locations and associated cables on the marine ecology was examined to ensure minimal disturbance to marine life. Further research is needed to specify wind mills characteristics that suit the study area especially with the presence of heavy traffic due to many oil production and shipping activities in the Arabian Gulf most of the year.

Eurogrid: a new glideinWMS based portal for CDF data analysis

NASA Astrophysics Data System (ADS)

Amerio, S.; Benjamin, D.; Dost, J.; Compostella, G.; Lucchesi, D.; Sfiligoi, I.

2012-12-01

The CDF experiment at Fermilab ended its Run-II phase on September 2011 after 11 years of operations and 10 fb-1 of collected data. CDF computing model is based on a Central Analysis Farm (CAF) consisting of local computing and storage resources, supported by OSG and LCG resources accessed through dedicated portals. At the beginning of 2011 a new portal, Eurogrid, has been developed to effectively exploit computing and disk resources in Europe: a dedicated farm and storage area at the TIER-1 CNAF computing center in Italy, and additional LCG computing resources at different TIER-2 sites in Italy, Spain, Germany and France, are accessed through a common interface. The goal of this project is to develop a portal easy to integrate in the existing CDF computing model, completely transparent to the user and requiring a minimum amount of maintenance support by the CDF collaboration. In this paper we will review the implementation of this new portal, and its performance in the first months of usage. Eurogrid is based on the glideinWMS software, a glidein based Workload Management System (WMS) that works on top of Condor. As CDF CAF is based on Condor, the choice of the glideinWMS software was natural and the implementation seamless. Thanks to the pilot jobs, user-specific requirements and site resources are matched in a very efficient way, completely transparent to the users. Official since June 2011, Eurogrid effectively complements and supports CDF computing resources offering an optimal solution for the future in terms of required manpower for administration, support and development.

A rapid method for assessing the environmental performance of commercial farms in the Pampas of Argentina.

PubMed

Viglizzo, E F; Frank, F; Bernardos, J; Buschiazzo, D E; Cabo, S

2006-06-01

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.

Farm to Work: Development of a Modified Community-Supported Agriculture Model at Worksites, 2007-2012.

PubMed

Thi, Christina A; Horton, Karissa D; Loyo, Jennifer; Jowers, Esbelle M; Rodgers, Lindsay Faith; Smiley, Andrew W; Leversen, Eric; Hoelscher, Deanna M

2015-10-22

The Farm to Work program is a modified community-supported agriculture model at worksites in Texas. The objective of the Farm to Work program is to increase fruit and vegetable intake among employees and their households by decreasing cost, improving convenience, and increasing access while also creating a new market for local farmers at worksites. The objectives of this article were to describe the development, implementation, and outcome of a 5-year participation trend analysis and to describe the community relationships that were formed to enable the successful implementation of the program. The Farm to Work program began in November 2007 as a collaborative effort between the nonprofit Sustainable Food Center, the Texas Department of State Health Services, the Web development company WebChronic Consulting LLC, and Naegelin Farm. The program provides a weekly or biweekly opportunity for employees to order a basket of produce online to be delivered to the worksite by a local farmer. A 5-year participation trend analysis, including seasonal variation and sales trends, was conducted using sales data from November 2007 through December 2012. The total number of baskets delivered from November 2007 through December 2012 was 38,343; of these, 37,466 were sold and 877 were complimentary. The total value of sold and complimentary baskets was $851,035 and $21,925, respectively. Participation in the program increased over time and was highest in 2012. The Farm to Work program increased access to locally grown fruits and vegetables for employees and created a new market for farmers. Increased program participation indicates that Farm to Work can increase employees' fruit and vegetable consumption and thus help prevent chronic diseases in this population.

Investment appraisal of technology innovations on dairy farm electricity consumption.

PubMed

Upton, J; Murphy, M; De Boer, I J M; Groot Koerkamp, P W G; Berentsen, P B M; Shalloo, L

2015-02-01

The aim of this study was to conduct an investment appraisal for milk-cooling, water-heating, and milk-harvesting technologies on a range of farm sizes in 2 different electricity-pricing environments. This was achieved by using a model for electricity consumption on dairy farms. The model simulated the effect of 6 technology investment scenarios on the electricity consumption and electricity costs of the 3 largest electricity-consuming systems within the dairy farm (i.e., milk-cooling, water-heating, and milking machine systems). The technology investment scenarios were direct expansion milk-cooling, ice bank milk-cooling, milk precooling, solar water-heating, and variable speed drive vacuum pump-milking systems. A dairy farm profitability calculator was combined with the electricity consumption model to assess the effect of each investment scenario on the total discounted net income over a 10-yr period subsequent to the investment taking place. Included in the calculation were the initial investments, which were depreciated to zero over the 10-yr period. The return on additional investment for 5 investment scenarios compared with a base scenario was computed as the investment appraisal metric. The results of this study showed that the highest return on investment figures were realized by using a direct expansion milk-cooling system with precooling of milk to 15°C with water before milk entry to the storage tank, heating water with an electrical water-heating system, and using standard vacuum pump control on the milking system. Return on investment figures did not exceed the suggested hurdle rate of 10% for any of the ice bank scenarios, making the ice bank system reliant on a grant aid framework to reduce the initial capital investment and improve the return on investment. The solar water-heating and variable speed drive vacuum pump scenarios failed to produce positive return on investment figures on any of the 3 farm sizes considered on either the day and night tariff or the flat tariff, even when the technology costs were reduced by 40% in a sensitivity analysis of technology costs. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessing Local Knowledge Use in Agroforestry Management with Cognitive Maps

NASA Astrophysics Data System (ADS)

Isaac, Marney E.; Dawoe, Evans; Sieciechowicz, Krystyna

2009-06-01

Small-holder farmers often develop adaptable agroforestry management techniques to improve and diversify crop production. In the cocoa growing region of Ghana, local knowledge on such farm management holds a noteworthy role in the overall farm development. The documentation and analysis of such knowledge use in cocoa agroforests may afford an applicable framework to determine mechanisms driving farmer preference and indicators in farm management. This study employed 12 in-depth farmer interviews regarding variables in farm management as a unit of analysis and utilized cognitive mapping as a qualitative method of analysis. Our objectives were (1) to illustrate and describe agroforestry management variables and associated farm practices, (2) to determine the scope of decision making of individual farmers, and (3) to investigate the suitability of cognitive mapping as a tool for assessing local knowledge use. Results from the cognitive maps revealed an average of 16 ± 3 variables and 19 ± 3 links between management variables in the farmer cognitive maps. Farmer use of advantageous ecological processes was highly central to farm management (48% of all variables), particularly manipulation of organic matter, shade and food crop establishment, and maintenance of a tree stratum as the most common, highly linked variables. Over 85% of variables included bidirectional arrows, interpreted as farm management practices dominated by controllable factors, insofar as farmers indicated an ability to alter most farm characteristics. Local knowledge use on cocoa production revealed detailed indicators for site evaluation, thus affecting farm preparation and management. Our findings suggest that amid multisourced information under conditions of uncertainty, strategies for adaptable agroforestry management should integrate existing and localized management frameworks and that cognitive mapping provides a tool-based approach to advance such a management support system.

Assessing local knowledge use in agroforestry management with cognitive maps.

PubMed

Isaac, Marney E; Dawoe, Evans; Sieciechowicz, Krystyna

2009-06-01

Small-holder farmers often develop adaptable agroforestry management techniques to improve and diversify crop production. In the cocoa growing region of Ghana, local knowledge on such farm management holds a noteworthy role in the overall farm development. The documentation and analysis of such knowledge use in cocoa agroforests may afford an applicable framework to determine mechanisms driving farmer preference and indicators in farm management. This study employed 12 in-depth farmer interviews regarding variables in farm management as a unit of analysis and utilized cognitive mapping as a qualitative method of analysis. Our objectives were (1) to illustrate and describe agroforestry management variables and associated farm practices, (2) to determine the scope of decision making of individual farmers, and (3) to investigate the suitability of cognitive mapping as a tool for assessing local knowledge use. Results from the cognitive maps revealed an average of 16 +/- 3 variables and 19 +/- 3 links between management variables in the farmer cognitive maps. Farmer use of advantageous ecological processes was highly central to farm management (48% of all variables), particularly manipulation of organic matter, shade and food crop establishment, and maintenance of a tree stratum as the most common, highly linked variables. Over 85% of variables included bidirectional arrows, interpreted as farm management practices dominated by controllable factors, insofar as farmers indicated an ability to alter most farm characteristics. Local knowledge use on cocoa production revealed detailed indicators for site evaluation, thus affecting farm preparation and management. Our findings suggest that amid multisourced information under conditions of uncertainty, strategies for adaptable agroforestry management should integrate existing and localized management frameworks and that cognitive mapping provides a tool-based approach to advance such a management support system.

Assessment and quantification of post-weaning multi-systemic wasting syndrome severity at farm level.

PubMed

Alarcon, Pablo; Velasova, Martina; Werling, Dirk; Stärk, Katharina D C; Chang, Yu-Mei; Nevel, Amanda; Pfeiffer, Dirk U; Wieland, Barbara

2011-01-01

Post-weaning multi-systemic wasting syndrome (PMWS) causes major economic losses for the English pig industry and severity of clinical signs and economic impact vary considerably between affected farms. We present here a novel approach to quantify severity of PMWS based on morbidity and mortality data and presence of porcine circovirus type 2 (PCV2). In 2008-2009, 147 pig farms across England, non-vaccinating for PCV2, were enrolled in a cross-sectional study. Factor analysis was used to generate variables representing biologically meaningful aspects of variation among qualitative and quantitative morbidity variables. Together with other known variables linked to PMWS, the resulting factors were included in a principal component analysis (PCA) to derive an algorithm for PMWS severity. Factor analysis resulted in two factors: Morbidity Factor 1 (MF1) representing mainly weaner and grower morbidity, and Morbidity Factor 2 (MF2) which mainly reflects variation in finisher morbidity. This indicates that farms either had high morbidity mainly in weaners/growers or mainly in finishers. Subsequent PCA resulted in the extraction of one component representing variation in MF1, post-weaning mortality and percentage of PCV2 PCR positive animals. Component scores were normalised to a value range from 0 to 10 and farms classified into: non or slightly affected farms with a score <4, moderately affected farms with scores 4-6.5 and highly affected farms with a score >6.5. The identified farm level PMWS severities will be used to identify risk factors related to these, to assess the efficacy of PCV2 vaccination and investigating the economic impact of potential control measures. Copyright © 2010 Elsevier B.V. All rights reserved.

A participative approach to develop sustainability indicators for dehesa agroforestry farms.

PubMed

Escribano, M; Díaz-Caro, C; Mesias, F J

2018-05-29

This paper provides a list of specific indicators that will allow the managers of dehesa farms to assess their sustainability in an easy and reliable way. To this end a Delphi analysis has been carried out with a group of experts in agroforestry systems and sustainability. A total of 30 experts from public institutions, farming, research bodies, environmental and rural development associations, agricultural organizations and companies took part in the study which intended to design a set of sustainability indicators adapted to dehesa agroforestry systems. The experts scored 83 original indicators related to the basic pillars of sustainability (environmental, social and economic) through a two-round procedure. Finally, 24 indicators were selected based on their importance and the consensus achieved. From an environmental point of view, and in line with its significance for dehesa ecosystems, it has been observed that "Stocking rate" is the indicator with greater relevance. Within the economic pillar, "Farm profitability" is the most important indicator, while regarding the technical indicators "Percentage of animal diet based on grazing" is the one that got the highest score. Finally, the "Degree of job satisfaction" and the "Generational renewal" were the most relevant labor indicators. It is considered that the Delphi approach used in this research settles some of the flaws of other sustainability models, such as the adaptation to the system to be studied and the involvement of stakeholders in the design. Copyright © 2018 Elsevier B.V. All rights reserved.

Financial aspects of veterinary herd health management programmes.

PubMed

Ifende, V I; Derks, M; Hooijer, G A; Hogeveen, H

2014-09-06

Veterinary herd health management (VHHM) programmes have been shown to be economically effective in the past. However, no current information is available on costs and benefits of these programmes. This study compared economics and farm performance between participants and non-participants in VHHM programmes in 1013 dairy farms with over 40 cows. Milk Production Registration (MPR) data and a questionnaire concerning VHHM were used. Based on the level of participation in VHHM (as indicated in the questionnaire), costs of the programmes were calculated using a normative model. The economic value of the production effects was similarly calculated using normative modelling based on MPR data. Participants in VHHM had a better performance with regard to production, but not with regard to reproduction. Over 90 per cent of the VHHM participants were visited at least once every six weeks and most participants discussed at least three topics. In most farms, the veterinarian did the pregnancy checks as part of the VHHM programmes. There was a benefit to cost ratio of about five per cow per year for VHHM participants, and a mean difference in net returns of €30 per cow per year after adjusting for the cost of the programme. This portrays that participation in a VHHM programme is cost-efficient. There is, however, much unexplained variation in the net returns, possibly due to diverse approaches by veterinarians towards VHHM or by other factors not included in this analysis, like nutritional quality or management abilities of the farmer. British Veterinary Association.

A predictive control framework for optimal energy extraction of wind farms

NASA Astrophysics Data System (ADS)

Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

2016-09-01

This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

Valuing the visual impact of wind farms: A calculus method for synthesizing choice experiments studies.

PubMed

Wen, Cheng; Dallimer, Martin; Carver, Steve; Ziv, Guy

2018-05-06

Despite the great potential of mitigating carbon emission, development of wind farms is often opposed by local communities due to the visual impact on landscape. A growing number of studies have applied nonmarket valuation methods like Choice Experiments (CE) to value the visual impact by eliciting respondents' willingness to pay (WTP) or willingness to accept (WTA) for hypothetical wind farms through survey questions. Several meta-analyses have been found in the literature to synthesize results from different valuation studies, but they have various limitations related to the use of the prevailing multivariate meta-regression analysis. In this paper, we propose a new meta-analysis method to establish general functions for the relationships between the estimated WTP or WTA and three wind farm attributes, namely the distance to residential/coastal areas, the number of turbines and turbine height. This method involves establishing WTA or WTP functions for individual studies, fitting the average derivative functions and deriving the general integral functions of WTP or WTA against wind farm attributes. Results indicate that respondents in different studies consistently showed increasing WTP for moving wind farms to greater distances, which can be fitted by non-linear (natural logarithm) functions. However, divergent preferences for the number of turbines and turbine height were found in different studies. We argue that the new analysis method proposed in this paper is an alternative to the mainstream multivariate meta-regression analysis for synthesizing CE studies and the general integral functions of WTP or WTA against wind farm attributes are useful for future spatial modelling and benefit transfer studies. We also suggest that future multivariate meta-analyses should include non-linear components in the regression functions. Copyright © 2018. Published by Elsevier B.V.

Ecological Modernization and the US Farm Bill: The Case of the Conservation Security Program

ERIC Educational Resources Information Center

Lenihan, Martin H.; Brasier, Kathryn J.

2010-01-01

This paper examines the debate surrounding the inception of the Conservation Security Program (CSP) under the 2002 US Farm Bill as a possible expression of ecological modernization by examining the discursive contributions made by official actors, social movement organizations, and producer organizations. Based on this analysis, the CSP embodies…

Targeting Erosion Control: Adoption of Erosion Control Practices. A Report from a National Research Project.

ERIC Educational Resources Information Center

West, Peter; And Others

Research analyzed adoption of erosion control practices by farm operators in two counties in each of four states: Alabama, Missouri, Tennessee, and Washington. Analysis was based on farm survey data and technical and financial assistance information from county Soil Conservation Service (SCS) and Agricultural Stabilization and Conservation Service…

Optimizing wind farm layout via LES-calibrated geometric models inclusive of wind direction and atmospheric stability effects

NASA Astrophysics Data System (ADS)

Archer, Cristina; Ghaisas, Niranjan

2015-04-01

The energy generation at a wind farm is controlled primarily by the average wind speed at hub height. However, two other factors impact wind farm performance: 1) the layout of the wind turbines, in terms of spacing between turbines along and across the prevailing wind direction; staggering or aligning consecutive rows; angles between rows, columns, and prevailing wind direction); and 2) atmospheric stability, which is a measure of whether vertical motion is enhanced (unstable), suppressed (stable), or neither (neutral). Studying both factors and their complex interplay with Large-Eddy Simulation (LES) is a valid approach because it produces high-resolution, 3D, turbulent fields, such as wind velocity, temperature, and momentum and heat fluxes, and it properly accounts for the interactions between wind turbine blades and the surrounding atmospheric and near-surface properties. However, LES are computationally expensive and simulating all the possible combinations of wind directions, atmospheric stabilities, and turbine layouts to identify the optimal wind farm configuration is practically unfeasible today. A new, geometry-based method is proposed that is computationally inexpensive and that combines simple geometric quantities with a minimal number of LES simulations to identify the optimal wind turbine layout, taking into account not only the actual frequency distribution of wind directions (i.e., wind rose) at the site of interest, but also atmospheric stability. The geometry-based method is calibrated with LES of the Lillgrund wind farm conducted with the Software for Offshore/onshore Wind Farm Applications (SOWFA), based on the open-access OpenFOAM libraries. The geometric quantities that offer the best correlations (>0.93) with the LES results are the blockage ratio, defined as the fraction of the swept area of a wind turbine that is blocked by an upstream turbine, and the blockage distance, the weighted distance from a given turbine to all upstream turbines that can potentially block it. Based on blockage ratio and distance, an optimization procedure is proposed that explores many different layout variables and identifies, given actual wind direction and stability distributions, the optimal wind farm layout, i.e., the one with the highest wind energy production. The optimization procedure is applied to both the calibration wind farm (Lillgrund) and a test wind farm (Horns Rev) and a number of layouts more efficient than the existing ones are identified. The optimization procedure based on geometric models proposed here can be applied very quickly (within a few hours) to any proposed wind farm, once enough information on wind direction frequency and, if available, atmospheric stability frequency has been gathered and once the number of turbines and/or the areal extent of the wind farm have been identified.

A social-ecological analysis of ecosystem services supply and trade-offs in European wood-pastures.

PubMed

Torralba, Mario; Fagerholm, Nora; Hartel, Tibor; Moreno, Gerardo; Plieninger, Tobias

2018-05-01

Wood-pastures are complex social-ecological systems (SES), which are the product of long-term interaction between society and its surrounding landscape. Traditionally characterized by multifunctional low-intensity management that enhanced a wide range of ecosystem services (ES), current farm management has shifted toward more intensive farm models. This study assesses the supply of ES in four study areas dominated by managed wood-pastures in Spain, Sweden, and Romania. On the basis of 144 farm surveys and the use of multivariate techniques, we characterize farm management and structure in the study areas and identify the trade-offs in ES supply associated with this management. We link these trade-offs to multiple factors that characterize the landholding: economic, social, environmental, technological, and governance. Finally, we analyze how landholders' values and perspectives have an effect on management decisions. Results show a differentiated pattern of ES supply in the four study areas. We identified four types of trade-offs in ES supply that appear depending on what is being promoted by the farm management and that are associated with different dimensions of wood-pasture management: productivity-related trade-offs, crop production-related trade-offs, multifunctionality-related trade-offs, and farm accessibility-related trade-offs. These trade-offs are influenced by complex interactions between the properties of the SES, which have a direct influence on landholders' perspectives and motivations. The findings of this paper advance the understanding of the dynamics between agroecosystems and society and can inform system-based agricultural and conservation policies.

A social-ecological analysis of ecosystem services supply and trade-offs in European wood-pastures

PubMed Central

Hartel, Tibor

2018-01-01

Wood-pastures are complex social-ecological systems (SES), which are the product of long-term interaction between society and its surrounding landscape. Traditionally characterized by multifunctional low-intensity management that enhanced a wide range of ecosystem services (ES), current farm management has shifted toward more intensive farm models. This study assesses the supply of ES in four study areas dominated by managed wood-pastures in Spain, Sweden, and Romania. On the basis of 144 farm surveys and the use of multivariate techniques, we characterize farm management and structure in the study areas and identify the trade-offs in ES supply associated with this management. We link these trade-offs to multiple factors that characterize the landholding: economic, social, environmental, technological, and governance. Finally, we analyze how landholders’ values and perspectives have an effect on management decisions. Results show a differentiated pattern of ES supply in the four study areas. We identified four types of trade-offs in ES supply that appear depending on what is being promoted by the farm management and that are associated with different dimensions of wood-pasture management: productivity-related trade-offs, crop production–related trade-offs, multifunctionality-related trade-offs, and farm accessibility–related trade-offs. These trade-offs are influenced by complex interactions between the properties of the SES, which have a direct influence on landholders’ perspectives and motivations. The findings of this paper advance the understanding of the dynamics between agroecosystems and society and can inform system-based agricultural and conservation policies. PMID:29732404

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms

PubMed Central

Garza, Sarah J.; Miller, Ryan S.

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources. PMID:26571497

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

PubMed

Burdett, Christopher L; Kraus, Brian R; Garza, Sarah J; Miller, Ryan S; Bjork, Kathe E

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.

The farm apprentice: agricultural college students recollections of learning to farm "safely".

PubMed

Sanderson, L L; Dukeshire, S R; Rangel, C; Garbes, R

2010-10-01

A consistent message in the farm safety literature is the need to develop effective interventions to manage the unacceptably high rate of injury and death among farm children. To better understand the influence of childhood farm experiences on safety beliefs, attitudes, and practices, semi-structured interviews were conducted with 24 farm youth attending the Nova Scotia Agricultural College. The interviews were designed to elicit information pertaining to participants' earliest memories of involvement in farm activities, the decision-making processes that led them to assume work-related responsibilities, and the roles that their parents played in their safety training. A common theme of experiencing childhood as a "farm apprentice" emerged across all narratives whereby farm activities were learned primarily through observational learning and modeling of parents and then mastered through repetition. As "farm apprentices," the youths' involvement in dangerous activities such as tractor driving and livestock handling began at early ages, with very little formal training and supervision. Although participants clearly described themselves as being exposed to dangerous activities, they believed that they had the capacity to control the risks and farm safely. Based on our findings, the concept of the "farm apprentice" appears to be integral to the social context of the farming community and should be considered in the design of interventions to reduce child injury and death.

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

PubMed

Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

2017-05-01

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

The impact of escaped farmed Atlantic salmon (Salmo salar L.) on catch statistics in Scotland.

PubMed

Green, Darren M; Penman, David J; Migaud, Herve; Bron, James E; Taggart, John B; McAndrew, Brendan J

2012-01-01

In Scotland and elsewhere, there are concerns that escaped farmed Atlantic salmon (Salmo salar L.) may impact on wild salmon stocks. Potential detrimental effects could arise through disease spread, competition, or inter-breeding. We investigated whether there is evidence of a direct effect of recorded salmon escape events on wild stocks in Scotland using anglers' counts of caught salmon (classified as wild or farmed) and sea trout (Salmo trutta L.). This tests specifically whether documented escape events can be associated with reduced or elevated escapes detected in the catch over a five-year time window, after accounting for overall variation between areas and years. Alternate model frameworks were somewhat inconsistent, however no robust association was found between documented escape events and higher proportion of farm-origin salmon in anglers' catch, nor with overall catch size. A weak positive correlation was found between local escapes and subsequent sea trout catch. This is in the opposite direction to what would be expected if salmon escapes negatively affected wild fish numbers. Our approach specifically investigated documented escape events, contrasting with earlier studies examining potentially wider effects of salmon farming on wild catch size. This approach is more conservative, but alleviates some potential sources of confounding, which are always of concern in observational studies. Successful analysis of anglers' reports of escaped farmed salmon requires high data quality, particularly since reports of farmed salmon are a relatively rare event in the Scottish data. Therefore, as part of our analysis, we reviewed studies of potential sensitivity and specificity of determination of farmed origin. Specificity estimates are generally high in the literature, making an analysis of the form we have performed feasible.

The Impact of Escaped Farmed Atlantic Salmon (Salmo salar L.) on Catch Statistics in Scotland

PubMed Central

Green, Darren M.; Penman, David J.; Migaud, Herve; Bron, James E.; Taggart, John B.; McAndrew, Brendan J.

2012-01-01

In Scotland and elsewhere, there are concerns that escaped farmed Atlantic salmon (Salmo salar L.) may impact on wild salmon stocks. Potential detrimental effects could arise through disease spread, competition, or inter-breeding. We investigated whether there is evidence of a direct effect of recorded salmon escape events on wild stocks in Scotland using anglers' counts of caught salmon (classified as wild or farmed) and sea trout (Salmo trutta L.). This tests specifically whether documented escape events can be associated with reduced or elevated escapes detected in the catch over a five-year time window, after accounting for overall variation between areas and years. Alternate model frameworks were somewhat inconsistent, however no robust association was found between documented escape events and higher proportion of farm-origin salmon in anglers' catch, nor with overall catch size. A weak positive correlation was found between local escapes and subsequent sea trout catch. This is in the opposite direction to what would be expected if salmon escapes negatively affected wild fish numbers. Our approach specifically investigated documented escape events, contrasting with earlier studies examining potentially wider effects of salmon farming on wild catch size. This approach is more conservative, but alleviates some potential sources of confounding, which are always of concern in observational studies. Successful analysis of anglers' reports of escaped farmed salmon requires high data quality, particularly since reports of farmed salmon are a relatively rare event in the Scottish data. Therefore, as part of our analysis, we reviewed studies of potential sensitivity and specificity of determination of farmed origin. Specificity estimates are generally high in the literature, making an analysis of the form we have performed feasible. PMID:22970132

The economic efficiency of conservation measures for amphibians in organic farming--results from bio-economic modelling.

PubMed

Schuler, Johannes; Sattler, Claudia; Helmecke, Angela; Zander, Peter; Uthes, Sandra; Bachinger, Johann; Stein-Bachinger, Karin

2013-01-15

This paper presents a whole farm bio-economic modelling approach for the assessment and optimisation of amphibian conservation conditions applied at the example of a large scale organic farm in North-Eastern Germany. The assessment focuses mainly on the habitat quality as affected by conservation measures such as through specific adapted crop production activities (CPA) and in-field buffer strips for the European tree frog (Hyla arborea), considering also interrelations with other amphibian species (i.e. common spadefoot toad (Pelobates fuscus), fire-bellied toad (Bombina bombina)). The aim of the approach is to understand, analyse and optimize the relationships between the ecological and economic performance of an organic farming system, based on the expectation that amphibians are differently impacted by different CPAs. The modelling system consists of a set of different sub-models that generate a farm model on the basis of environmentally evaluated CPAs. A crop-rotation sub-model provides a set of agronomically sustainable crop rotations that ensures overall sufficient nitrogen supply and controls weed, pest and disease infestations. An economic sub-model calculates the gross margins for each possible CPA including costs of inputs such as labour and machinery. The conservation effects of the CPAs are assessed with an ecological sub-model evaluates the potential negative or positive effect that each work step of a CPA has on amphibians. A mathematical programming sub-model calculates the optimal farm organization taking into account the limited factors of the farm (e.g. labour, land) as well as ecological improvements. In sequential model runs, the habitat quality is to be improved by the model, while the highest possible gross margin is still to be achieved. The results indicate that the model can be used to show the scope of action that a farmer has to improve habitat quality by reducing damage to amphibian population on its land during agricultural activities. Thereby, depending on the level of habitat quality that is aimed at, different measures may provide the most efficient solution. Lower levels of conservation can be achieved with low-cost adapted CPAs, such as an increased cutting height, reduced sowing density and grubbing instead of ploughing. Higher levels of conservation require e.g. grassland-like managed buffer strips around ponds in sensible areas, which incur much higher on-farm conservation costs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks.

PubMed

Lee, Kyuyoung; Polson, Dale; Lowe, Erin; Main, Rodger; Holtkamp, Derald; Martínez-López, Beatriz

2017-03-01

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63-0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14-5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating GPFARM Crop Growth, Soil Water, and Soil Nitrogen Components for Colorado Dryland Locations

USDA-ARS?s Scientific Manuscript database

GPFARM is a farm/ranch decision support system (DSS) designed to assist in strategic management planning for land units from the field to the whole-farm level. This study evaluated the regional applicability and efficacy of GPFARM based on simulation model performance for dry mass grain yield, tota...

Data-Driven Risk Assessment from Small Scale Epidemics: Estimation and Model Choice for Spatio-Temporal Data with Application to a Classical Swine Fever Outbreak

PubMed Central

Gamado, Kokouvi; Marion, Glenn; Porphyre, Thibaud

2017-01-01

Livestock epidemics have the potential to give rise to significant economic, welfare, and social costs. Incursions of emerging and re-emerging pathogens may lead to small and repeated outbreaks. Analysis of the resulting data is statistically challenging but can inform disease preparedness reducing potential future losses. We present a framework for spatial risk assessment of disease incursions based on data from small localized historic outbreaks. We focus on between-farm spread of livestock pathogens and illustrate our methods by application to data on the small outbreak of Classical Swine Fever (CSF) that occurred in 2000 in East Anglia, UK. We apply models based on continuous time semi-Markov processes, using data-augmentation Markov Chain Monte Carlo techniques within a Bayesian framework to infer disease dynamics and detection from incompletely observed outbreaks. The spatial transmission kernel describing pathogen spread between farms, and the distribution of times between infection and detection, is estimated alongside unobserved exposure times. Our results demonstrate inference is reliable even for relatively small outbreaks when the data-generating model is known. However, associated risk assessments depend strongly on the form of the fitted transmission kernel. Therefore, for real applications, methods are needed to select the most appropriate model in light of the data. We assess standard Deviance Information Criteria (DIC) model selection tools and recently introduced latent residual methods of model assessment, in selecting the functional form of the spatial transmission kernel. These methods are applied to the CSF data, and tested in simulated scenarios which represent field data, but assume the data generation mechanism is known. Analysis of simulated scenarios shows that latent residual methods enable reliable selection of the transmission kernel even for small outbreaks whereas the DIC is less reliable. Moreover, compared with DIC, model choice based on latent residual assessment correlated better with predicted risk. PMID:28293559

The System Dynamics Model for Development of Organic Agriculture

NASA Astrophysics Data System (ADS)

Rozman, Črtomir; Škraba, Andrej; Kljajić, Miroljub; Pažek, Karmen; Bavec, Martina; Bavec, Franci

2008-10-01

Organic agriculture is the highest environmentally valuable agricultural system, and has strategic importance at national level that goes beyond the interests of agricultural sector. In this paper we address development of organic farming simulation model based on a system dynamics methodology (SD). The system incorporates relevant variables, which affect the development of the organic farming. The group decision support system (GDSS) was used in order to identify most relevant variables for construction of causal loop diagram and further model development. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long term dynamic context and will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level.

Wavelet analysis for wind fields estimation.

PubMed

Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.

The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling.

PubMed

Flood, Jessica S; Porphyre, Thibaud; Tildesley, Michael J; Woolhouse, Mark E J

2013-10-08

When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. Utilising point distances <1 km and <5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance <1 km missed a high proportion of map-based CPs; <5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.

Sustainability evaluation of different systems for sea cucumber ( Apostichopus japonicus) farming based on emergy theory

NASA Astrophysics Data System (ADS)

Wang, Guodong; Dong, Shuanglin; Tian, Xiangli; Gao, Qinfeng; Wang, Fang

2015-06-01

Emergy analysis is effective for analyzing ecological economic systems. However, the accuracy of the approach is affected by the diversity of economic level, meteorological and hydrological parameters in different regions. The present study evaluated the economic benefits, environmental impact, and sustainability of indoor, semi-intensive and extensive farming systems of sea cucumber ( Apostichopus japonicus) in the same region. The results showed that A. japonicus indoor farming system was high in input and output (yield) whereas pond extensive farming system was low in input and output. The output/input ratio of indoor farming system was lower than that of pond extensive farming system, and the output/input ratio of semi-intensive farming system fell in between them. The environmental loading ratio of A. japonicus extensive farming system was lower than that of indoor farming system. In addition, the emergy yield and emergy exchange ratios, and emergy sustainability and emergy indexes for sustainable development were higher in extensive farming system than those in indoor farming system. These results indicated that the current extensive farming system exerted fewer negative influences on the environment, made more efficient use of available resources, and met more sustainable development requirements than the indoor farming system. A. japonicus farming systems showed more emergy benefits than fish farming systems. The pond farming systems of A. japonicus exploited more free local environmental resources for production, caused less potential pressure on the local environment, and achieved higher sustainability than indoor farming system.

From population viability analysis to coviability of farmland biodiversity and agriculture.

PubMed

Mouysset, L; Doyen, L; Jiguet, F

2014-02-01

Substantial declines in farmland biodiversity have been reported in Europe for several decades. Agricultural changes have been identified as a main driver of these declines. Although different agrienvironmental schemes have been implemented, their positive effect on biodiversity is relatively unknown. This raises the question as to how to reconcile farming production and biodiversity conservation to operationalize a sustainable and multifunctional agriculture. We devised a bioeconomic model and conducted an analysis based on coviability of farmland biodiversity and agriculture. The coviability approach extended population viability analyses by including bioeconomic risk. Our model coupled stochastic dynamics of both biodiversity and farming land-uses selected at the microlevel with public policies at the macrolevel on the basis of financial incentives (taxes or subsidies) for land uses. The coviability approach made it possible for us to evaluate bioeconomic risks of these public incentives through the probability of satisfying a mix of biodiversity and economic constraints over time. We calibrated the model and applied it to a community of 34 common birds in metropolitan France at the small agricultural regions scale. We identified different public policies and scenarios with tolerable (0-0%) agroecological risk and modeled their outcomes up to 2050. Budgetary, economic, and ecological (based on Farmland Bird Index) constraints were essential to understanding the set of viable public policies. Our results suggest that some combinations of taxes on cereals and subsidies on grasslands could be relevant to develop a multifunctional agriculture. Moreover, the flexibility and multicriteria viewpoint underlying the coviability approach may help in the implementation of adaptive management. © 2013 Society for Conservation Biology.

The structure and strength of public attitudes towards wind farm development

NASA Astrophysics Data System (ADS)

Bidwell, David Charles

A growing social science literature seeks to understand why, despite broad public support for wind energy, proposals for specific projects are often met with strong local opposition. This gap between general and specific attitudes is viewed as a significant obstacle to the deployment of wind energy technologies. This dissertation applies theoretical perspectives and methodological tools from social psychology to provide insights on the structure and strength of attitudes towards the potential development of commercial wind farm in three coastal areas of Michigan. A survey of attitudes was completed by 375 residents in these communities and structural equation modeling was used to explore the relationship among variables. The analysis found that attitudes towards wind farm development are shaped by anticipated economic benefits to the community, but expectations of economic benefit are driven by personal values. Social psychology has long recognized that all attitudes are not created equal. Weak attitudes are fleeting and prone to change, while strong attitudes are stable over time and resistant to change. There are two fundamental paths to strong attitudes: repeated experience with an attitude object or the application of deeply held principles or values to that object. Structural equation models were also used to understand the strength of attitudes among the survey respondents. Both the anticipated effects of wind farm development and personal values were found to influence the strength of attitudes towards wind farms. However, while expectations that wind farm development will have positive effects on the economy bolster two measures of attitude strength (collective identity and importance), these expectations are associated with a decline in a third measure (confidence). A follow-up survey asking identical questions was completed by completed by 187 respondents to the initial survey. Linear regressions models were used to determine the effects of attitude strength on the stability of attitudes towards wind farms. In this study, attitude strength did not have a major effect on the stability of attitudes. Perceived importance of the issue of wind farm development did result in slightly more stable attitudes towards renewable energy. These survey results were compared to responses provided by 28 residents who completed surveys before and after participating in an informational session about commercial wind farm development. A regression analysis found that participation in an informational event changed the substance and quality of participants' attitudes. Attitudes towards wind farm development became more positive, and confidence in those attitudes grew stronger. These findings suggest that the gap between general attitudes towards wind energy and attitudes towards specific wind farm proposals could be narrowed by providing information and opportunities for discussion in communities with potential for commercial wind farm development. Future research is needed to track local attitudes and attitude strength throughout a proposal and development process.

Impact of water allocation strategies to manage groundwater resources in Western Australia: Equity and efficiency considerations

NASA Astrophysics Data System (ADS)

Iftekhar, Md Sayed; Fogarty, James

2017-05-01

In many parts of the world groundwater is being depleting at an alarming rate. Where groundwater extraction is licenced, regulators often respond to resource depletion by reducing all individual licences by a fixed proportion. This approach can be effective in achieving a reduction in the volume of water extracted, but the approach is not efficient. In water resource management the issue of the equity-efficiency trade-off has been explored in a number of contexts, but not in the context of allocation from a groundwater system. To contribute to this knowledge gap we conduct an empirical case study for Western Australia's most important groundwater system: the Gnangara Groundwater System (GGS). Resource depletion is a serious issue for the GGS, and substantial reductions in groundwater extraction are required to stabilise the system. Using an individual-based farm optimization model we study both the overall impact and the distributional impact of a fixed percentage water allocation cut to horticulture sector licence holders. The model is parameterised using water licence specific data on farm area and water allocation. The modelling shows that much of the impact of water allocation reductions can be mitigated through changing the cropping mix and the irrigation technology used. The modelling also shows that the scope for gains through the aggregation of holdings into larger farms is much greater than the potential losses due to water allocation reductions. The impact of water allocation cuts is also shown to impact large farms more than small farms. For example, the expected loss in net revenue per ha for a 10-ha farm is around three times the expected loss per ha for a 1-ha farm; and the expected loss per ha for a 25-ha farm is around five times the expected loss per ha for a 1-ha farm.

Evaluation of 'best practice' (SCOPS) guidelines for nematode control on commercial sheep farms in England and Wales.

PubMed

Learmount, Jane; Gettinby, George; Boughtflower, Valerie; Stephens, Nathalie; Hartley, Kayleigh; Allanson, Peter; Gutierrez, Alba Barrecheguren; Perez, David; Taylor, Mike

2015-01-30

Parasitic diseases are a major constraint to optimum livestock production and are the major cause of economic loss in UK sheep flocks, with farmers remaining dependant on anthelmintics for control. In the UK, research and evidence based, "best practice" guidelines for sustainable control of parasites in sheep (SCOPS) were first produced in 2004 and have been regularly updated since. This study was designed to evaluate the effect of these best practice guidelines for worm control on lamb production and infection levels, compared with more traditional management. Sixteen farms were selected based on a 2 cube factorial design with 3 factors known to affect worm epidemiology: control regimen; farm type; and climatic region. A formalised plan for worm control using 7 potential resistance-delaying practices was prepared for each of the 8 best practice (SCOPS) farms, in conjunction with the farms veterinarians. The 8 farms in the traditional management group (CONTROL farms) were selected based on ongoing evidence of them using worm control strategies deemed to be "higher-risk". A cohort of 40-50 study lambs at each farm was monitored from birth to finishing, allowing evaluation of lamb productivity, worm infection levels and for comparison of numbers of anthelmintic treatments. Birth and mid-season weights were used to calculate daily live-weight gain. Birth and finish dates were used to calculate time to finish and finish weights were also compared. Faecal egg counts, larval culture and species differentiation were undertaken throughout the year to assess the impact of the control strategies on worm burdens. There was no significant difference in results for any of the 3 production responses when comparing predicted means accounting for the differences in birth weight. In fact SCOPS farms had, on average, a higher daily weight gain and finish weight than CONTROL farms when comparing observed means. Statistical analysis of infection levels clearly showed no significant effect according to farm type (p=0.71) or treatment (p=0.81). In contrast the effect of region (p=0.08), although not significant, had a much larger effect size (standardised mean difference) with lower parasite burdens based on faecal egg counts on Northern farms compared to Southern farms. For both ewes and lambs, significantly fewer treatments were carried out on the SCOPS farms. The data collected from this study suggests that farms implementing SCOPS principles use less anthelmintic than other farms, without loss of animal performance or increased worm burden. Copyright © 2015. Published by Elsevier B.V.

Farm and management variables linked to fecal shedding of Campylobacter and Salmonella in commercial squab production.

PubMed

Jeffrey, J S; Atwill, E R; Hunter, A

2001-01-01

A cross-sectional study was performed to determine the relationship of farm variables and management practices to fecal shedding of Campylobacter or Salmonella on commercial squab (young pigeon) farms. A detailed survey provided information on biosecurity, cleaning and disinfection, bird health, vector control, and loft and pen. Twenty pigeons on each of 12 farms were cultured before and after the producers completed a voluntary quality assurance training program (QAP), based on principles of hazard analysis critical control point (HACCP). The prevalence of positive samples for Salmonella and C. jejuni was 1/480 (0.21%) and 19/480 (3.96%), respectively. Campylobacter was present on one farm during both visits; three farms during the first visit, and three farms during the second visit. Analysis by fixed-effects logistic regression showed the probability of having a positive C. jejuni culture was increased by not using dry manure in the nesting material, not cleaning shipping crates, cleaning landing boards, and by increased frequency of chemical disinfection of water. Having a positive parent and higher numbers of squab per pen (density) were also associated with higher odds of being positive for C. jejuni. Factors not associated with a positive C. jejuni culture included, other avian species on the farm, type of shipping crate, covered drinkers, fly problems, bird age, level of nest box within the loft, and QAP training. Prevalence of food safety pathogens was extremely low on the squab facilities tested as compared with reports from commercial broiler or turkey flocks. This observation suggests that one or more farm variables or management practices were effectively reducing infection, or possibly a species-related difference existed in carriage rates and shedding of pathogens. These results emphasize critical control points for food safety pathogens may vary widely, and the formulation of effective QAP programs are dependent on science-based knowledge of diverse animal production systems.

Assessing conservation opportunity on private land: socio-economic, behavioral, and spatial dimensions.

PubMed

Raymond, Christopher M; Brown, Gregory

2011-10-01

This study presents a method for assessing conservation opportunity on private land based on landholders' socio-economic, behavioral, and farm characteristics. These characteristics include age, gender, education, level of off-farm income, farm size, proportion of remnant native vegetation on-farm, and ecological value of native vegetation on-farm. A sample of landholders who own greater than 2 ha of land in the South Australian Murray-Darling Basin region were sent a mail-based survey about their values and preferences for environmental management (N = 659, 52% response). Cross-tabulations and ANOVA statistical analysis techniques were used to compare the socio-economic attributes across three landholder classes: disengaged, moderately engaged, and highly engaged in native vegetation planting. Results indicate that highly engaged landholders were more likely to be female, formally educated, hobby farmers who managed small parcels of land and have high off-farm incomes, whereas disengaged landholders held significantly stronger farming connections (more farming experience, family have lived on the farm for more generations). Spatial analysis revealed area-specific differences in conservation opportunity and conservation priority. In some areas, properties of high ecological value were managed by highly engaged landholders, but nearby properties of high value were managed by moderately engaged or disengaged landholders. Environmental managers therefore cannot assume areas of high conservation priority will be areas of high conservation opportunity. At the regional scale, the potential for revegetation seems most promising within the moderately engaged landholder group considering the vast amount of land managed by this group in areas of high ecological value, particularly within the less represented Mallee and Coorong and Rangelands sub-regions. We suggest that incentive schemes which purchase conservation need to be targeted at disengaged landholders; mentoring schemes led by commercial farmers highly engaged in native vegetation planting should be directed at moderately engaged landholders, and; awards programs which acknowledge conservation successes should be targeted at highly engaged landholders. Copyright © 2011 Elsevier Ltd. All rights reserved.

One-Water Hydrologic Flow Model (MODFLOW-OWHM)

USGS Publications Warehouse

Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas; Niswonger, Richard G.

2014-01-01

The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.” In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM). An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.

A Hierarchical Network Approach for Modeling Rift Valley Fever Epidemics with Applications in North America

PubMed Central

Xue, Ling; Cohnstaedt, Lee W.; Scott, H. Morgan; Scoglio, Caterina

2013-01-01

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread. PMID:23667453

A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America.

PubMed

Xue, Ling; Cohnstaedt, Lee W; Scott, H Morgan; Scoglio, Caterina

2013-01-01

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread.

Determinants associated with veterinary antimicrobial prescribing in farm animals in the Netherlands: a qualitative study.

PubMed

Speksnijder, D C; Jaarsma, A D C; van der Gugten, A C; Verheij, T J M; Wagenaar, J A

2015-04-01

Antimicrobial use in farm animals might contribute to the development of antimicrobial resistance in humans and animals, and there is an urgent need to reduce antimicrobial use in farm animals. Veterinarians are typically responsible for prescribing and overseeing antimicrobial use in animals. A thorough understanding of veterinarians' current prescribing practices and their reasons to prescribe antimicrobials might offer leads for interventions to reduce antimicrobial use in farm animals. This paper presents the results of a qualitative study of factors that influence prescribing behaviour of farm animal veterinarians. Semi-structured interviews with eleven farm animal veterinarians were conducted, which were taped, transcribed and iteratively analysed. This preliminary analysis was further discussed and refined in an expert meeting. A final conceptual model was derived from the analysis and sent to all the respondents for validation. Many conflicting interests are identifiable when it comes to antimicrobial prescribing by farm animal veterinarians. Belief in the professional obligation to alleviate animal suffering, financial dependency on clients, risk avoidance, shortcomings in advisory skills, financial barriers for structural veterinary herd health advisory services, lack of farmers' compliance to veterinary recommendations, public health interests, personal beliefs regarding the veterinary contribution to antimicrobial resistance and major economic powers are all influential determinants in antimicrobial prescribing behaviour of farm animal veterinarians. Interventions to change prescribing behaviour of farm animal veterinarians could address attitudes and advisory skills of veterinarians, as well as provide tools to deal with (perceived) pressure from farmers and advisors to prescribe antimicrobials. Additional (policy) measures could probably support farm animal veterinarians in acting as a more independent animal health consultant. © 2014 Blackwell Verlag GmbH.

Modeling velocity space-time correlations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2016-11-01

Turbulent fluctuations of wind velocities cause power-output fluctuations in wind farms. The statistics of velocity fluctuations can be described by velocity space-time correlations in the atmospheric boundary layer. In this context, it is important to derive simple physics-based models. The so-called Tennekes-Kraichnan random sweeping hypothesis states that small-scale velocity fluctuations are passively advected by large-scale velocity perturbations in a random fashion. In the present work, this hypothesis is used with an additional mean wind velocity to derive a model for the spatial and temporal decorrelation of velocities in wind farms. It turns out that in the framework of this model, space-time correlations are a convolution of the spatial correlation function with a temporal decorrelation kernel. In this presentation, first results on the comparison to large eddy simulations will be presented and the potential of the approach to characterize power output fluctuations of wind farms will be discussed. Acknowledgements: 'Fellowships for Young Energy Scientists' (YES!) of FOM, the US National Science Foundation Grant IIA 1243482, and support by the Max Planck Society.

Distinguishing ovarian maturity of farmed white sturgeon (Acipenser transmontanus) by Fourier transform infrared spectroscopy: a potential tool for caviar production management.

PubMed

Lu, Xiaonan; Webb, Molly; Talbott, Mariah; Van Eenennaam, Joel; Palumbo, Amanda; Linares-Casenave, Javier; Doroshov, Serge; Struffenegger, Peter; Rasco, Barbara

2010-04-14

Fourier transform infrared spectroscopy (FT-IR, 4000-400 cm(-1)) was applied to blood plasma of farmed white sturgeon (N = 40) to differentiate and predict the stages of ovarian maturity. Spectral features of sex steroids (approximately 3000 cm(-1)) and vitellogenin (approximately 1080 cm(-1)) were identified. Clear segregation of maturity stages (previtellogenesis, vitellogenesis, postvitellogenesis, and follicular atresia) was achieved using principal component analysis (PCA). Progression of oocyte development in the late phase of vitellogenesis was also monitored using PCA based on changes in plasma concentrations of sex steroid and lipid content. The observed oocyte polarization index (PI, a measure of nuclear migration) was correlated with changes in plasma sex steroid levels revealed by FT-IR PCA results. A partial least squares (PLS) model predicted PI values within the range 0.12-0.40 (R = 0.95, SEP = 2.18%) from differences in spectral features. These results suggest that FT-IR may be a good tool for assessing ovarian maturity in farmed sturgeon and will reduce the need for the invasive ovarian biopsy required for PI determination.

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt.

PubMed

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-11-09

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Numerical simulations of flow fields through conventionally controlled wind turbines & wind farms

NASA Astrophysics Data System (ADS)

Emre Yilmaz, Ali; Meyers, Johan

2014-06-01

In the current study, an Actuator-Line Model (ALM) is implemented in our in-house pseudo-spectral LES solver SP-WIND, including a turbine controller. Below rated wind speed, turbines are controlled by a standard-torque-controller aiming at maximum power extraction from the wind. Above rated wind speed, the extracted power is limited by a blade pitch controller which is based on a proportional-integral type control algorithm. This model is used to perform a series of single turbine and wind farm simulations using the NREL 5MW turbine. First of all, we focus on below-rated wind speed, and investigate the effect of the farm layout on the controller calibration curves. These calibration curves are expressed in terms of nondimensional torque and rotational speed, using the mean turbine-disk velocity as reference. We show that this normalization leads to calibration curves that are independent of wind speed, but the calibration curves do depend on the farm layout, in particular for tightly spaced farms. Compared to turbines in a lone-standing set-up, turbines in a farm experience a different wind distribution over the rotor due to the farm boundary-layer interaction. We demonstrate this for fully developed wind-farm boundary layers with aligned turbine arrangements at different spacings (5D, 7D, 9D). Further we also compare calibration curves obtained from full farm simulations with calibration curves that can be obtained at a much lower cost using a minimal flow unit.

A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot.

PubMed

Steensels, M; Antler, A; Bahr, C; Berckmans, D; Maltz, E; Halachmi, I

2016-09-01

Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian's diagnosis served as a binary reference for the model (healthy-sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.

Communicating Performance Assessments Results - 13609

DOE Office of Scientific and Technical Information (OSTI.GOV)

Layton, Mark

2013-07-01

The F-Area Tank Farms (FTF) and H-Area Tank Farm (HTF) are owned by the U.S. Department of Energy (DOE) and operated by Savannah River Remediation LLC (SRR), Liquid Waste Operations contractor at DOE's Savannah River Site (SRS). The FTF and HTF are active radioactive waste storage and treatment facilities consisting of 51 carbon steel waste tanks and ancillary equipment such as transfer lines, evaporators and pump tanks. Performance Assessments (PAs) for each Tank Farm have been prepared to support the eventual closure of the underground radioactive waste tanks and ancillary equipment. PAs provide the technical bases and results to bemore » used in subsequent documents to demonstrate compliance with the pertinent requirements for final closure of the Tank Farms. The Tank Farms are subject to a number of regulatory requirements. The State regulates Tank Farm operations through an industrial waste water permit and through a Federal Facility Agreement approved by the State, DOE and the Environmental Protection Agency (EPA). Closure documentation will include State-approved Tank Farm Closure Plans and tank-specific closure modules utilizing information from the PAs. For this reason, the State of South Carolina and the EPA must be involved in the performance assessment review process. The residual material remaining after tank cleaning is also subject to reclassification prior to closure via a waste determination pursuant to Section 3116 of the Ronald W. Reagan National Defense Authorization Act of Fiscal Year 2005. PAs are performance-based, risk-informed analyses of the fate and transport of FTF and HTF residual wastes following final closure of the Tank Farms. Since the PAs serve as the primary risk assessment tools in evaluating readiness for closure, it is vital that PA conclusions be communicated effectively. In the course of developing the FTF and HTF PAs, several lessons learned have emerged regarding communicating PA results. When communicating PA results it is important to stress that the primary goal of the PA results is to provide risk understanding, recognizing the magnitude of risk and identifying the conceptual model decisions and critical assumptions that most impact the results. Conceptual models that describe reality using simplified, mathematical approaches, and their roles in arriving at the PA results, must also be communicated. When presenting PA results, evaluations will typically be focused on a single baseline (or Base Case) to provide a foundation for discussion. The PA results are supplemented by other studies (alternate configurations, uncertainty analyses, and sensitivity analyses) which provide a breadth of modeling to supplement the Base Case. The suite of information offered by the various modeling cases and studies provides confidence that the overall risk is understood along with the underlying parameters and conditions that contribute to risk. (author)« less

A Customizable Dashboarding System for Watershed Model Interpretation

NASA Astrophysics Data System (ADS)

Easton, Z. M.; Collick, A.; Wagena, M. B.; Sommerlot, A.; Fuka, D.

2017-12-01

Stakeholders, including policymakers, agricultural water managers, and small farm managers, can benefit from the outputs of commonly run watershed models. However, the information that each stakeholder needs is be different. While policy makers are often interested in the broader effects that small farm management may have on a watershed during extreme events or over long periods, farmers are often interested in field specific effects at daily or seasonal period. To provide stakeholders with the ability to analyze and interpret data from large scale watershed models, we have developed a framework that can support custom exploration of the large datasets produced. For the volume of data produced by these models, SQL-based data queries are not efficient; thus, we employ a "Not Only SQL" (NO-SQL) query language, which allows data to scale in both quantity and query volumes. We demonstrate a stakeholder customizable Dashboarding system that allows stakeholders to create custom `dashboards' to summarize model output specific to their needs. Dashboarding is a dynamic and purpose-based visual interface needed to display one-to-many database linkages so that the information can be presented for a single time period or dynamically monitored over time and allows a user to quickly define focus areas of interest for their analysis. We utilize a single watershed model that is run four times daily with a combined set of climate projections, which are then indexed, and added to an ElasticSearch datastore. ElasticSearch is a NO-SQL search engine built on top of Apache Lucene, a free and open-source information retrieval software library. Aligned with the ElasticSearch project is the open source visualization and analysis system, Kibana, which we utilize for custom stakeholder dashboarding. The dashboards create a visualization of the stakeholder selected analysis and can be extended to recommend robust strategies to support decision-making.

Multi-Criteria Analysis for Solar Farm Location Suitability

NASA Astrophysics Data System (ADS)

Mierzwiak, Michal; Calka, Beata

2017-12-01

Currently the number of solar farms, as a type of renewable sources of energy, is growing rapidly. Photovoltaic power stations have many advantages, which is an incentive for their building and development. Solar energy is readily available and inexhaustible, and its production is environmentally friendly. In the present study multiple environmental and economic criteria were taken into account to select a potential photovoltaic farm location, with particular emphasis on: protected areas, land cover, solar radiation, slope angle, proximity to roads, built-up areas, and power lines. Advanced data analysis were used because of the multiplicity of criteria and their diverse influence on the choice of a potential location. They included the spatial analysis, the Weighted Linear Combination Technique (WLC), and the Analytic Hierarchy Process (AHP) as a decisionmaking method. The analysis was divided into two stages. In the first one, the areas where the location of solar farms was not possible were excluded. In the second one, the best locations meeting all environmental and economic criteria were selected. The research was conducted for the Legionowo District, using data from national surveying and mapping resources such as: BDOT10k (Database of Topographic Objects), NMT (Numerical Terrain Model), and lands and buildings register. Finally, several areas meeting the criteria were chosen. The research deals with solar farms with up to 40 kW power. The results of the study are presented as thematic maps. The advantage of the method is its versatility. It can be used not only for any area, but with little modification of the criteria, it can also be applied to choose a location for wind farms.

Forage-based dairying in a water-limited future: use of models to investigate farming system adaptation in southern Australia.

PubMed

Chapman, D F; Dassanayake, K; Hill, J O; Cullen, B R; Lane, N

2012-07-01

The irrigated dairy industry in southern Australia has experienced significant restrictions in irrigation water allocations since 2005, consistent with climate change impact predictions for the region. Simulation models of pasture growth (DairyMod), crop yield (Agricultural Production Systems Simulator, APSIM), and dairy system management and production (UDDER) were used in combination to investigate a range of forage options that may be capable of sustaining dairy business profitability under restricted water-allocation scenarios in northern Victoria, Australia. A total of 23 scenarios were simulated and compared with a base farm system (100% of historical water allocations, grazed perennial ryegrass pasture with supplements; estimated operating surplus $A2,615/ha at a milk price of $A4.14/kg of milk solids). Nine simulations explored the response of the base farm to changes in stocking rate or the implementation of a double cropping rotation on 30% of farm area, or both. Five simulations explored the extreme scenario of dairying without any irrigation water. Two general responses to water restrictions were investigated in a further 9 simulations. Annual ryegrass grazed pasture, complemented by a double cropping rotation (maize grown in summer for silage, followed by either brassica forage crop and annual ryegrass for silage in winter and spring) on 30% of farm area, led to an estimated operating surplus of $A1746/ha at the same stocking rate as the base farm when calving was moved to autumn (instead of late winter, as in the base system). Estimated total irrigation water use was 2.7ML/ha compared with 5.4ML/ha for the base system. Summer-dormant perennial grass plus double cropping (30% of farm area) lifted operating surplus by a further $A100/ha if associated with autumn calving (estimated total irrigation water use 3.1ML/ha). Large shifts in the forage base of dairy farms could sustain profitability in the face of lower, and fluctuating, water allocations. However, changes in other strategic management policies, notably calving date and stocking rate, would be required, and these systems would be more complex to manage. The adaptation scenarios that resulted in the highest estimated operating surplus were those where at least 10 t of pasture or crop DM was grazed directly by cows per hectare per year, resulting in grazed pasture intake of at least 2 t of DM/cow, and at least 60% of all homegrown feed that was consumed was grazed directly. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Use of aerial photos and field reconnaissance to predict groundwater flow of a karst area in the Inner Bluegrass Region of Kentucky

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gremos, K.; Sendlein, L.V.A.

1993-03-01

Significant areas of the continental US (Kentucky included) are underlain by karstified limestone. In many of these areas agriculture is a leading business and a potential non-point source of pollution to the groundwater. A study is underway to assess the Best Management Practices (BMP) on a farm in north-central Woodford County in Kentucky. As part of the study, various computer-based decision models for integrated farm operation will be assessed. Because surface area and run off are integral parts of all of these models, diversion of surface run off through karst features such as sinkholes will modify predictions from these models.more » This study utilizes areal photographs to identify all sinkholes on the property and characterize their morphometric parameters such as length, width, depth, and area and distribution. Sink hole areas represent approximately 10 percent of the area and all but a few discharge within the basin monitored as part of the model. The bedrock geology and fractures of the area have been defined using fracture trace analysis and a rectified drainage linear analysis. Surface drainage patterns, spring distribution, and stream and spring discharge data have been collected. Dye tracing has identified groundwater basins whose catchment area is outside the boundaries of the study site.« less

Within-farm transmission dynamics of foot and mouth disease as revealed by the 2001 epidemic in Great Britain.

PubMed

Chis Ster, Irina; Dodd, Peter J; Ferguson, Neil M

2012-08-01

This paper uses statistical and mathematical models to examine the potential impact of within-farm transmission dynamics on the spread of the 2001 foot and mouth disease (FMD) outbreak in Great Britain. We partly parameterize a simple within farm transmission model using data from experimental studies of FMD pathogenesis, embed this model within an existing between-farm transmission model, and then estimate unknown parameters (such as the species-specific within-farm reproduction number) from the 2001 epidemic case data using Markov Chain Monte-Carlo (MCMC) methods. If the probability of detecting an infected premises depends on farm size and species mix then the within-farm species specific basic reproduction ratios for baseline models are estimated to be 21 (16, 25) and 14 (10, 19) for cattle and sheep, respectively. Alternatively, if detection is independent of farm size, then the corresponding estimates are 49 (41, 61) and 10 (1.4, 21). Both model variants predict that the average fraction of total farm infectiousness accumulated prior to detection of infection on an IP is about 30-50% in cattle or mixed farms. The corresponding estimate for sheep farms depended more on the detection model, being 65-80% if detection was linked to the farms' characteristics, but only 25% if not. We highlighted evidence which reinforces the role of within-farm dynamics in contributing to the long tail of the 2001 epidemic. Copyright © 2012 Elsevier B.V. All rights reserved.

A review of network analysis terminology and its application to foot-and-mouth disease modelling and policy development.

PubMed

Dubé, C; Ribble, C; Kelton, D; McNab, B

2009-04-01

Livestock movements are important in spreading infectious diseases and many countries have developed regulations that require farmers to report livestock movements to authorities. This has led to the availability of large amounts of data for analysis and inclusion in computer simulation models developed to support policy formulation. Social network analysis has become increasingly popular to study and characterize the networks resulting from the movement of livestock from farm-to-farm and through other types of livestock operations. Network analysis is a powerful tool that allows one to study the relationships created among these operations, providing information on the role that they play in acquiring and spreading infectious diseases, information that is not readily available from more traditional livestock movement studies. Recent advances in the study of real-world complex networks are now being applied to veterinary epidemiology and infectious disease modelling and control. A review of the principles of network analysis and of the relevance of various complex network theories to infectious disease modelling and control is presented in this paper.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Ji Sung; Koo, Eunmo; Munoz-Esparza, Domingo

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines createsmore » the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.« less

The Interactive Effect of Diversification and Farming Scale on Productivity of Family Farm:Taking Rice Cultivation as An Example

NASA Astrophysics Data System (ADS)

Wei, Zhou

2017-05-01

Based on the diversification and cultivation scale, the rice cropping data of rural fixed observation points in 2011 were selected and the effect of diversification degree on rice productivity was analyzed by the Tobit model. The empirical results of the model show that diversification of sample farm will lead to loss of rice production efficiency. With the increase of rice planting scale, the loss of rice production efficiency will need to be further increased by diversification. Thus, we should stick to the family farm of specialized production operation. The transfer of land, the price and quantity of leasing, respecting the law of the market; the raising of funds can be considered non-subsidized capital market financing to help, while maintaining a certain degree of diversification, to avoid idle assets, low resource efficiency loss.

Risk factors associated with highly pathogenic avian influenza subtype H5N8 outbreaks on broiler duck farms in South Korea.

PubMed

Kim, W-H; An, J-U; Kim, J; Moon, O-K; Bae, S H; Bender, J B; Cho, S

2018-04-19

Highly Pathogenic Avian Influenza (HPAI) subtype H5N8 outbreaks occurred in poultry farms in South Korea in 2014 resulting in significant damage to the poultry industry. Between 2014 and 2016, the pandemic disease caused significant economic loss and social disruption. To evaluate the risk factors for HPAI infection in broiler duck farms, we conducted a retrospective case-control study on broiler duck farms. Forty-three farms with confirmed laboratories on premises were selected as the case group, and 43 HPAI-negative farms were designated as the control group. Control farms were matched based on farm location and were within a 3-km radius from the case premises. Spatial and environmental factors were characterized by site visit and plotted through a geographic information system (GIS). Univariable and multivariable logistic regression models were developed to assess possible risk factors associated with HPAI broiler duck farm infection. Four final variables were identified as risk factors in a final multivariable logistic model: "Farms with ≥7 flocks" (odds ratio [OR] = 6.99, 95% confidence interval [CI] 1.34-37.04), "Farm owner with ≥15 years of raising poultry career" (OR = 7.91, 95% CI 1.69-37.14), "Presence of any poultry farms located within 500 m of the farm" (OR = 6.30, 95% CI 1.08-36.93) and "Not using a faecal removal service" (OR = 27.78, 95% CI 3.89-198.80). This highlights that the HPAI H5N8 outbreaks in South Korea were associated with farm owner education, number of flocks and facilities and farm biosecurity. Awareness of these factors may help to reduce the spread of HPAI H5N8 across broiler duck farms in Korea during epidemics. Greater understanding of the risk factors for H5N8 may improve farm vulnerability to HPAI and other subtypes and help to establish policies to prevent re-occurrence. These findings are relevant to global prevention recommendations and intervention protocols. © 2018 Blackwell Verlag GmbH.

Financial evaluation of different vaccination strategies for controlling the bluetongue virus serotype 8 epidemic in The Netherlands in 2008.

PubMed

Velthuis, Annet G J; Mourits, Monique C M; Saatkamp, Helmut W; de Koeijer, Aline A; Elbers, Armin R W

2011-05-04

Bluetongue (BT) is a vector-borne disease of ruminants caused by bluetongue virus that is transmitted by biting midges (Culicoides spp.). In 2006, the introduction of BTV serotype 8 (BTV-8) caused a severe epidemic in Western and Central Europe. The principal effective veterinary measure in response to BT was believed to be vaccination accompanied by other measures such as movement restrictions and surveillance. As the number of vaccine doses available at the start of the vaccination campaign was rather uncertain, the Dutch Ministry of Agriculture, Nature and Food Quality and the Dutch agricultural industry wanted to evaluate several different vaccination strategies. This study aimed to rank eight vaccination strategies based on their efficiency (i.e. net costs in relation to prevented losses or benefits) for controlling the bluetongue virus serotype 8 epidemic in 2008. An economic model was developed that included the Dutch professional cattle, sheep and goat sectors together with the hobby farms. Strategies were evaluated based on the least cost - highest benefit frontier, the benefit-cost ratio and the total net returns. Strategy F, where all adult sheep at professional farms in The Netherlands would be vaccinated was very efficient at lowest costs, whereas strategy D, where additional to all adult sheep at professional farms also all adult cattle in the four Northern provinces would be vaccinated, was also very efficient but at a little higher costs. Strategy C, where all adult sheep and cattle at professional farms in the whole of The Netherlands would be vaccinated was also efficient but again at higher costs. This study demonstrates that a financial analysis differentiates between vaccination strategies and indicates important decision rules based on efficiency.

Financial Evaluation of Different Vaccination Strategies for Controlling the Bluetongue Virus Serotype 8 Epidemic in the Netherlands in 2008

PubMed Central

Velthuis, Annet G. J.; Mourits, Monique C. M.; Saatkamp, Helmut W.; de Koeijer, Aline A.; Elbers, Armin R. W.

2011-01-01

Background Bluetongue (BT) is a vector-borne disease of ruminants caused by bluetongue virus that is transmitted by biting midges (Culicoides spp.). In 2006, the introduction of BTV serotype 8 (BTV-8) caused a severe epidemic in Western and Central Europe. The principal effective veterinary measure in response to BT was believed to be vaccination accompanied by other measures such as movement restrictions and surveillance. As the number of vaccine doses available at the start of the vaccination campaign was rather uncertain, the Dutch Ministry of Agriculture, Nature and Food Quality and the Dutch agricultural industry wanted to evaluate several different vaccination strategies. This study aimed to rank eight vaccination strategies based on their efficiency (i.e. net costs in relation to prevented losses or benefits) for controlling the bluetongue virus serotype 8 epidemic in 2008. Methodology/Principal Findings An economic model was developed that included the Dutch professional cattle, sheep and goat sectors together with the hobby farms. Strategies were evaluated based on the least cost - highest benefit frontier, the benefit-cost ratio and the total net returns. Strategy F, where all adult sheep at professional farms in the Netherlands would be vaccinated was very efficient at lowest costs, whereas strategy D, where additional to all adult sheep at professional farms also all adult cattle in the four Northern provinces would be vaccinated, was also very efficient but at a little higher costs. Strategy C, where all adult sheep and cattle at professional farms in the whole of the Netherlands would be vaccinated was also efficient but again at higher costs. Conclusions/Significance This study demonstrates that a financial analysis differentiates between vaccination strategies and indicates important decision rules based on efficiency. PMID:21573195

Are Village Animal Health Workers Able to Assist in Strengthening Transboundary Animal Disease Control in Cambodia?

PubMed

Stratton, J; Toribio, J-A L M L; Suon, S; Young, J R; Cowled, B; Windsor, P A

2017-04-01

A cross-sectional survey of 445 Village Animal Health Workers (VAHWs) from 19 provinces in Cambodia was undertaken. The aim was to establish their levels of training, farm visit frequency, reasons for visits and disease reporting practices, enabling the strengths and weaknesses of the VAHW system in Cambodia to be determined, in providing both a fee-based smallholder livestock clinical service and a government partnership in transboundary animal disease (TAD) surveillance and control. The study used 'guided group interviews' and identified that VAHWs had good contact with farmers with 61.5% making more than one farm visit daily. However, incomes from services remained low, with 45% VAHWs obtaining between 20 and 40% of their household income from VAHW activities. VAHWs recorded relatively high rates of disease reporting, with 72% claiming they report diseases immediately and 74% undertaking monthly reporting to veterinary authorities. Logistic regression analysis revealed VAHW contact frequency with district and/or provincial officers was associated with more VAHW farm visits, and frequency of VAHW visits to smallholder farms was positively associated with average monthly expenditure on animal medication and equipment. This suggests that increased veterinary extension to VAHWs and access to veterinary equipment, vaccines and drugs may further increase VAHW-farmer engagement. VAHWs provide an accessible, market-based, animal health 'treatment and reporting' service linked to livestock smallholders across Cambodia. However, for improved TAD prevention and more efficient control of outbreaks, research that assesses provision of an animal health 'preventive-based' business model is urgently needed to reduce both the costs to farmers and the risks to the economy due to foot-and-mouth disease and other TADs in Cambodia. © 2015 Blackwell Verlag GmbH.

Prevalence and risk factors for foot and mouth disease infection in small ruminants in Israel.

PubMed

Elnekave, Ehud; van Maanen, Kees; Shilo, Hila; Gelman, Boris; Storm, Nick; Berdenstain, Svetlane; Berke, Olaf; Klement, Eyal

2016-03-01

During the last decade, 27% of the foot and mouth disease (FMD) outbreaks in Israel affected small ruminant (SR) farms. FMD outbreaks reoccur in Israel despite vaccination of all livestock and application of control measures. We performed a cross-sectional serological study, aimed at estimating the prevalence of FMD infection in SR in Israel and the possible risk factors for infection. Overall, 2305 samples of adult sheep (n=1948) and goats (n=357) were collected during 2011-14 in two separate surveys. One survey was based on random sampling of intensive management system farms and the other was originally aimed at the detection of Brucella melitensis at extensive and semi-intensive management system farms. Sera were tested by NS blocking ELISA (PrioCHECK(®)). The serological prevalence of antibodies against non structural proteins (NSP) of FMD virus was estimated at 3.7% (95% confidence interval (CI95%)=3.0% -4.5%). Additionally, a significantly lower infection prevalence (p value=0.049) of 1.0% (CI95%=0.1%-3.6%) was found in a small sample (197 sera) of young SR, collected during 2012. The positive samples from adult SR were scattered all over Israel, though two significant infection clusters were found by the spatial scan statistic. Occurrence of an outbreak on a non-SR farm within 5km distance was associated with a fifteen times increase in the risk of FMD infection of SR in the univariable analysis. Yet, this variable was not included in the multivariable analysis due to collinearities with the other independent variables. Multivariable logistic regression modeling found significantly negative associations (P value<0.05) of grazing and being in a herd larger than 500 animals with risk of infection. Grazing herds and herds larger than 500 animals, both represent farms that are intensively or semi-intensively managed. Higher maintenance of bio-safety, fewer introductions of new animals and higher vaccination compliance in these farms may explain their lower risk of infection by FMD virus. We conclude that despite the wide distribution of infection among SR farms, low farm level prevalence indicates that in Israel SR pose only limited role in the transmission and dissemination of FMD. This conclusion may be applicable for other endemic countries in which, similar to Israel, all livestock are vaccinated against FMD. Copyright © 2016 Elsevier B.V. All rights reserved.

A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

NASA Astrophysics Data System (ADS)

Norin, L.

2015-02-01

In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.

A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

NASA Astrophysics Data System (ADS)

Norin, L.

2014-08-01

In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Cross-Sectional Study Into the Prevalence of Dairy Cattle Lameness and Associated Herd-Level Risk Factors in England and Wales

PubMed Central

Griffiths, Bethany E.; Grove White, Dai; Oikonomou, Georgios

2018-01-01

Lameness is one of the most pressing issues within the dairy industry; it has severe economic implications while causing a serious impact on animal welfare. A study conducted approximately 10 years ago found the within farm lameness prevalence in the UK to be 36.8%. Our objective here is to provide an update on within farm lameness prevalence in the UK, and to provide further evidence on farm level risk factors. A convenience sample of 61 dairy farms were recruited across England and Wales from September 2015 to December 2016. A single farm visit was made and the milking herd was mobility scored, as the cows exited the milking parlor after morning, afternoon, or evening milking. Information regarding the farm and management system was then collected using a short interview with the farmer followed by collection of various subjective and objective measurements of the environment. The same, trained researcher performed all animal and facility-based measures on all visits. A series of univariable analyses were conducted to evaluate the association between various risk factors and herd lameness prevalence (logit transformed). A multivariable linear regression model was then fitted. The median number of milking cows per herd was 193, ranging from 74 to 1,519 cows. The mean within farm lameness prevalence was 31.6%, ranging from 5.8 to 65.4%. In total, 14,700 cows were mobility scored with 4,145 cows found to be lame (28.2%). A number of risk factors were associated with lameness at the univariable analysis level. Categorical risk factors retained in the final model were: resting area type, collecting yard groove spacing width, whether farms were undertaking the 60- to 100-day post calving claw trimming and the frequency of footbathing in the winter. The amount of concentrates fed in the milking parlors or out of parlor feeders was also associated with lameness prevalence. The results of this study have provided an update on the UK herd lameness prevalence and have confirmed the importance of cow comfort and footbathing frequency. The association between early lactation claw trimming and reduced lameness prevalence is, to the best of our knowledge, reported for the first time. PMID:29675419

Green Care: A Review of the Benefits and Potential of Animal-Assisted Care Farming Globally and in Rural America

PubMed Central

Artz, Brianna; Bitler Davis, Doris

2017-01-01

Simple Summary The term Green Care encompasses a number of therapeutic strategies that can include farm-animal-assisted therapy, horticultural therapy, and general, farm-based therapy. This review article provides an overview of how Green Care has been used as part of the therapeutic plan for a variety of psychological disorders and related physical disabilities in children, adolescents and adults. While many countries have embraced Green Care, and research-based evidence supports its efficacy in a variety of therapeutic models, it has not yet gained widespread popularity in the United States. We suggest that Green Care could prove to be an effective approach to providing mental health care in the U.S., particularly in rural areas that are typically underserved by more traditional mental health facilities, but have an abundance of farms, livestock, and green spaces where care might be effectively provided. Abstract The term Green Care includes therapeutic, social or educational interventions involving farming; farm animals; gardening or general contact with nature. Although Green Care can occur in any setting in which there is interaction with plants or animals, this review focuses on therapeutic practices occurring on farms. The efficacy of care farming is discussed and the broad utilization of care farming and farm care communities in Europe is reviewed. Though evidence from care farms in the United States is included in this review, the empirical evidence which could determine its efficacy is lacking. For example, the empirical evidence supporting or refuting the efficacy of therapeutic horseback riding in adults is minimal, while there is little non-equine care farming literature with children. The health care systems in Europe are also much different than those in the United States. In order for insurance companies to cover Green Care techniques in the United States, extensive research is necessary. This paper proposes community-based ways that Green Care methods can be utilized without insurance in the United States. Though Green Care can certainly be provided in urban areas, this paper focuses on ways rural areas can utilize existing farms to benefit the mental and physical health of their communities. PMID:28406428

A comparison of emission calculations using different modeled indicators with 1-year online measurements.

PubMed

Lengers, Bernd; Schiefler, Inga; Büscher, Wolfgang

2013-12-01

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm's characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow(-1) year(-1)) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow(-1) year(-1) (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between -6.4% and 10.5%), compared with findings from the literature.

From Invention to Innovation: Risk Analysis to Integrate One Health Technology in the Dairy Farm.

PubMed

Lombardo, Andrea; Boselli, Carlo; Amatiste, Simonetta; Ninci, Simone; Frazzoli, Chiara; Dragone, Roberto; De Rossi, Alberto; Grasso, Gerardo; Mantovani, Alberto; Brajon, Giovanni

2017-01-01

Current Hazard Analysis Critical Control Points (HACCP) approaches mainly fit for food industry, while their application in primary food production is still rudimentary. The European food safety framework calls for science-based support to the primary producers' mandate for legal, scientific, and ethical responsibility in food supply. The multidisciplinary and interdisciplinary project ALERT pivots on the development of the technological invention (BEST platform) and application of its measurable (bio)markers-as well as scientific advances in risk analysis-at strategic points of the milk chain for time and cost-effective early identification of unwanted and/or unexpected events of both microbiological and toxicological nature. Health-oriented innovation is complex and subject to multiple variables. Through field activities in a dairy farm in central Italy, we explored individual components of the dairy farm system to overcome concrete challenges for the application of translational science in real life and (veterinary) public health. Based on an HACCP-like approach in animal production, the farm characterization focused on points of particular attention (POPAs) and critical control points to draw a farm management decision tree under the One Health view (environment, animal health, food safety). The analysis was based on the integrated use of checklists (environment; agricultural and zootechnical practices; animal health and welfare) and laboratory analyses of well water, feed and silage, individual fecal samples, and bulk milk. The understanding of complex systems is a condition to accomplish true innovation through new technologies. BEST is a detection and monitoring system in support of production security, quality and safety: a grid of its (bio)markers can find direct application in critical points for early identification of potential hazards or anomalies. The HACCP-like self-monitoring in primary production is feasible, as well as the biomonitoring of live food producing animals as sentinel population for One Health.

Modeling large wind farms in conventionally neutral atmospheric boundary layers under varying initial conditions

NASA Astrophysics Data System (ADS)

Allaerts, Dries; Meyers, Johan

2014-05-01

Atmospheric boundary layers (ABL) are frequently capped by an inversion layer limiting the entrainment rate and boundary layer growth. Commonly used analytical models state that the entrainment rate is inversely proportional to the inversion strength. The height of the inversion turns out to be a second important parameter. Conventionally neutral atmospheric boundary layers (CNBL) are ABLs with zero surface heat flux developing against a stratified free atmosphere. In this regime the inversion-filling process is merely driven by the downward heat flux at the inversion base. As a result, CNBLs are strongly dependent on the heating history of the boundary layer and strong inversions will fail to erode during the course of the day. In case of large wind farms, the power output of the farm inside a CNBL will depend on the height and strength of the inversion above the boundary layer. On the other hand, increased turbulence levels induced by wind farms may partially undermine the rigid lid effect of the capping inversion, enhance vertical entrainment of air into the farm, and increase boundary layer growth. A suite of large eddy simulations (LES) is performed to investigate the effect of the capping inversion on the conventionally neutral atmospheric boundary layer and on the wind farm performance under varying initial conditions. For these simulations our in-house pseudo-spectral LES code SP-Wind is used. The wind turbines are modelled using a non-rotating actuator disk method. In the absence of wind farms, we find that a decrease in inversion strength corresponds to a decrease in the geostrophic angle and an increase in entrainment rate and geostrophic drag. Placing the initial inversion base at higher altitudes further reduces the effect of the capping inversion on the boundary layer. The inversion can be fully neglected once it is situated above the equilibrium height that a truly neutral boundary layer would attain under the same external conditions such as geostrophic wind speed and surface roughness. Wind farm simulations show the expected increase in boundary layer height and growth rate with respect to the case without wind farms. Raising the initial strength of the capping inversion in these simulations dampens the turbulent growth of the boundary layer above the farm, decreasing the farms energy extraction. The authors acknowledge support from the European Research Council (FP7-Ideas, grant no. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government.

Calibration of an electronic nose for poultry farm

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.

2017-03-01

Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.

Farm, household, and farmer characteristics associated with changes in management practices and technology adoption among dairy smallholders.

PubMed

Martínez-García, Carlos Galdino; Ugoretz, Sarah Janes; Arriaga-Jordán, Carlos Manuel; Wattiaux, Michel André

2015-02-01

This study explored whether technology adoption and changes in management practices were associated with farm structure, household, and farmer characteristics and to identify processes that may foster productivity and sustainability of small-scale dairy farming in the central highlands of Mexico. Factor analysis of survey data from 44 smallholders identified three factors-related to farm size, farmer's engagement, and household structure-that explained 70 % of cumulative variance. The subsequent hierarchical cluster analysis yielded three clusters. Cluster 1 included the most senior farmers with fewest years of education but greatest years of experience. Cluster 2 included farmers who reported access to extension, cooperative services, and more management changes. Cluster 2 obtained 25 and 35 % more milk than farmers in clusters 1 and 3, respectively. Cluster 3 included the youngest farmers, with most years of education and greatest availability of family labor. Access to a network and membership in a community of peers appeared as important contributors to success. Smallholders gravitated towards easy to implement technologies that have immediate benefits. Nonusers of high investment technologies found them unaffordable because of cost, insufficient farm size, and lack of knowledge or reliable electricity. Multivariate analysis may be a useful tool in planning extension activities and organizing channels of communication to effectively target farmers with varying needs, constraints, and motivations for change and in identifying farmers who may exemplify models of change for others who manage farms that are structurally similar but performing at a lower level.

Fast detection of Piscirickettsia salmonis in Salmo salar serum through MALDI-TOF-MS profiling.

PubMed

Olate, Verónica R; Nachtigall, Fabiane M; Santos, Leonardo S; Soto, Alex; Araya, Macarena; Oyanedel, Sandra; Díaz, Verónica; Marchant, Vanessa; Rios-Momberg, Mauricio

2016-03-01

Piscirickettsia salmonis is a pathogenic bacteria known as the aetiological agent of the salmonid rickettsial syndrome and causes a high mortality in farmed salmonid fishes. Detection of P. salmonis in farmed fishes is based mainly on molecular biology and immunohistochemistry techniques. These techniques are in most of the cases expensive and time consuming. In the search of new alternatives to detect the presence of P. salmonis in salmonid fishes, this work proposed the use of MALDI-TOF-MS to compare serum protein profiles from Salmo salar fish, including experimentally infected and non-infected fishes using principal component analysis (PCA). Samples were obtained from a controlled bioassay where S. salar was challenged with P. salmonis in a cohabitation model and classified according to the presence or absence of the bacteria by real time PCR analysis. MALDI spectra of the fish serum samples showed differences in its serum protein composition. These differences were corroborated with PCA analysis. The results demonstrated that the use of both MALDI-TOF-MS and PCA represents a useful tool to discriminate the fish status through the analysis of salmonid serum samples. Copyright © 2016 John Wiley & Sons, Ltd.

78 FR 24693 - Draft Qualitative Risk Assessment of Risk of Activity/Food Combinations for Activities (Outside...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-26

... Analysis and Risk-Based Preventive Controls for Human Food'' (the proposed preventive controls rule) and... Farm.'' The purpose of the draft RA is to provide a science-based risk analysis of those activity/food... Food, Drug, and Cosmetic Act for hazard analysis and risk-based preventive controls (the proposed...

Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model

NASA Astrophysics Data System (ADS)

Arnold, R. T.; Troost, Christian; Berger, Thomas

2015-01-01

Irrigation with surface water enables Chilean agricultural producers to generate one of the country's most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water-use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example, due to the cycles of El Niño or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years overproportionally impact on their supply of irrigation water and thereby farm profitability. This study uses a simulation model that consists of a hydrological balance model component and a multiagent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios.

Development and application of incrementally complex tools for wind turbine aerodynamics

NASA Astrophysics Data System (ADS)

Gundling, Christopher H.

Advances and availability of computational resources have made wind farm design using simulation tools a reality. Wind farms are battling two issues, affecting the cost of energy, that will make or break many future investments in wind energy. The most significant issue is the power reduction of downstream turbines operating in the wake of upstream turbines. The loss of energy from wind turbine wakes is difficult to predict and the underestimation of energy losses due to wakes has been a common problem throughout the industry. The second issue is a shorter lifetime of blades and past failures of gearboxes due to increased fluctuations in the unsteady loading of waked turbines. The overall goal of this research is to address these problems by developing a platform for a multi-fidelity wind turbine aerodynamic performance and wake prediction tool. Full-scale experiments in the field have dramatically helped researchers understand the unique issues inside a large wind farm, but experimental methods can only be used to a limited extent due to the cost of such field studies and the size of wind farms. The uncertainty of the inflow is another inherent drawback of field experiments. Therefore, computational fluid dynamics (CFD) predictions, strategically validated using carefully performed wind farm field campaigns, are becoming a more standard design practice. The developed CFD models include a blade element model (BEM) code with a free-vortex wake, an actuator disk or line based method with large eddy simulations (LES) and a fully resolved rotor based method with detached eddy simulations (DES) and adaptive mesh refinement (AMR). To create more realistic simulations, performance of a one-way coupling between different mesoscale atmospheric boundary layer (ABL) models and the three microscale CFD solvers is tested. These methods are validated using data from incrementally complex test cases that include the NREL Phase VI wind tunnel test, the Sexbierum wind farm and the Lillgrund offshore wind farm. By cross-comparing the lowest complexity free-vortex method with the higher complexity methods, a fast and accurate simulation tool has been generated that can perform wind farm simulations in a few hours.

Streamlining machine learning in mobile devices for remote sensing

NASA Astrophysics Data System (ADS)

Coronel, Andrei D.; Estuar, Ma. Regina E.; Garcia, Kyle Kristopher P.; Dela Cruz, Bon Lemuel T.; Torrijos, Jose Emmanuel; Lim, Hadrian Paulo M.; Abu, Patricia Angela R.; Victorino, John Noel C.

2017-09-01

Mobile devices have been at the forefront of Intelligent Farming because of its ubiquitous nature. Applications on precision farming have been developed on smartphones to allow small farms to monitor environmental parameters surrounding crops. Mobile devices are used for most of these applications, collecting data to be sent to the cloud for storage, analysis, modeling and visualization. However, with the issue of weak and intermittent connectivity in geographically challenged areas of the Philippines, the solution is to provide analysis on the phone itself. Given this, the farmer gets a real time response after data submission. Though Machine Learning is promising, hardware constraints in mobile devices limit the computational capabilities, making model development on the phone restricted and challenging. This study discusses the development of a Machine Learning based mobile application using OpenCV libraries. The objective is to enable the detection of Fusarium oxysporum cubense (Foc) in juvenile and asymptomatic bananas using images of plant parts and microscopic samples as input. Image datasets of attached, unattached, dorsal, and ventral views of leaves were acquired through sampling protocols. Images of raw and stained specimens from soil surrounding the plant, and sap from the plant resulted to stained and unstained samples respectively. Segmentation and feature extraction techniques were applied to all images. Initial findings show no significant differences among the different feature extraction techniques. For differentiating infected from non-infected leaves, KNN yields highest average accuracy, as opposed to Naive Bayes and SVM. For microscopic images using MSER feature extraction, KNN has been tested as having a better accuracy than SVM or Naive-Bayes.

Non-hazardous pesticide concentrations in surface waters: An integrated approach simulating application thresholds and resulting farm income effects.

PubMed

Bannwarth, M A; Grovermann, C; Schreinemachers, P; Ingwersen, J; Lamers, M; Berger, T; Streck, T

2016-01-01

Pesticide application rates are high and increasing in upland agricultural systems in Thailand producing vegetables, fruits and ornamental crops, leading to the pollution of stream water with pesticide residues. The objective of this study was to determine the maximum per hectare application rates of two widely used pesticides that would achieve non-hazardous pesticide concentrations in the stream water and to evaluate how farm household incomes would be affected if farmers complied with these restricted application rates. For this purpose we perform an integrated modeling approach of a hydrological solute transport model (the Soil and Water Assessment Tool, SWAT) and an agent-based farm decision model (Mathematical Programming-based Multi-Agent Systems, MPMAS). SWAT was used to simulate the pesticide fate and behavior. The model was calibrated to a 77 km(2) watershed in northern Thailand. The results show that to stay under a pre-defined eco-toxicological threshold, the current average application of chlorothalonil (0.80 kg/ha) and cypermethrin (0.53 kg/ha) would have to be reduced by 80% and 99%, respectively. The income effect of such reductions was simulated using MPMAS. The results suggest that if farm households complied with the application thresholds then their income would reduce by 17.3% in the case of chlorothalonil and by 38.3% in the case of cypermethrin. Less drastic income effects can be expected if methods of integrated pest management were more widely available. The novelty of this study is to combine two models from distinctive disciplines to evaluate pesticide reduction scenarios based on real-world data from a single study site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of the effect of accounting method, IPCC v. LCA, on grass-based and confinement dairy systems' greenhouse gas emissions.

PubMed

O'Brien, D; Shalloo, L; Patton, J; Buckley, F; Grainger, C; Wallace, M

2012-09-01

Life cycle assessment (LCA) and the Intergovernmental Panel on Climate Change (IPCC) guideline methodology, which are the principal greenhouse gas (GHG) quantification methods, were evaluated in this study using a dairy farm GHG model. The model was applied to estimate GHG emissions from two contrasting dairy systems: a seasonal calving pasture-based dairy farm and a total confinement dairy system. Data used to quantify emissions from these systems originated from a research study carried out over a 1-year period in Ireland. The genetic merit of cows modelled was similar for both systems. Total mixed ration was fed in the Confinement system, whereas grazed grass was mainly fed in the grass-based system. GHG emissions from these systems were quantified per unit of product and area. The results of both methods showed that the dairy system that emitted the lowest GHG emissions per unit area did not necessarily emit the lowest GHG emissions possible for a given level of product. Consequently, a recommendation from this study is that GHG emissions be evaluated per unit of product given the growing affluent human population and increasing demand for dairy products. The IPCC and LCA methods ranked dairy systems' GHG emissions differently. For instance, the IPCC method quantified that the Confinement system reduced GHG emissions per unit of product by 8% compared with the grass-based system, but the LCA approach calculated that the Confinement system increased emissions by 16% when off-farm emissions associated with primary dairy production were included. Thus, GHG emissions should be quantified using approaches that quantify the total GHG emissions associated with the production system, so as to determine whether the dairy system was causing emissions displacement. The IPCC and LCA methods were also used in this study to simulate, through a dairy farm GHG model, what effect management changes within both production systems have on GHG emissions. The findings suggest that single changes have a small mitigating effect on GHG emissions (<5%), except for strategies used to control emissions from manure storage in the Confinement system (14% to 24%). However, when several management strategies were combined, GHG emissions per unit of product could be reduced significantly (15% to 30%). The LCA method was identified as the preferred approach to assess the effect of management changes on GHG emissions, but the analysis indicated that further standardisation of the approach is needed given the sensitivity of the approach to allocation decisions regarding milk and meat.

Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis.

PubMed

Steensels, Machteld; Maltz, Ephraim; Bahr, Claudia; Berckmans, Daniel; Antler, Aharon; Halachmi, Ilan

2017-05-01

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow. In a first validation step (within-farm), the model was calibrated on the database of each farm separately. Two thirds of the sick cows and an equal number of healthy cows were randomly selected for model validation. The remaining one third of the cows, which did not participate in the model validation, were used for model calibration. In order to overcome the random selection effect, this procedure was repeated 100 times. In a second (between-farms) validation step, the model was calibrated on one farm and validated on another farm. Within-farm accuracy, ranging from 74 to 79%, was higher than between-farm accuracy, ranging from 49 to 72%, in all farms. The within-farm sensitivities ranged from 78 to 90%, and specificities ranged from 71 to 74%. The between-farms sensitivities ranged from 65 to 95%. The developed model can be improved in future research, by employing other variables that can be added; or by exploring other models to achieve greater sensitivity and specificity.

An economic decision-making support system for selection of reproductive management programs on dairy farms.

PubMed

Giordano, J O; Fricke, P M; Wiltbank, M C; Cabrera, V E

2011-12-01

Because the reproductive performance of lactating dairy cows influences the profitability of dairy operations, predicting the future reproductive and economic performance of dairy herds through decision support systems would be valuable to dairy producers and consultants. In this study, we present a highly adaptable tool created based on a mathematical model combining Markov chain simulation with partial budgeting to obtain the net present value (NPV; $/cow per year) of different reproductive management programs. The growing complexity of reproductive programs used by dairy farms demands that new decision support systems precisely reflect the events that occur on the farm. Therefore, the model requires productive, reproductive, and economic input data used for simulation of farm conditions to account for all factors related to reproductive management that increase costs and generate revenue. The economic performance of 3 different reproductive programs can be simultaneously compared with the current model. A program utilizing 100% visual estrous detection (ED) for artificial insemination (AI) is used as a baseline for comparison with 2 other programs that may include 100% timed AI (TAI) as well as any combination of TAI and ED. A case study is presented in which the model was used to compare 3 different reproductive management strategies (100% ED baseline compared with two 100% TAI options) using data from a commercial farm in Wisconsin. Sensitivity analysis was then used to assess the effect of varying specific reproductive parameters on the NPV. Under the simulated conditions of the case study, the model indicated that the two 100% TAI programs were superior to the 100% ED program and, of the 100% TAI programs, the one with the higher conception rate (CR) for resynchronized AI services was economically superior despite having higher costs and a longer interbreeding interval. A 4% increase in CR for resynchronized AI was sufficient for the inferior 100% TAI to outperform the superior program. Adding ED to the 100% TAI programs was only beneficial for the program with the lower CR. The improvement in service rate required for the 100% ED program to have the same NPV as the superior 100% TAI program was 12%. The decision support system developed in this study is a valuable tool that may be used to assist dairy producers and industry consultants in selecting the best farm-specific reproductive management strategy. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The risk factors for avian influenza on poultry farms: a meta-analysis.

PubMed

Wang, Youming; Li, Peng; Wu, Yangli; Sun, Xiangdong; Yu, Kangzhen; Yu, Chuanhua; Qin, Aijian

2014-11-01

Avian influenza is a severe threat both to humans and poultry, but so far, no systematic review on the identification and evaluation of the risk factors of avian influenza infection has been published. The objective of this meta-analysis is to provide evidence for decision-making and further research on AI prevention through identifying the risk factors associated with AI infection on poultry farms. The results from 15 selected studies on risk factors for AI infections on poultry farms were analyzed quantitatively by meta-analysis. Open water source (OR=2.89), infections on nearby farms (OR=4.54), other livestock (OR=1.90) and disinfection of farm (OR=0.54) have significant association with AI infection on poultry farms. The subgroup analysis results indicate that there exist different risk factors for AI infections in different types of farms. The main risk factors for AI infection in poultry farms are environmental conditions (open water source, infections on nearby farms), keeping other livestock on the same farm and no disinfection of the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM

PubMed Central

Hood, Heather M.; Ocasio, Linda R.; Sachs, Matthew S.; Galagan, James E.

2013-01-01

The filamentous fungus Neurospora crassa played a central role in the development of twentieth-century genetics, biochemistry and molecular biology, and continues to serve as a model organism for eukaryotic biology. Here, we have reconstructed a genome-scale model of its metabolism. This model consists of 836 metabolic genes, 257 pathways, 6 cellular compartments, and is supported by extensive manual curation of 491 literature citations. To aid our reconstruction, we developed three optimization-based algorithms, which together comprise Fast Automated Reconstruction of Metabolism (FARM). These algorithms are: LInear MEtabolite Dilution Flux Balance Analysis (limed-FBA), which predicts flux while linearly accounting for metabolite dilution; One-step functional Pruning (OnePrune), which removes blocked reactions with a single compact linear program; and Consistent Reproduction Of growth/no-growth Phenotype (CROP), which reconciles differences between in silico and experimental gene essentiality faster than previous approaches. Against an independent test set of more than 300 essential/non-essential genes that were not used to train the model, the model displays 93% sensitivity and specificity. We also used the model to simulate the biochemical genetics experiments originally performed on Neurospora by comprehensively predicting nutrient rescue of essential genes and synthetic lethal interactions, and we provide detailed pathway-based mechanistic explanations of our predictions. Our model provides a reliable computational framework for the integration and interpretation of ongoing experimental efforts in Neurospora, and we anticipate that our methods will substantially reduce the manual effort required to develop high-quality genome-scale metabolic models for other organisms. PMID:23935467

Tracking unaccounted water use in data sparse arid environment

NASA Astrophysics Data System (ADS)

Hafeez, M. M.; Edraki, M.; Ullah, M. K.; Chemin, Y.; Sixsmith, J.; Faux, R.

2009-12-01

Hydrological knowledge of irrigated farms within the inundation plains of the Murray Darling Basin (MDB) is very limited in quality and reliability of the observation network that has been declining rapidly over the past decade. This paper focuses on Land Surface Diversions (LSD) that encompass all forms of surface water diversion except the direct extraction of water from rivers, watercourses and lakes by farmers for the purposes of irrigation and stock and domestic supply. Its accurate measurement is very challenging, due to the practical difficulties associated with separating the different components of LSD and estimating them accurately for a large catchment. The inadequacy of current methods of measuring and monitoring LSD poses severe limitations on existing and proposed policies for managing such diversions. It is commonly believed that LSD comprises 20-30% of total diversions from river valleys in the MDB areas. But, scientific estimates of LSD do not exist, because they were considered unimportant prior the onset of recent draught in Australia. There is a need to develop hydrological water balance models through the coupling of hydrological variables derived from on ground hydrological measurements and remote sensing techniques to accurately model LSD. Typically, the hydrological water balance components for farm/catchment scale models includes: irrigation inflow, outflow, rainfall, runoff, evapotranspiration, soil moisture change and deep percolation. The actual evapotranspiration (ETa) is the largest and single most important component of hydrological water balance model. An accurate quantification of all components of hydrological water balance model at farm/catchment scale is of prime importance to estimate the volume of LSD. A hydrological water balance model is developed to calculate LSD at 6 selected pilot farms. The catchment hydrological water balance model is being developed by using selected parameters derived from hydrological water balance model at farm scale. LSD results obtained through the modelling process have been compared with LSD estimates measured with the ground observed data at 6 pilot farms. The differences between the values are between 3 to 5 percent of the water inputs which is within the confidence limit expected from such analysis. Similarly, the LSD values at the catchment scale have been estimated with a great confidence. The hydrological water balance models at farm and catchment scale provide reliable quantification of LSD. Improved LSD estimates can guide water management decisions at farm to catchment scale and could be instrumental for enhancing the integrity of the water allocation process and making them fairer and equitable across stakeholders.

Social environments, risk-taking and injury in farm adolescents

PubMed Central

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-01-01

Background Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. Objectives In a nationally representative sample of young Canadians aged 11–15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Methods Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Results Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Conclusions Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. PMID:28137978

Role of self-sufficiency, productivity and diversification on the economic sustainability of farming systems with autochthonous sheep breeds in less favoured areas in Southern Europe.

PubMed

Ripoll-Bosch, R; Joy, M; Bernués, A

2014-08-01

Traditional mixed livestock cereal- and pasture-based sheep farming systems in Europe are threatened by intensification and specialisation processes. However, the intensification process does not always yield improved economic results or efficiency. This study involved a group of farmers that raised an autochthonous sheep breed (Ojinegra de Teruel) in an unfavourable area of North-East Spain. This study aimed to typify the farms and elucidate the existing links between economic performance and certain sustainability indicators (i.e. productivity, self-sufficiency and diversification). Information was obtained through direct interviews with 30 farms (73% of the farmers belonging to the breeders association). Interviews were conducted in 2009 and involved 32 indicators regarding farm structure, management and economic performance. With a principal component analysis, three factors were obtained explaining 77.9% of the original variance. This factors were named as inputs/self-sufficiency, which included the use of on-farm feeds, the amount of variable costs per ewe and economic performance; productivity, which included lamb productivity and economic autonomy; and productive orientation, which included the degree of specialisation in production. A cluster analysis identified the following four groups of farms: high-input intensive system; low-input self-sufficient system; specialised livestock system; and diversified crops-livestock system. In conclusion, despite the large variability between and within groups, the following factors that explain the economic profitability of farms were identified: (i) high feed self-sufficiency and low variable costs enhance the economic performance (per labour unit) of the farms; (ii) animal productivity reduces subsidy dependence, but does not necessarily imply better economic performance; and (iii) diversity of production enhances farm flexibility, but is not related to economic performance.

IBSEM: An Individual-Based Atlantic Salmon Population Model.

PubMed

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a 'wild' genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors.

A modelling approach for the assessment of the effects of Common Agricultural Policy measures on farmland biodiversity in the EU27.

PubMed

Overmars, Koen P; Helming, John; van Zeijts, Henk; Jansson, Torbjörn; Terluin, Ida

2013-09-15

In this paper we describe a methodology to model the impacts of policy measures within the Common Agricultural Policy (CAP) on farm production, income and prices, and on farmland biodiversity. Two stylised scenarios are used to illustrate how the method works. The effects of CAP measures, such as subsidies and regulations, are calculated and translated into changes in land use and land-use intensity. These factors are then used to model biodiversity with a species-based indicator on a 1 km scale in the EU27. The Common Agricultural Policy Regionalised Impact Modelling System (CAPRI) is used to conduct the economic analysis and Dyna-CLUE (Conversion of Land Use and its Effects) is used to model land use changes. An indicator that expresses the relative species richness was used as the indicator for biodiversity in agricultural areas. The methodology is illustrated with a baseline scenario and two scenarios that include a specific policy. The strength of the methodology is that impacts of economic policy instruments can be linked to changes in agricultural production, prices and incomes, on the one hand, and to biodiversity effects, on the other - with land use and land-use intensity as the connecting drivers. The method provides an overall assessment, but for detailed impact assessment at landscape, farm or field level, additional analysis would be required. Copyright © 2013 Elsevier Ltd. All rights reserved.

Physical activity and sedentary behaviours among rural adults in Suixi, China: a cross-sectional study.

PubMed

Ding, Ding; Sallis, James F; Hovell, Melbourne F; Du, Jianzhong; Zheng, Miao; He, Haiying; Owen, Neville

2011-04-26

Modernisation and urbanisation have led to lifestyle changes and increasing risks for chronic diseases in China. Physical activity and sedentary behaviours among rural populations need to be better understood, as the rural areas are undergoing rapid transitions. This study assessed levels of physical activity and sedentary behaviours of farming and non-farming adults in rural Suixi, described activity differences between farming and non-farming seasons, and examined correlates of leisure-time physical activity (LTPA) and TV viewing. A random sample of rural adults (n=287) in Suixi County, Guangdong, China were surveyed in 2009 by trained interviewers. Questionnaires assessed multiple physical activities and sedentary behaviours, and their correlates. Analysis of covariance compared activity patterns across occupations, and multiple logistic regressions assessed correlates of LTPA and TV viewing. Quantitative data analyses were followed by community consultation for validation and interpretation of findings. Activity patterns differed by occupation. Farmers were more active through their work than other occupations, but were less active and more sedentary during the non-farming season than the farming season. Rural adults in Suixi generally had a low level of LTPA and a high level of TV viewing. Marital status, household size, social modelling for LTPA and owning sports equipment were significantly associated with LTPA but not with TV time. Most findings were validated through community consultation. For chronic disease prevention, attention should be paid to the currently decreasing occupational physical activity and increasing sedentary behaviours in rural China. Community and socially-based initiatives provide opportunities to promote LTPA and prevent further increase in sedentary behaviours. © 2011 Ding et al; licensee BioMed Central Ltd.

Prospective and participatory integrated assessment of agricultural systems from farm to regional scales: Comparison of three modeling approaches.

PubMed

Delmotte, Sylvestre; Lopez-Ridaura, Santiago; Barbier, Jean-Marc; Wery, Jacques

2013-11-15

Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS. Copyright © 2013 Elsevier Ltd. All rights reserved.

Factors Affecting Herd Status for Bovine Tuberculosis in Dairy Cattle in Northern Thailand

PubMed Central

Singhla, Tawatchai; Punyapornwithaya, Veerasak; VanderWaal, Kimberly L.; Alvarez, Julio; Sreevatsan, Srinand; Phornwisetsirikun, Somphorn; Sankwan, Jamnong; Srijun, Mongkol; Wells, Scott J.

2017-01-01

The objective of this case-control study was to identify farm-level risk factors associated with bovine tuberculosis (bTB) in dairy cows in northern Thailand. Spatial analysis was performed to identify geographical clustering of case-farms located in Chiang Mai and Chiang Rai provinces in northern Thailand. To identify management factors affecting bTB status, a matched case-control study was conducted with 20 case-farms and 38 control-farms. Case-farms were dairy farms with at least single intradermal tuberculin test- (SIT-) reactor(s) in the farms during 2011 to 2015. Control-farms were dairy farms with no SIT-reactors in the same period and located within 5 km from case-farms. Questionnaires were administered for data collection with questions based on epidemiological plausibility and characteristics of the local livestock industry. Data were analyzed using multiple logistic regressions. A significant geographic cluster was identified only in Chiang Mai province (p < 0.05). The risk factor associated with presence of SIT-reactors in dairy herds located in this region was purchasing dairy cows from dealers (OR = 5.85, 95% CI = 1.66–20.58, and p = 0.006). From this study, it was concluded that geographic clustering was identified for dairy farms with SIT-reactors in these provinces, and the cattle movements through cattle dealers increased the risks for SIT-reactor farm status. PMID:28553557

Concentrations of the urinary pyrethroid metabolite 3-phenoxybenzoic acid in farm worker families in the MICASA study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trunnelle, Kelly J., E-mail: kjtrunnelle@ucdavis.edu; Bennett, Deborah H.; Ahn, Ki Chang

Indoor pesticide exposure is a growing concern, particularly from pyrethroids, a commonly used class of pesticides. Pyrethroid concentrations may be especially high in homes of immigrant farm worker families who often live in close proximity to agricultural fields, and are faced with poor housing conditions, causing higher pest infestation and more pesticide use. We investigate exposure of farm worker families to pyrethroids in a study of mothers and children living in Mendota, CA within the population-based Mexican Immigration to California: Agricultural Safety and Acculturation (MICASA) Study. We present pyrethroid exposure based on an ELISA analysis of urinary metabolite 3-phenoxybenzoic acidmore » (3PBA) levels among 105 women and 103 children. The median urinary 3PBA levels (children=2.56 ug/g creatinine, mothers=1.46 ug/g creatinine) were higher than those reported in population based studies for the United States general population, but similar to or lower than studies with known high levels of pyrethroid exposure. A positive association was evident between poor housing conditions and the urinary metabolite levels, showing that poor housing conditions are a contributing factor to the higher levels of 3PBA seen in the urine of these farm worker families. Further research is warranted to fully investigate sources of exposure. - Highlights: • We investigate exposure of farm worker families to pyrethroids. • We present pyrethroid exposure based on an ELISA analysis of urinary 3PBA levels. • 3PBA levels were higher than those reported for the U.S. general population. • Poor housing conditions may be associated with pyrethroid exposure.« less

Compatibility between livestock databases used for quantitative biosecurity response in New Zealand.

PubMed

Jewell, C P; van Andel, M; Vink, W D; McFadden, A M J

2016-05-01

To characterise New Zealand's livestock biosecurity databases, and investigate their compatibility and capacity to provide a single integrated data source for quantitative outbreak analysis. Contemporary snapshots of the data in three national livestock biosecurity databases, AgriBase, FarmsOnLine (FOL) and the National Animal Identification and Tracing Scheme (NAIT), were obtained on 16 September, 1 September and 30 April 2014, respectively, and loaded into a relational database. A frequency table of animal numbers per farm was calculated for the AgriBase and FOL datasets. A two dimensional kernel density estimate was calculated for farms reporting the presence of cattle, pigs, deer, and small ruminants in each database and the ratio of farm densities for AgriBase versus FOL calculated. The extent to which records in the three databases could be matched and linked was quantified, and the level of agreement amongst them for the presence of different species on properties assessed using Cohen's kappa statistic. AgriBase contained fewer records than FOL, but recorded animal numbers present on each farm, whereas FOL contained more records, but captured only presence/absence of animals. The ratio of farm densities in AgriBase relative to FOL for pigs and deer was reasonably homogeneous across New Zealand, with AgriBase having a farm density approximately 80% of FOL. For cattle and small ruminants, there was considerable heterogeneity, with AgriBase showing a density of cattle farms in the Central Otago region that was 20% of FOL, and a density of small ruminant farms in the central West Coast area that was twice that of FOL. Only 37% of records in FOL could be linked to AgriBase, but the level of agreement for the presence of different species between these databases was substantial (kappa>0.6). Both NAIT and FOL shared common farm identifiers which could be used to georeference animal movements, and there was a fair to substantial agreement (kappa 0.32-0.69) between these databases for the presence of cattle and deer on properties. The three databases broadly agreed with each other, but important differences existed in both species composition and spatial coverage which raises concern over their accuracy. Importantly, they cannot be reliably linked together to provide a single picture of New Zealand's livestock industry, limiting the ability to use advanced quantitative techniques to provide effective decision support during disease outbreaks. We recommend that a single integrated database be developed, with alignment of resources and legislation for its upkeep.

Likelihood of a marine vessel accident from wind energy development in the Atlantic: Likelihood of shipping accident from wind energy in the Atlantic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Copping, Andrea; Breithaupt, Stephen; Whiting, Jonathan

2015-11-02

Offshore wind energy development is planned for areas off the Atlantic coast. Many of the planned wind development areas fall within traditional commercial vessel routes. In order to mitigate possible hazards to ships and to wind turbines, it is important to understand the potential for increased risk to commercial shipping from the presence of wind farms. Using Automatic Identification System (AIS) data, historical shipping routes between ports in the Atlantic were identified, from Maine to the Florida Straits. The AIS data were also used as inputs to a numerical model that can simulate cargo, tanker and tug/towing vessel movement alongmore » typical routes. The model was used to recreate present day vessel movement, as well as to simulate future routing that may be required to avoid wind farms. By comparing the present and future routing of vessels, a risk analysis was carried out to determine the increased marginal risk of vessel collisions, groundings, and allisions with stationary objects, due to the presence of wind farms. The outcome of the analysis showed little increase in vessel collisions or allisions, and a decrease in groundings as more vessels were forced seaward by the wind farms.« less

Conducting On-Farm Animal Research: Procedures & Economic Analysis.

ERIC Educational Resources Information Center

Amir, Pervaiz; Knipscheer, Hendrik C.

This book is intended to give animal scientists elementary tools to perform on-farm livestock analysis and to provide crop-oriented farming systems researchers with methods for conducting animal research. Chapter 1 describes farming systems research as a systems approach to on-farm animal research. Chapter 2 outlines some important…

Emergy analysis of a farm biogas project in China: A biophysical perspective of agricultural ecological engineering

NASA Astrophysics Data System (ADS)

Zhou, S. Y.; Zhang, B.; Cai, Z. F.

2010-05-01

This paper aims to present a biophysical understanding of the agricultural ecological engineering by emergy analysis for a farm biogas project in China as a representative case. Accounting for the resource inputs into and accumulation within the project, as well as the outputs to the social system, emergy analysis provides an empirical study in the biophysical dimension of the agricultural ecological engineering. Economic benefits and ecological economic benefits of the farm biogas project indicated by market value and emergy monetary value are discussed, respectively. Relative emergy-based indices such as renewability (R%), emergy yield ratio (EYR), environmental load ratio (ELR) and environmental sustainability index (ESI) are calculated to evaluate the environmental load and local sustainability of the concerned biogas project. The results show that the farm biogas project has more reliance on the local renewable resources input, less environmental pressure and higher sustainability compared with other typical agricultural systems. In addition, holistic evaluation and its policy implications for better operation and management of the biogas project are presented.

Control of Groundwater Pollution from Animal Feeding Operations: A Farm-Level Dynamic Model for Policy Analysis

NASA Astrophysics Data System (ADS)

Wang, J.; Baerenklau, K.

2012-12-01

Consolidation in livestock production generates higher farm incomes due to economies of scale, but it also brings waste disposal problems. Over-application of animal waste on adjacent land produces adverse environmental and health effects, including groundwater nitrate pollution. The situation is particularly noticeable in California. In respond to this increasingly severe problem, EPA published a type of command-and-control regulation for concentrated animal feeding operations (CAFOs) in 2003. The key component of the regulation is its nutrient management plans (NMPs), which intend to limit the land application rates of animal waste. Although previous studies provide a full perspective on potential economic impacts for CAFOs to meet nutrient standards, their models are static and fail to reflect changes in management practices other than spreading manure on additional land and changing cropping patterns. We develop a dynamic environmental-economic modeling framework for representative CAFOs. The framework incorporates four models (i.e., animal model, crop model, hydrologic model, and economic model) that include various components such as herd management, manure handling system, crop rotation, water sources, irrigation system, waste disposal options, and pollutant emissions. We also include the dynamics of soil characteristics in the rootzone as well as the spatial heterogeneity of the irrigation system. The operator maximizes discounted total farm profit over multiple periods subject to environmental regulations. Decision rules from the dynamic optimization problem demonstrate best management practices for CAFOs to improve their economic and environmental performance. Results from policy simulations suggest that direct quantity restrictions of emission or incentive-based emission policies are much more cost-effective than the standard approach of limiting the amount of animal waste that may be applied to fields (as shown in the figure below); reason being, policies targeting intermediate pollution and final pollution create incentives for the operator to examine the effects of other management practices to reduce pollution in addition to controlling the polluting inputs. Incentive-based mechanisms are slightly more cost-effective than quantity controls when seasonal emissions fluctuate. Our approach demonstrates the importance of taking into account the spatial & temporal dynamics in the rootzone and the integrated effects of water, nitrogen, and salinity on crop yield and nitrate emissions. It also highlights the significant role the environment can play in pollution control and the potential benefits from designing policies that acknowledge this role.oss of Total Net Farm Income Under Alternative Policies

Wavelet Analysis for Wind Fields Estimation

PubMed Central

Leite, Gladeston C.; Ushizima, Daniela M.; Medeiros, Fátima N. S.; de Lima, Gilson G.

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B3 spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms−1. Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699

Modeling sheep pox disease from the 1994-1998 epidemic in Evros Prefecture, Greece.

PubMed

Malesios, C; Demiris, N; Abas, Z; Dadousis, K; Koutroumanidis, T

2014-10-01

Sheep pox is a highly transmissible disease which can cause serious loss of livestock and can therefore have major economic impact. We present data from sheep pox epidemics which occurred between 1994 and 1998. The data include weekly records of infected farms as well as a number of covariates. We implement Bayesian stochastic regression models which, in addition to various explanatory variables like seasonal and environmental/meteorological factors, also contain serial correlation structure based on variants of the Ornstein-Uhlenbeck process. We take a predictive view in model selection by utilizing deviance-based measures. The results indicate that seasonality and the number of infected farms are important predictors for sheep pox incidence. Copyright © 2014 Elsevier Ltd. All rights reserved.

A generic bio-economic farm model for environmental and economic assessment of agricultural systems.

PubMed

Janssen, Sander; Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K

2010-12-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

PubMed Central

Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K.

2010-01-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. PMID:21113782

Optimization of land use of agricultural farms in Sumedang regency by using linear programming models

NASA Astrophysics Data System (ADS)

Zenis, F. M.; Supian, S.; Lesmana, E.

2018-03-01

Land is one of the most important assets for farmers in Sumedang Regency. Therefore, agricultural land should be used optimally. This study aims to obtain the optimal land use composition in order to obtain maximum income. The optimization method used in this research is Linear Programming Models. Based on the results of the analysis, the composition of land use for rice area of 135.314 hectares, corn area of 11.798 hectares, soy area of 2.290 hectares, and peanuts of 2.818 hectares with the value of farmers income of IDR 2.682.020.000.000,-/year. The results of this analysis can be used as a consideration in decisions making about cropping patterns by farmers.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs.

PubMed

Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs

NASA Astrophysics Data System (ADS)

Teshager, Awoke Dagnew; Gassman, Philip W.; Secchi, Silvia; Schoof, Justin T.; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Imbedding HACCP principles in dairy herd health and production management: case report on calf rearing

PubMed Central

2008-01-01

Driven by consumer demands, European legislation has suggested the use of HACCP (Hazard Analysis Critical Control Point) as the quality risk management programme for the whole dairy chain. Until now, an exception has been made for primary producers, but as regulations evolve, on-farm HACCP-like programmes should be ready to assure food safety as well as animal health and animal welfare. In our field experiment, the HACCP-concept was used to combine both optimal farm management and formalisation of quality assurance in an on-farm situation in the Netherlands. The process of young stock rearing was chosen, since its importance for the future of the farm is often underestimated. Hazards and their associated risk factors can be controlled within the farm-specific standards and tolerances, as targets can be controlled by corrective measures and by implementation of farm-specific worksheets. The veterinarian is pivotal for the facility-based HACCP team, since he/she has knowledge about on-farm risk assessment and relations between clinical pathology, feed and farm management. The HACCP concept in combination with veterinary herd health and production management programmes offers a promising approach to optimise on-farm production processes (i.e., young stock rearing) in addition to a structural approach for quality risk management on dairy farms. PMID:21851722

Imbedding HACCP principles in dairy herd health and production management: case report on calf rearing.

PubMed

Boersema, Jsc; Noordhuizen, Jptm; Vieira, A; Lievaart, Jj; Baumgartner, W

2008-09-01

Driven by consumer demands, European legislation has suggested the use of HACCP (Hazard Analysis Critical Control Point) as the quality risk management programme for the whole dairy chain. Until now, an exception has been made for primary producers, but as regulations evolve, on-farm HACCP-like programmes should be ready to assure food safety as well as animal health and animal welfare. In our field experiment, the HACCP-concept was used to combine both optimal farm management and formalisation of quality assurance in an on-farm situation in the Netherlands. The process of young stock rearing was chosen, since its importance for the future of the farm is often underestimated. Hazards and their associated risk factors can be controlled within the farm-specific standards and tolerances, as targets can be controlled by corrective measures and by implementation of farm-specific worksheets. The veterinarian is pivotal for the facility-based HACCP team, since he/she has knowledge about on-farm risk assessment and relations between clinical pathology, feed and farm management. The HACCP concept in combination with veterinary herd health and production management programmes offers a promising approach to optimise on-farm production processes (i.e., young stock rearing) in addition to a structural approach for quality risk management on dairy farms.

Array Effects in Large Wind Farms. Cooperative Research and Development Final Report, CRADA Number CRD-09-343

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moriarty, Patrick

2016-02-23

The effects of wind turbine wakes within operating wind farms have a substantial impact on the overall energy production from the farm. The current generation of models drastically underpredicts the impact of these wakes leading to non-conservative estimates of energy capture and financial losses to wind farm operators and developers. To improve these models, detailed research of operating wind farms is necessary. Rebecca Barthelmie of Indiana University is a world leader of wind farm wakes effects and would like to partner with NREL to help improve wind farm modeling by gathering additional wind farm data, develop better models and increasemore » collaboration with European researchers working in the same area. This is currently an active area of research at NREL and the capabilities of both parties should mesh nicely.« less

Lameness Prevalence and Risk Factors in Large Dairy Farms in Upstate New York. Model Development for the Prediction of Claw Horn Disruption Lesions

PubMed Central

Foditsch, Carla; Oikonomou, Georgios; Machado, Vinícius Silva; Bicalho, Marcela Luccas; Ganda, Erika Korzune; Lima, Svetlana Ferreira; Rossi, Rodolfo; Ribeiro, Bruno Leonardo; Kussler, Arieli; Bicalho, Rodrigo Carvalho

2016-01-01

The main objectives of this prospective cohort study were a) to describe lameness prevalence at drying off in large high producing New York State herds based on visual locomotion score (VLS) and identify potential cow and herd level risk factors, and b) to develop a model that will predict the probability of a cow developing claw horn disruption lesions (CHDL) in the subsequent lactation using cow level variables collected at drying off and/or available from farm management software. Data were collected from 23 large commercial dairy farms located in upstate New York. A total of 7,687 dry cows, that were less than 265 days in gestation, were enrolled in the study. Farms were visited between May 2012 and March 2013, and cows were assessed for body condition score (BCS) and VLS. Data on the CHDL events recorded by the farm employees were extracted from the Dairy-Comp 305 database, as well as information regarding the studied cows’ health events, milk production, and reproductive records throughout the previous and subsequent lactation period. Univariable analyses and mixed multivariable logistic regression models were used to analyse the data at the cow level. The overall average prevalence of lameness (VLS > 2) at drying off was 14%. Lactation group, previous CHDL, mature equivalent 305-d milk yield (ME305), season, BCS at drying off and sire PTA for strength were all significantly associated with lameness at the drying off (cow-level). Lameness at drying off was associated with CHDL incidence in the subsequent lactation, as well as lactation group, previous CHDL and ME305. These risk factors for CHDL in the subsequent lactation were included in our predictive model and adjusted predicted probabilities for CHDL were calculated for all studied cows. ROC analysis identified an optimum cut-off point for these probabilities and using this cut-off point we could predict CHDL incidence in the subsequent lactation with an overall specificity of 75% and sensitivity of 59%. Using this approach, we would have detected 33% of the studied population as being at risk, eventually identifying 59% of future CHDL cases. Our predictive model could help dairy producers focusing their efforts on CHDL reduction by implementing aggressive preventive measures for high risk cows. PMID:26795970

Risk factors for lameness in freestall-housed dairy cows across two breeds, farming systems, and countries.

PubMed

Dippel, S; Dolezal, M; Brenninkmeyer, C; Brinkmann, J; March, S; Knierim, U; Winckler, C

2009-11-01

Lameness poses a considerable problem in modern dairy farming. Several new developments (e.g., herd health plans) strive to help farmers improve the health and welfare of their herd. It was thus our aim to identify lameness risk factors common across regions, breeds, and farming systems for freestall-housed dairy cows. We analyzed data from 103 nonorganic and organic dairy farms in Germany and Austria that kept 24 to 145 Holstein Friesian or Fleckvieh cows in the milking herd (mean = 48). Data on housing, management, behavior, and lameness scores for a total of 3,514 cows were collected through direct observations and an interview. Mean lameness prevalence was 34% (range = 0-81%). Data were analyzed applying logistic regression with generalized estimating equations in a split-sample design. The final model contained 1 animal-based parameter and 3 risk factors related to lying as well as 1 nutritional animal-based parameter, while correcting for the significant confounders parity and data subset. Risk for lameness increased with decreasing lying comfort, that is, more frequent abnormal lying behavior, mats or mattresses used as a stall base compared with deep-bedded stall bases, the presence of head lunge impediments, or neck rail-curb diagonals that were too short. Cows in the lowest body condition quartile (1.25-2.50 for Holstein Friesian and 2.50-3.50 for Fleckvieh) had the highest risk of being lame. In cross-validation the model correctly classified 71 and 70% of observations in the model-building and validation samples, respectively. Only 2 out of 15 significant odds ratios (including contrasts) changed direction. They pertained to the 2 variables with the highest P-values in the model. In conclusion, lying comfort and nutrition are key risk areas for lameness in freestall-housed dairy cows. Abnormal lying behavior in particular proved to be a good predictor of lameness risk and should thus be included in on-farm protocols. The study is part of the European Commission's Welfare Quality project.

Agricultural work exposures and pulmonary function among hired farm workers in California (the MICASA study).

PubMed

Rodriquez, Erik J; Stoecklin-Marois, Maria T; Bennett, Deborah H; Tancredi, Daniel J; Schenker, Marc B

2014-01-01

Despite California's dependence on hired farm labor, scarce research has been conducted on the respiratory health of hired farm workers. Agricultural exposures to inorganic and organic dusts can adversely affect an individual's respiratory health and differ by farm type and job task. The purpose of the present analysis was to examine associations between agricultural work exposures and pulmonary function among 450 California farm workers. Data were collected as part of the Mexican Immigration to California: Agricultural Safety and Acculturation (MICASA) study, a prospective cohort study examining occupational risk factors and health of hired farm worker families in Mendota, California. Time-weighted self-reported average (TWSRA) dust scores were calculated from assessments of past-12-month agricultural work history. Other dust exposure indicator variables included months worked in agriculture in the past 12 months and years worked in agriculture. Multiple linear regression modeled FEV1 (forced expiratory volume in 1 second), FEF(25-75%) (forced midexpiratory flow rate), FVC (forced vital capacity), FEV6, FEV1/FVC, and FEV1/FEV6 separately. Seventy-six percent of participants had worked in agriculture in the past year. In models conducted for crops and tasks separately, high TWSRA dust score was associated with better FEV6. Crop and task models showed associations between greater months worked in agriculture in the past year and better FEV1, FEF(25-75%), and FEV6. Both models also found greater years worked in agriculture to be associated with worse FEV1/FEV6. Results were generally in the opposite direction as expected given past research but not uncommon. Future research should investigate relationships between pulmonary function and agricultural dust exposure over a lifetime and changes in pulmonary function over time.

Effect of dairy farming system, herd, season, parity, and days in milk on modeling of the coagulation, curd firming, and syneresis of bovine milk.

PubMed

Bittante, G; Cipolat-Gotet, C; Malchiodi, F; Sturaro, E; Tagliapietra, F; Schiavon, S; Cecchinato, A

2015-04-01

The objectives of this study were to characterize the variation in curd firmness model parameters obtained from coagulating bovine milk samples, and to investigate the effects of the dairy system, season, individual farm, and factors related to individual cows (days in milk and parity). Individual milk samples (n = 1,264) were collected during the evening milking of 85 farms representing different environments and farming systems in the northeastern Italian Alps. The dairy herds were classified into 4 farming system categories: traditional system with tied animals (29 herds), modern dairy systems with traditional feeding based on hay and compound feed (30 herds), modern dairy system with total mixed ration (TMR) that included silage as a large proportion of the diet (9 herds), and modern dairy system with silage-free TMR (17 herds). Milk samples were analyzed for milk composition and coagulation properties, and parameters were modeled using curd firmness measures (CFt) collected every 15 s from a lacto-dynamographic analysis of 90 min. When compared with traditional milk coagulation properties (MCP), the curd firming measures showed greater variability and yielded a more accurate description of the milk coagulation process: the model converged for 93.1% of the milk samples, allowing estimation of 4 CFt parameters and 2 derived traits [maximum CF (CF(max)) and time from rennet addition to CF(max) (t(max))] for each sample. The milk samples whose CFt equations did not converge showed longer rennet coagulation times obtained from the model (RCT(eq)) and higher somatic cell score, and came from less-productive cows. Among the sources of variation tested for the CFt parameters, dairy herd system yielded the greatest differences for the contrast between the traditional farm and the 3 modern farms, with the latter showing earlier coagulation and greater instant syneresis rate constant (k(SR)). The use of TMR yielded a greater tmax because of a higher instant curd-firming rate constant (k(CF)). Season of sampling was found to be very important, yielding higher values during winter for all traits except k(CF) and k(SR). All CFt traits were affected by individual cow factors. For parity, milk produced by first-lactation cows showed higher k(CF) and k(SR), but delays in achieving CF(max). With respect to stage of lactation, RCT(eq) and potential asymptotic CF increased during the middle of lactation and stabilized thereafter, whereas the 2 instant rate constants presented the opposite pattern, with the lowest (k(CF)) and highest (k(SR)) values occurring in mid lactation. The new challenge offered by prolonging the test interval and individual modeling of milk technological properties allowed us to study the effects of parameters related to the environment and to individual cows. This novel strategy may be useful for investigating the genetic variability of these new coagulation traits. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Minimization of bovine tuberculosis control costs in US dairy herds

PubMed Central

Smith, Rebecca L.; Tauer, Loren W.; Schukken, Ynte H.; Lu, Zhao; Grohn, Yrjo T.

2013-01-01

The objective of this study was to minimize the cost of controlling an isolated bovine tuberculosis (bTB) outbreak in a US dairy herd, using a stochastic simulation model of bTB with economic and biological layers. A model optimizer produced a control program that required 2-month testing intervals (TI) with 2 negative whole-herd tests to leave quarantine. This control program minimized both farm and government costs. In all cases, test-and-removal costs were lower than depopulation costs, although the variability in costs increased for farms with high holding costs or small herd sizes. Increasing herd size significantly increased costs for both the farm and the government, while increasing indemnity payments significantly decreased farm costs and increasing testing costs significantly increased government costs. Based on the results of this model, we recommend 2-month testing intervals for herds after an outbreak of bovine tuberculosis, with 2 negative whole herd tests being sufficient to lift quarantine. A prolonged test and cull program may cause a state to lose its bTB-free status during the testing period. When the cost of losing the bTB-free status is greater than $1.4 million then depopulation of farms could be preferred over a test and cull program. PMID:23953679

Agricultural Industry Advanced Vehicle Technology: Benchmark Study for Reduction in Petroleum Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roger Hoy

2014-09-01

Diesel use on farms in the United States has remained relatively constant since 1985, decreasing slightly in 2009, which may be attributed to price increases and the economic recession. During this time, the United States’ harvested area also has remained relatively constant at roughly 300 million acres. In 2010, farm diesel use was 5.4% of the total United States diesel use. Crops accounting for an estimated 65% of United States farm diesel use include corn, soybean, wheat, hay, and alfalfa, respectively, based on harvested crop area and a recent analysis of estimated fuel use by crop. Diesel use in thesemore » cropping systems primarily is from tillage, harvest, and various other operations (e.g., planting and spraying) (Figure 3). Diesel efficiency is markedly variable due to machinery types, conditions of operation (e.g., soil type and moisture), and operator variability. Farm diesel use per acre has slightly decreased in the last two decades and diesel is now estimated to be less than 5% of farm costs per acre. This report will explore current trends in increasing diesel efficiency in the farm sector. The report combines a survey of industry representatives, a review of literature, and data analysis to identify nascent technologies for increasing diesel efficiency« less

Farms, Families, and Markets: New Evidence on Completeness of Markets in Agricultural Settings

PubMed Central

LaFave, Daniel; Thomas, Duncan

2016-01-01

The farm household model has played a central role in improving the understanding of small-scale agricultural households and non-farm enterprises. Under the assumptions that all current and future markets exist and that farmers treat all prices as given, the model simplifies households’ simultaneous production and consumption decisions into a recursive form in which production can be treated as independent of preferences of household members. These assumptions, which are the foundation of a large literature in labor and development, have been tested and not rejected in several important studies including Benjamin (1992). Using multiple waves of longitudinal survey data from Central Java, Indonesia, this paper tests a key prediction of the recursive model: demand for farm labor is unrelated to the demographic composition of the farm household. The prediction is unambiguously rejected. The rejection cannot be explained by contamination due to unobserved heterogeneity that is fixed at the farm level, local area shocks or farm-specific shocks that affect changes in household composition and farm labor demand. We conclude that the recursive form of the farm household model is not consistent with the data. Developing empirically tractable models of farm households when markets are incomplete remains an important challenge. PMID:27688430

Development of a forecasting model for brucellosis spreading in the Italian cattle trade network aimed to prioritise the field interventions.

PubMed

Savini, L; Candeloro, L; Conte, A; De Massis, F; Giovannini, A

2017-01-01

Brucellosis caused by Brucella abortus is an important zoonosis that constitutes a serious hazard to public health. Prevention of human brucellosis depends on the control of the disease in animals. Livestock movement data represent a valuable source of information to understand the pattern of contacts between holdings, which may determine the inter-herds and intra-herd spread of the disease. The manuscript addresses the use of computational epidemic models rooted in the knowledge of cattle trade network to assess the probabilities of brucellosis spread and to design control strategies. Three different spread network-based models were proposed: the DFC (Disease Flow Centrality) model based only on temporal cattle network structure and unrelated to the epidemiological disease parameters; a deterministic SIR (Susceptible-Infectious-Recovered) model; a stochastic SEIR (Susceptible-Exposed-Infectious-Recovered) model in which epidemiological and demographic within-farm aspects were also modelled. Containment strategies based on farms centrality in the cattle network were tested and discussed. All three models started from the identification of the entire sub-network originated from an infected farm, up to the fifth order of contacts. Their performances were based on data collected in Sicily in the framework of the national eradication plan of brucellosis in 2009. Results show that the proposed methods improves the efficacy and efficiency of the tracing activities in comparison to the procedure currently adopted by the veterinary services in the brucellosis control, in Italy. An overall assessment shows that the SIR model is the most suitable for the practical needs of the veterinary services, being the one with the highest sensitivity and the shortest computation time.

Development of a forecasting model for brucellosis spreading in the Italian cattle trade network aimed to prioritise the field interventions

PubMed Central

Candeloro, L.; Conte, A.; De Massis, F.; Giovannini, A.

2017-01-01

Brucellosis caused by Brucella abortus is an important zoonosis that constitutes a serious hazard to public health. Prevention of human brucellosis depends on the control of the disease in animals. Livestock movement data represent a valuable source of information to understand the pattern of contacts between holdings, which may determine the inter-herds and intra-herd spread of the disease. The manuscript addresses the use of computational epidemic models rooted in the knowledge of cattle trade network to assess the probabilities of brucellosis spread and to design control strategies. Three different spread network-based models were proposed: the DFC (Disease Flow Centrality) model based only on temporal cattle network structure and unrelated to the epidemiological disease parameters; a deterministic SIR (Susceptible-Infectious-Recovered) model; a stochastic SEIR (Susceptible-Exposed-Infectious-Recovered) model in which epidemiological and demographic within-farm aspects were also modelled. Containment strategies based on farms centrality in the cattle network were tested and discussed. All three models started from the identification of the entire sub-network originated from an infected farm, up to the fifth order of contacts. Their performances were based on data collected in Sicily in the framework of the national eradication plan of brucellosis in 2009. Results show that the proposed methods improves the efficacy and efficiency of the tracing activities in comparison to the procedure currently adopted by the veterinary services in the brucellosis control, in Italy. An overall assessment shows that the SIR model is the most suitable for the practical needs of the veterinary services, being the one with the highest sensitivity and the shortest computation time. PMID:28654703

A Management Tool for Assessing Aquaculture Environmental Impacts in Chilean Patagonian Fjords: Integrating Hydrodynamic and Pellets Dispersion Models

NASA Astrophysics Data System (ADS)

Tironi, Antonio; Marin, Víctor H.; Campuzano, Francisco J.

2010-05-01

This article introduces a management tool for salmon farming, with a scope in the local sustainability of salmon aquaculture of the Aysen Fjord, Chilean Patagonia. Based on Integrated Coastal Zone Management (ICZM) principles, the tool combines a large 3-level nested hydrodynamic model, a particle tracking module and a GIS application into an assessment tool for particulate waste dispersal of salmon farming activities. The model offers an open source alternative to particulate waste modeling and evaluation, contributing with valuable information for local decision makers in the process of locating new facilities and monitoring stations.

Contribution of large scale coherence to wind turbine power: A large eddy simulation study in periodic wind farms

NASA Astrophysics Data System (ADS)

Chatterjee, Tanmoy; Peet, Yulia T.

2018-03-01

Length scales of eddies involved in the power generation of infinite wind farms are studied by analyzing the spectra of the turbulent flux of mean kinetic energy (MKE) from large eddy simulations (LES). Large-scale structures with an order of magnitude bigger than the turbine rotor diameter (D ) are shown to have substantial contribution to wind power. Varying dynamics in the intermediate scales (D -10 D ) are also observed from a parametric study involving interturbine distances and hub height of the turbines. Further insight about the eddies responsible for the power generation have been provided from the scaling analysis of two-dimensional premultiplied spectra of MKE flux. The LES code is developed in a high Reynolds number near-wall modeling framework, using an open-source spectral element code Nek5000, and the wind turbines have been modelled using a state-of-the-art actuator line model. The LES of infinite wind farms have been validated against the statistical results from the previous literature. The study is expected to improve our understanding of the complex multiscale dynamics in the domain of large wind farms and identify the length scales that contribute to the power. This information can be useful for design of wind farm layout and turbine placement that take advantage of the large-scale structures contributing to wind turbine power.

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt

PubMed Central

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-01-01

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations. PMID:27834862

Simulation of wind turbine wakes using the actuator line technique

PubMed Central

Sørensen, Jens N.; Mikkelsen, Robert F.; Henningson, Dan S.; Ivanell, Stefan; Sarmast, Sasan; Andersen, Søren J.

2015-01-01

The actuator line technique was introduced as a numerical tool to be employed in combination with large eddy simulations to enable the study of wakes and wake interaction in wind farms. The technique is today largely used for studying basic features of wakes as well as for making performance predictions of wind farms. In this paper, we give a short introduction to the wake problem and the actuator line methodology and present a study in which the technique is employed to determine the near-wake properties of wind turbines. The presented results include a comparison of experimental results of the wake characteristics of the flow around a three-bladed model wind turbine, the development of a simple analytical formula for determining the near-wake length behind a wind turbine and a detailed investigation of wake structures based on proper orthogonal decomposition analysis of numerically generated snapshots of the wake. PMID:25583862

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

Opportunities of energy supply of farm holdings on the basis of small-scale renewable energy sources

NASA Astrophysics Data System (ADS)

Efendiev, A. M.; Nikolaev, Yu. E.; Evstaf'ev, D. P.

2016-02-01

One of the major national economic problems of Russia is raising of agricultural production, which will provide strategic security and sustainable supply of the population with provisions. Creation of subsidiary small holdings, farm holdings, and peasant farm holdings will require addressing issues of energy supply. At considerable distance of small farms from centralized energy systems (by fuel, electricity and thermal energy) it is proposed to create a system of local energy networks on the basis of low-powered power plants using renewable energy sources (RES). There is economic unreasonableness of use of imported components of small power plants. Creation of new combined small power plants on renewable energy sources produced by domestic manufacturers is recommended. Schemes of arrangements of small power plants based on renewable energy sources are proposed, variants and characteristics of a basic source are provided—biogas plants developed by the authors. Calculations revealed that heat and power supply of self-contained farms distant from small power plants based on renewable energy sources is 2.5-2.6 times cheaper than from centralized networks. Production of biogas through anaerobic fermentation of organic waste of cattle complexes is considered as the basis. The analysis of biowaste output in various cattle farms is carried out, and the volume of biogas is determined to meet the requirements of these farms in electrical and thermal energy. The objective of the present article is to study the possibility of creating small combined power plants in Russia based on renewable sources of energy for independent consumers.

Analysis of the interaction among rice, weeds, inorganic fertilizer, and a herbivore in a composite farming paddy ecosystem.

PubMed

Wu, Zhaohua; Wang, Yi; Zhou, Xiaoli; Zhou, Tiejun

2018-06-01

As one of the Globally Important Agricultural Heritage Systems (GIAHS), rice field composite farming is an ecological measure in rice production, which can reduce the amount of chemical fertilizers, pesticides and herbicides. This research studies the interaction among rice, weed, inorganic fertilizer and herbivore in a composite farming paddy ecosystem. We develop a differential equation model to analyze the relations and interactions among those components. Results show the existence of an equilibrium for paddy and weed extinction, one or two equilibria for rice extinction, an equilibrium for weed extinction, and an equilibrium for rice and weed coexistence. Based on the obtained stability conditions of these equilibria, measures are proposed to avoid the existence or the stability of equilibria for rice extinction. Other measures are proposed to lead to a stable equilibrium for weed extinction, which is the most desirable result in rice production. Conditions for maximizing the yield of rice are also obtained by taking the relative mortality of rice as variable. In addition, we discover the existence of Hopf bifurcation phenomenon in the system, and develop the critical value of Hopf bifurcation by taking the artificial fertilizer rate as the bifurcation parameter. Our findings provide effective guidance and insights for rice production in a composite farming paddy ecosystem. Copyright © 2018 Elsevier Inc. All rights reserved.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management

NASA Astrophysics Data System (ADS)

Dalgaard, T.; Bienkowski, J. F.; Bleeker, A.; Dragosits, U.; Drouet, J. L.; Durand, P.; Frumau, A.; Hutchings, N. J.; Kedziora, A.; Magliulo, V.; Olesen, J. E.; Theobald, M. R.; Maury, O.; Akkal, N.; Cellier, P.

2012-12-01

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha-1 yr-1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha-1 yr-1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha-1 yr-1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007-2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998-2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25-50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

DOE PAGES

Annoni, Jennifer; Fleming, Paul; Scholbrock, Andrew; ...

2018-02-08

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operatedmore » at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.« less

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Annoni, Jennifer; Fleming, Paul; Scholbrock, Andrew

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operatedmore » at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.« less

Use of meteorological information in the risk analysis of a mixed wind farm and solar

NASA Astrophysics Data System (ADS)

Mengelkamp, H.-T.; Bendel, D.

2010-09-01

Use of meteorological information in the risk analysis of a mixed wind farm and solar power plant portfolio H.-T. Mengelkamp*,** , D. Bendel** *GKSS Research Center Geesthacht GmbH **anemos Gesellschaft für Umweltmeteorologie mbH The renewable energy industry has rapidly developed during the last two decades and so have the needs for high quality comprehensive meteorological services. It is, however, only recently that international financial institutions bundle wind farms and solar power plants and offer shares in these aggregate portfolios. The monetary value of a mixed wind farm and solar power plant portfolio is determined by legal and technical aspects, the expected annual energy production of each wind farm and solar power plant and the associated uncertainty of the energy yield estimation or the investment risk. Building an aggregate portfolio will reduce the overall uncertainty through diversification in contrast to the single wind farm/solar power plant energy yield uncertainty. This is similar to equity funds based on a variety of companies or products. Meteorological aspects contribute to the diversification in various ways. There is the uncertainty in the estimation of the expected long-term mean energy production of the wind and solar power plants. Different components of uncertainty have to be considered depending on whether the power plant is already in operation or in the planning phase. The uncertainty related to a wind farm in the planning phase comprises the methodology of the wind potential estimation and the uncertainty of the site specific wind turbine power curve as well as the uncertainty of the wind farm effect calculation. The uncertainty related to a solar power plant in the pre-operational phase comprises the uncertainty of the radiation data base and that of the performance curve. The long-term mean annual energy yield of operational wind farms and solar power plants is estimated on the basis of the actual energy production and it's relation to a climatologically stable long-term reference period. These components of uncertainty are of technical nature and based on subjective estimations rather than on a statistically sound data analysis. And then there is the temporal and spatial variability of the wind speed and radiation. Their influence on the overall risk is determined by the regional distribution of the power plants. These uncertainty components are calculated on the basis of wind speed observations and simulations and satellite derived radiation data. The respective volatility (temporal variability) is calculated from the site specific time series and the influence on the portfolio through regional correlation. For an exemplary portfolio comprising fourteen wind farms and eight solar power plants the annual mean energy production to be expected is calculated, the different components of uncertainty are estimated for each single wind farm and solar power plant and for the portfolio as a whole. The reduction in uncertainty (or risk) through bundling the wind farms and the solar power plants (the portfolio effect) is calculated by Markowitz' Modern Portfolio Theory. This theory is applied separately for the wind farm and the solar power plant bundle and for the combination of both. The combination of wind and photovoltaic assets clearly shows potential for a risk reduction. Even assets with a comparably low expected return can lead to a significant risk reduction depending on their individual characteristics.

The seroprevalence of Toxoplasma gondii in Ontario sheep flocks

PubMed Central

Waltner-Toews, David; Mondesire, Roy; Menzies, Paula

1991-01-01

In a random sample of 103 sheep farms in Ontario, 99% of the farms had some sheep serologically positive for Toxoplasma gondii, based on an enzymelinked immunosorbent assay (ELISA). The percent of sheep affected within farms ranged from 3.8% to 97.8%, with an average flock prevalence of 57.6%. When farm management variables were considered in a multivariate analysis, significantly lower rates of serologically positive sheep were associated with neutering of female cats and clipping of ewes' perineums before lambing; significantly higher prevalence rates were found on farms where sheep were purchased from other flocks, pigs were raised on the same farm, sheep shared pasture with other animals, flowing water was available at pasture, and pastured replacements had access to housing. As well, in univariate analyses, higher prevalence was positively associated with an increasing number of cat litters born over the previous two years and offering creep feed or forage to lambs, and inversely with the amount of labor expended on sheep rearing. PMID:17423914

Mycobacteria in Terrestrial Small Mammals on Cattle Farms in Tanzania

PubMed Central

Durnez, Lies; Katakweba, Abdul; Sadiki, Harrison; Katholi, Charles R.; Kazwala, Rudovick R.; Machang'u, Robert R.; Portaels, Françoise; Leirs, Herwig

2011-01-01

The control of bovine tuberculosis and atypical mycobacterioses in cattle in developing countries is important but difficult because of the existence of wildlife reservoirs. In cattle farms in Tanzania, mycobacteria were detected in 7.3% of 645 small mammals and in cow's milk. The cattle farms were divided into “reacting” and “nonreacting” farms, based on tuberculin tests, and more mycobacteria were present in insectivores collected in reacting farms as compared to nonreacting farms. More mycobacteria were also present in insectivores as compared to rodents. All mycobacteria detected by culture and PCR in the small mammals were atypical mycobacteria. Analysis of the presence of mycobacteria in relation to the reactor status of the cattle farms does not exclude transmission between small mammals and cattle but indicates that transmission to cattle from another source of infection is more likely. However, because of the high prevalence of mycobacteria in some small mammal species, these infected animals can pose a risk to humans, especially in areas with a high HIV-prevalence as is the case in Tanzania. PMID:21785686

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE PAGES

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

2017-10-02

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

The 'Real Welfare' scheme: benchmarking welfare outcomes for commercially farmed pigs.

PubMed

Pandolfi, F; Stoddart, K; Wainwright, N; Kyriazakis, I; Edwards, S A

2017-10-01

Animal welfare standards have been incorporated in EU legislation and in farm assurance schemes, based on scientific information and aiming to safeguard the welfare of the species concerned. Recently, emphasis has shifted from resource-based measures of welfare to animal-based measures, which are considered to assess more accurately the welfare status. The data used in this analysis were collected from April 2013 to May 2016 through the 'Real Welfare' scheme in order to assess on-farm pig welfare, as required for those finishing pigs under the UK Red Tractor Assurance scheme. The assessment involved five main measures (percentage of pigs requiring hospitalization, percentage of lame pigs, percentage of pigs with severe tail lesions, percentage of pigs with severe body marks and enrichment use ratio) and optional secondary measures (percentage of pigs with mild tail lesions, percentage of pigs with dirty tails, percentage of pigs with mild body marks, percentage of pigs with dirty bodies), with associated information about the environment and the enrichment in the farms. For the complete database, a sample of pens was assessed from 1928 farm units. Repeated measures were taken in the same farm unit over time, giving 112 240 records at pen level. These concerned a total of 13 480 289 pigs present on the farm during the assessments, with 5 463 348 pigs directly assessed using the 'Real Welfare' protocol. The three most common enrichment types were straw, chain and plastic objects. The main substrate was straw which was present in 67.9% of the farms. Compared with 2013, a significant increase of pens with undocked-tail pigs, substrates and objects was observed over time (P0.3). The results from the first 3 years of the scheme demonstrate a reduction of the prevalence of animal-based measures of welfare problems and highlight the value of this initiative.

Modelling the nitrogen loadings from large yellow croaker (Larimichthys crocea) cage aquaculture.

PubMed

Cai, Huiwen; Ross, Lindsay G; Telfer, Trevor C; Wu, Changwen; Zhu, Aiyi; Zhao, Sheng; Xu, Meiying

2016-04-01

Large yellow croaker (LYC) cage farming is a rapidly developing industry in the coastal areas of the East China Sea. However, little is known about the environmental nutrient loadings resulting from the current aquaculture practices for this species. In this study, a nitrogenous waste model was developed for LYC based on thermal growth and bioenergetic theories. The growth model produced a good fit with the measured data of the growth trajectory of the fish. The total, dissolved and particulate nitrogen outputs were estimated to be 133, 51 and 82 kg N tonne(-1) of fish production, respectively, with daily dissolved and particulate nitrogen outputs varying from 69 to 104 and 106 to 181 mg N fish(-1), respectively, during the 2012 operational cycle. Greater than 80 % of the nitrogen input from feed was predicted to be lost to the environment, resulting in low nitrogen retention (<20 %) in the fish tissues. Ammonia contributed the greatest proportion (>85 %) of the dissolved nitrogen generated from cage farming. This nitrogen loading assessment model is the first to address nitrogenous output from LYC farming and could be a valuable tool to examine the effects of management and feeding practices on waste from cage farming. The application of this model could help improve the scientific understanding of offshore fish farming systems. Furthermore, the model predicts that a 63 % reduction in nitrogenous waste production could be achieved by switching from the use of trash fish for feed to the use of pelleted feed.

Cross-sectional serosurvey of avian influenza antibodies presence in domestic ducks of Kathmandu, Nepal.

PubMed

Karki, S; Lupiani, B; Budke, C M; Manandhar, S; Ivanek, R

2014-09-01

Kathmandu, Nepal has been classified as a high-risk area for highly pathogenic avian influenza (HPAI) by the Nepali Government. While ducks have an important role in the transmission of avian influenza viruses (AIV), including HPAI, seroprevalence of antibodies to AIV in domestic ducks of Kathmandu has never been assessed. The objectives of this study were (i) to estimate the prevalence of seroconversion to AIV in domestic ducks in major duck-raising areas of Kathmandu and (ii) to assess the effect of age, sex, presence of swine and the number of ducks on the farm on the carriage of antibodies to AIV in these ducks. From April through July of 2011, a cross-sectional study was conducted and a total of 310 ducks in the major duck-raising areas of Kathmandu were sampled. The estimated prevalence of AIV antibodies was 27.2% [95% confidence interval (CI): 24.6-29.5]. Of 62 enrolled farms, 42% had at least one seropositive duck. Half of the enrolled farms also kept pigs of which 52% had at least one seropositive duck. Bivariate analysis indicated association between ducks' seroconversion to AIV and their age, sex and farm size. However, the final multivariable model, after controlling for clustering of ducks within farms, identified age as the only significant risk factor. Based on this model, ducks older than 1 year of age were more likely to be seropositive compared to ducks <6 months of age [odds ratio = 2.17 (1.07-4.39)]. These results provide baseline information about the AIV seroprevalence in domestic ducks in the major duck-raising areas of Kathmandu and identify a high-risk group that can be targeted in surveillance activities. Future studies should be conducted to differentiate the subtypes of AIV present among domestic ducks in Kathmandu, with particular interest in the presence of HPAI viruses. © 2014 Blackwell Verlag GmbH.

Toxoplasma gondii in sheep and goats: seroprevalence and potential risk factors under dairy husbandry practices.

PubMed

Tzanidakis, Nikolaos; Maksimov, Pavlo; Conraths, Franz J; Kiossis, Evaggelos; Brozos, Christos; Sotiraki, Smaragda; Schares, Gereon

2012-12-21

Sheep and goats are highly susceptible for infections with Toxoplasma gondii and may play a major role in the transmission of toxoplasmosis to humans. The aim of this study was to obtain up-to-date data on T. gondii infection in small ruminants and to identify putative risk factors in sheep and goats reared under dairy husbandry systems most commonly applied in Greece. To this end, ELISA tests were established for the examination of sheep and goat sera based on the use of TgSAG1, a major surface antigen of T. gondii tachyzoites. Serum samples from 2-4 years old small ruminants, 1501 from sheep and 541 from goats were examined. These samples had been collected on 69 farms in a mountainous and in a costal environment of Northern Greece from September 2008 to January 2009. In addition to farms containing only sheep (n=28) and farms containing only goats (n=9) also mixed farms with both animal species (n=32) were sampled. A standardized questionnaire was used to obtain information on putative risk factors. Sheep showed a higher seroprevalence (48.6% [729/1501]) for T. gondii than goats (30.7% [166/541]). Univariate multi-level modelling assuming random effects by the factor "farm" revealed that goats were statistically significantly less often seropositive than sheep (OR 0.475 [95% CI: 0.318-0.707]). No statistically significant regional differences in seroprevalence were observed. Risk factor analysis using univariate multi-level modelling revealed that sheep and goats that were kept under intensive (OR 4.30 [95% CI: 1.39-13.27]) or semi-intensive (OR 5.35 [95% CI: 2.33-12.28]) conditions had significantly higher odds of being seropositive. Further significant risk factors were "feeding concentrate" (OR 3.88 [95% CI: 1.81-8.29]) and providing "water from the public supply" (OR 1.67 [95% CI: 4.56-12.39]) to small ruminants. Copyright © 2012 Elsevier B.V. All rights reserved.

Molecular and Statistical Analysis of Campylobacter spp. and Antimicrobial-Resistant Campylobacter Carriage in Wildlife and Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S; Jardine, C M

2017-05-01

The objectives of this study were to (i) compare the carriage of Campylobacter and antimicrobial-resistant Campylobacter among livestock and mammalian wildlife on Ontario farms, and (ii) investigate the potential sharing of Campylobacter subtypes between livestock and wildlife. Using data collected from a cross-sectional study of 25 farms in 2010, we assessed associations, using mixed logistic regression models, between Campylobacter and antimicrobial-resistant Campylobacter carriage and the following explanatory variables: animal species (beef, dairy, swine, raccoon, other), farm type (swine, beef, dairy), type of sample (livestock or wildlife) and Campylobacter species (jejuni, coli, other). Models included a random effect to account for clustering by farm where samples were collected. Samples were subtyped using a Campylobacter-specific 40 gene comparative fingerprinting assay. A total of 92 livestock and 107 wildlife faecal samples were collected, and 72% and 27% tested positive for Campylobacter, respectively. Pooled faecal samples from livestock were significantly more likely to test positive for Campylobacter than wildlife samples. Relative to dairy cattle, pig samples were at significantly increased odds of testing positive for Campylobacter. The odds of isolating Campylobacter jejuni from beef cattle samples were significantly greater compared to dairy cattle and raccoon samples. Fifty unique subtypes of Campylobacter were identified, and only one subtype was found in both wildlife and livestock samples. Livestock Campylobacter isolates were significantly more likely to exhibit antimicrobial resistance (AMR) compared to wildlife Campylobacter isolates. Campylobacter jejuni was more likely to exhibit AMR when compared to C. coli. However, C. jejuni isolates were only resistant to tetracycline, and C.  coli isolates exhibited multidrug resistance patterns. Based on differences in prevalence of Campylobacter spp. and resistant Campylobacter between livestock and wildlife samples, and the lack of similarity in molecular subtypes and AMR patterns, we concluded that the sharing of Campylobacter species between livestock and mammalian wildlife was uncommon. © 2016 Blackwell Verlag GmbH.

Long-term effect of rice-based farming systems on soil health.

PubMed

Bihari, Priyanka; Nayak, A K; Gautam, Priyanka; Lal, B; Shahid, M; Raja, R; Tripathi, R; Bhattacharyya, P; Panda, B B; Mohanty, S; Rao, K S

2015-05-01

Integrated rice-fish culture, an age-old farming system, is a technology which could produce rice and fish sustainably at a time by optimizing scarce resource use through complementary use of land and water. An understanding of microbial processes is important for the management of farming systems as soil microbes are the living part of soil organic matter and play critical roles in soil C and N cycling and ecosystem functioning of farming system. Rice-based integrated farming system model for small and marginal farmers was established in 2001 at Central Rice Research Institute, Cuttack, Odisha. The different enterprises of farming system were rice-fish, fish-fingerlings, fruits, vegetables, rice-fish refuge, and agroforestry. This study was conducted with the objective to assess the soil physicochemical properties, microbial population, carbon and nitrogen fractions, soil enzymatic activity, and productivity of different enterprises. The effect of enterprises induced significant changes in the chemical composition and organic matter which in turn influenced the activities of enzymes (urease, acid, and alkaline phosphatase) involved in the C, N, and P cycles. The different enterprises of long-term rice-based farming system caused significant variations in nutrient content of soil, which was higher in rice-fish refuge followed by rice-fish enterprise. Highest microbial populations and enzymatic properties were recorded in rice-fish refuge system because of waterlogging and reduced condition prolonged in this system leading to less decomposition of organic matter. The maximum alkaline phosphatase, urease, and FDA were observed in rice-fish enterprise. However, highest acid phosphatase and dehydrogenase activity were obtained in vegetable enterprise and fish-fingerlings enterprise, respectively.

Social environments, risk-taking and injury in farm adolescents.

PubMed

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-12-01

Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. In a nationally representative sample of young Canadians aged 11-15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Farm Business Management Analysis: Adjusting the Farm Business to Increase Profit. Unit III. Volume 15, Number 3. Instructor's Guide.

ERIC Educational Resources Information Center

Denker, Robert; And Others

Designed primarily for Missouri vocational agricultural instructors participating in the Farm Business Management Analysis Program, this instructor's guide, consisting of 10 lessons, deals with adjusting a farm business to increase profits. The following topics are covered in the individual lessons: law and the farm family, planning income tax…

Longitudinal study on the temporal and micro-spatial distribution of Galba truncatula in four farms in Belgium as a base for small-scale risk mapping of Fasciola hepatica.

PubMed

Charlier, Johannes; Soenen, Karen; De Roeck, Els; Hantson, Wouter; Ducheyne, Els; Van Coillie, Frieke; De Wulf, Robert; Hendrickx, Guy; Vercruysse, Jozef

2014-11-26

The trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step forward to this respect. The aim of this study was to conduct a longitudinal field survey in Flanders (Belgium) to (i) characterise suitable small water bodies (SWB) for Galba truncatula and (ii) describe the population dynamics of G. truncatula. Four F. hepatica-infected farms from two distinct agricultural regions were examined for the abundance of G. truncatula from the beginning (April 2012) until the end (November 2012) of the grazing season. Per farm, 12 to 18 SWB were selected for monthly examination, using a 10 m transect analysis. Observations on G. truncatula abundance were coupled with meteorological and (micro-)environmental factors and the within-herd prevalence of F. hepatica using simple comparison or negative binomial regression models. A total of 54 examined SWB were classified as a pond, ditch, trench, furrow or moist area. G. truncatula abundance was significantly associated with SWB-type, region and total monthly precipitation, but not with monthly temperature. The clear differences in G. truncatula abundance between the 2 studied regions did not result in comparable differences in F. hepatica prevalence in the cattle. Exploration of the relationship of G. truncatula abundance with (micro)-environmental variables revealed a positive association with soil and water pH and the occurrence of Ranunculus sp. and a negative association with mowed pastures, water temperature and presence of reed-like plant species. Farm-level predictions of G. truncatula risk and subsequent risk for F. hepatica occurrence would require a rainfall, soil type (representing the agricultural region) and SWB layer in a geographic information system. While rainfall and soil type information is easily accessible, the recent advances in very high spatial resolution cameras carried on board of satellites, planes or drones should allow the delineation of SWBs in the future.

Integrated Food-Energy Systems: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Gerst, M.; Cox, M. E.; Locke, K. A.; Laser, M.; Raker, M.; Gooch, C.; Kapuscinski, A. R.

2015-12-01

Predominant forms of food and energy systems pose multiple challenges to the environment as current configurations tend to be structured around centralized one-way through-put of materials and energy. One proposed form of system transformation involves locally integrating "unclosed" material and energy loops from food and energy systems. Such systems, which have been termed integrated food-energy systems (IFES), have existed in diverse niche forms but have not been systematically studied with respect to technological, governance, and environmental differences. This is likely because IFES can have widely different configurations, from co-located renewable energy production on cropland to agroforestry. As a first step in creating a synthesis of IFES, our research team constructed a taxonomy using exploratory data analysis of diverse IFES cases (Gerst et al., 2015, ES&T 49:734-741). It was found that IFES may be categorized by type of primary product produced (plant- or animal-based food or energy) and the degree and direction of vertical supply chain coordination. To further explore these implications, we have begun a study of a highly-coordinated, animal-driven IFES: dairy farms with biogas production from anaerobic digestion of manure. The objectives of the research are to understand the barriers to adoption and the potential benefits to the farms financial resilience and to the environment. To address these objectives, we are interviewing 50 farms across New York and Vermont, collecting information on farmer decision-making and farm operation. These results will be used to calibrate biophysical and economic models of the farm in order understand the future conditions under which adoption of an IFES is beneficial.

Feeding behavior improves prediction of dairy cow voluntary feed intake but cannot serve as the sole indicator.

PubMed

Halachmi, I; Ben Meir, Y; Miron, J; Maltz, E

2016-09-01

Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows' voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: 'BW,' 'milk yield' and 'days in milking' parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake (R 2=0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.

Environmental performances of Sardinian dairy sheep production systems at different input levels.

PubMed

Vagnoni, E; Franca, A; Breedveld, L; Porqueddu, C; Ferrara, R; Duce, P

2015-01-01

Although sheep milk production is a significant sector for the European Mediterranean countries, it shows serious competitiveness gaps. Minimizing the ecological impacts of dairy sheep farming systems could represent a key factor for farmers to bridging the gaps in competitiveness of such systems and also obtaining public incentives. However, scarce is the knowledge about the environmental performance of Mediterranean dairy sheep farms. The main objectives of this paper were (i) to compare the environmental impacts of sheep milk production from three dairy farms in Sardinia (Italy), characterized by different input levels, and (ii) to identify the hotspots for improving the environmental performances of each farm, by using a Life Cycle Assessment (LCA) approach. The LCA was conducted using two different assessment methods: Carbon Footprint-IPCC and ReCiPe end-point. The analysis, conducted "from cradle to gate", was based on the functional unit 1 kg of Fat and Protein Corrected Milk (FPCM). The observed trends of the environmental performances of the studied farming systems were similar for both evaluation methods. The GHG emissions revealed a little range of variation (from 2.0 to 2.3 kg CO2-eq per kg of FPCM) with differences between farming systems being not significant. The ReCiPe end-point analysis showed a larger range of values and environmental performances of the low-input farm were significantly different compared to the medium- and high-input farms. In general, enteric methane emissions, field operations, electricity and production of agricultural machineries were the most relevant processes in determining the overall environmental performances of farms. Future research will be dedicated to (i) explore and better define the environmental implications of the land use impact category in the Mediterranean sheep farming systems, and (ii) contribute to revising and improving the existing LCA dataset for Mediterranean farming systems. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of cephalonium alone and in combination with an internal teat sealant for dry cow therapy in seasonally calving dairy cows.

PubMed

Bates, A J; Chambers, G; Laven, R A

2016-03-01

To assess the effect of combining an internal teat sealant (ITS) and a long-acting cephalonium-based dry cow therapy (DCT) on the prevalence of cows with a somatic cell count (SCC) >150,000 cells/mL 60-80 days after calving, and the incidence of clinical mastitis diagnosed by farm staff in the first 100 days after calving. Cows from a spring-calving, pasture-based, dairy farm in the South Canterbury region of New Zealand were randomly allocated to receive cephalonium DCT (n=289) or cephalonium and internal teat sealant (n=304) at the end of lactation. Cows were inspected twice daily by farm staff during the dry period and following calving for signs of mastitis. Individual SCC were determined from herd tests conducted in the previous lactation and following calving. Logistic regression models were used to determine relationships with the prevalence of cows with a SCC >150,000 cells/mL after calving, and survival analysis was used to model time to the first case of clinical mastitis following calving at the cow and quarter level. The OR for a cow with a SCC >150,000 cells/mL after calving, including age and individual SCC in the preceding lactation in the model, was 0.53 (95% CI=0.32-0.89) for cows treated with combination therapy compared to cows receiving cephalonium (p=0.017). At the cow level, including age and preceding SCC in the model, the hazard ratio for diagnosis of clinical mastitis by farm staff in the first 100 days of lactation was 0.60 (95% CI=0.39-0.98) for cows treated with combination therapy compared to cows receiving cephalonium (p=0.04). At the quarter level, the hazard ratio for diagnosis of clinical mastitis, with age included in the model, was 0.41 (95% CI=0.23-0.74) for the combination therapy compared to cephalonium alone (p<0.001). The combination of internal teat sealant and cephalonium DCT was more effective than cephalonium alone at reducing clinical mastitis diagnosed by farm staff in the 100 days after calving, and the prevalence of cows with a SCC >150,000 cells/mL 60-80 days after calving. This study adds to the evidence that the prevention of intra mammary infections throughout the dry period and up to calving by using combination therapy is important in reducing the incidence of farmer-diagnosed clinical mastitis and prevalence of cows with a SCC >150,000 cells/mL 60-80 days after calving.

Lighting and marking policies are associated with reduced farm equipment-related crash rates: a policy analysis of nine Midwestern US states

PubMed Central

Ramirez, Marizen; Bedford, Ronald; Wu, Hongqian; Harland, Karisa; Cavanaugh, Joseph E; Peek-Asa, Corinne

2016-01-01

Objective To evaluate the effectiveness of roadway policies for lighting and marking of farm equipment in reducing crashes in Illinois, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota and Wisconsin. Methods In this ecological study, state policies on lighting and marking of farm equipment were scored for compliance with standards of the American Society of Agricultural and Biological Engineers (ASABE). Using generalized estimating equations negative binomial models, we estimated the relationships between lighting and marking scores, and farm equipment crash rates, per 100 000 farm operations. Results A total of 7083 crashes involving farm equipment was reported from 2005 to 2010 in the Upper Midwest and Great Plains. As the state lighting and marking score increased by 5 units, crash rates reduced by 17% (rate ratio=0.83; 95% CI 0.78 to 0.88). Lighting-only (rate ratio=0.48; 95% CI 0.45 to 0.51) and marking-only policies (rate ratio=0.89; 95% CI 0.83 to 0.96) were each associated with reduced crash rates. Conclusions Aligning lighting and marking policies with ASABE standards may effectively reduce crash rates involving farm equipment. PMID:27405602

Risk factors for highly pathogenic avian influenza in commercial layer chicken farms in bangladesh during 2011.

PubMed

Osmani, M G; Thornton, R N; Dhand, N K; Hoque, M A; Milon, Sk M A; Kalam, M A; Hossain, M; Yamage, M

2014-12-01

A case-control study conducted during 2011 involved 90 randomly selected commercial layer farms infected with highly pathogenic avian influenza type A subtype H5N1 (HPAI) and 175 control farms randomly selected from within 5 km of infected farms. A questionnaire was designed to obtain information about potential risk factors for contracting HPAI and was administered to farm owners or managers. Logistic regression analyses were conducted to identify significant risk factors. A total of 20 of 43 risk factors for contracting HPAI were identified after univariable logistic regression analysis. A multivariable logistic regression model was derived by forward stepwise selection. Both unmatched and matched analyses were performed. The key risk factors identified were numbers of staff, frequency of veterinary visits, presence of village chickens roaming on the farm and staff trading birds. Aggregating these findings with those from other studies resulted in a list of 16 key risk factors identified in Bangladesh. Most of these related to biosecurity. It is considered feasible for Bangladesh to achieve a very low incidence of HPAI. Using the cumulative list of risk factors to enhance biosecurity pertaining to commercial farms would facilitate this objective. © 2013 Blackwell Verlag GmbH.

DairyWise, a whole-farm dairy model.

PubMed

Schils, R L M; de Haan, M H A; Hemmer, J G A; van den Pol-van Dasselaar, A; de Boer, J A; Evers, A G; Holshof, G; van Middelkoop, J C; Zom, R L G

2007-11-01

A whole-farm dairy model was developed and evaluated. The DairyWise model is an empirical model that simulated technical, environmental, and financial processes on a dairy farm. The central component is the FeedSupply model that balanced the herd requirements, as generated by the DairyHerd model, and the supply of homegrown feeds, as generated by the crop models for grassland and corn silage. The output of the FeedSupply model was used as input for several technical, environmental, and economic submodels. The submodels simulated a range of farm aspects such as nitrogen and phosphorus cycling, nitrate leaching, ammonia emissions, greenhouse gas emissions, energy use, and a financial farm budget. The final output was a farm plan describing all material and nutrient flows and the consequences on the environment and economy. Evaluation of DairyWise was performed with 2 data sets consisting of 29 dairy farms. The evaluation showed that DairyWise was able to simulate gross margin, concentrate intake, nitrogen surplus, nitrate concentration in ground water, and crop yields. The variance accounted for ranged from 37 to 84%, and the mean differences between modeled and observed values varied between -5 to +3% per set of farms. We conclude that DairyWise is a powerful tool for integrated scenario development and evaluation for scientists, policy makers, extension workers, teachers and farmers.

Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

PubMed

Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

2016-09-01

Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.

County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987–2006

USGS Publications Warehouse

Gronberg, Jo Ann M.; Spahr, Norman E.

2012-01-01

The U.S. Geological Survey’s National Water-Quality Assessment program requires nutrient input for analysis of the national and regional assessment of water quality. Detailed information on nutrient inputs to the environment are needed to understand and address the many serious problems that arise from excess nutrients in the streams and groundwater of the Nation. This report updates estimated county-level farm and nonfarm nitrogen and phosphorus input from commercial fertilizer sales for the conterminous United States for 1987 through 2006. Estimates were calculated from the Association of American Plant Food Control Officials fertilizer sales data, Census of Agriculture fertilizer expenditures, and U.S. Census Bureau county population. A previous national approach for deriving farm and nonfarm fertilizer nutrient estimates was evaluated, and a revised method for selecting representative states to calculate national farm and nonfarm proportions was developed. A national approach was used to estimate farm and nonfarm fertilizer inputs because not all states distinguish between farm and nonfarm use, and the quality of fertilizer reporting varies from year to year. For states that distinguish between farm and nonfarm use, the spatial distribution of the ratios of nonfarm-to-total fertilizer estimates for nitrogen and phosphorus calculated using the national-based farm and nonfarm proportions were similar to the spatial distribution of the ratios generated using state-based farm and nonfarm proportions. In addition, the relative highs and lows in the temporal distribution of farm and nonfarm nitrogen and phosphorus input at the state level were maintained—the periods of high and low usage coincide between national- and state-based values. With a few exceptions, nonfarm nitrogen estimates were found to be reasonable when compared to the amounts that would result if the lawn application rates recommended by state and university agricultural agencies were used. Also, states with higher nonfarm-to-total fertilizer ratios for nitrogen and phosphorus tended to have higher urban land-use percentages.

Data-Mining-Based Intelligent Differential Relaying for Transmission Lines Including UPFC and Wind Farms.

PubMed

Jena, Manas Kumar; Samantaray, Subhransu Ranjan

2016-01-01

This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.

Herd factors associated with dairy cow mortality.

PubMed

McConnel, C; Lombard, J; Wagner, B; Kopral, C; Garry, F

2015-08-01

Summary studies of dairy cow removal indicate increasing levels of mortality over the past several decades. This poses a serious problem for the US dairy industry. The objective of this project was to evaluate associations between facilities, herd management practices, disease occurrence and death rates on US dairy operations through an analysis of the National Animal Health Monitoring System's Dairy 2007 survey. The survey included farms in 17 states that represented 79.5% of US dairy operations and 82.5% of the US dairy cow population. During the first phase of the study operations were randomly selected from a sampling list maintained by the National Agricultural Statistics Service. Only farms that participated in phase I and had 30 or more dairy cows were eligible to participate in phase II. In total, 459 farms had complete data for all selected variables and were included in this analysis. Univariable associations between dairy cow mortality and 162 a priori identified operation-level management practices or characteristics were evaluated. Sixty of the 162 management factors explored in the univariate analysis met initial screening criteria and were further evaluated in a multivariable model exploring more complex relationships. The final weighted, negative binomial regression model included six variables. Based on the incidence rate ratio, this model predicted 32.0% less mortality for operations that vaccinated heifers for at least one of the following: bovine viral diarrhea, infectious bovine rhinotracheitis, parainfluenza 3, bovine respiratory syncytial virus, Haemophilus somnus, leptospirosis, Salmonella, Escherichia coli or clostridia. The final multivariable model also predicted a 27.0% increase in mortality for operations from which a bulk tank milk sample tested ELISA positive for bovine leukosis virus. Additionally, an 18.0% higher mortality was predicted for operations that used necropsies to determine the cause of death for some proportion of dead dairy cows. The final model also predicted that increased proportions of dairy cows with clinical mastitis and infertility problems were associated with increased mortality. Finally, an increase in mortality was predicted to be associated with an increase in the proportion of lame or injured permanently removed dairy cows. In general terms, this model identified that mortality was associated with reproductive problems, non-infectious postpartum disease, infectious disease and infectious disease prevention, and information derived from postmortem evaluations. Ultimately, addressing excessive mortality levels requires a concerted effort that recognizes and appropriately manages the numerous and diverse underlying risks.

Herd size and bovine tuberculosis persistence in cattle farms in Great Britain.

PubMed

Brooks-Pollock, Ellen; Keeling, Matt

2009-12-01

Bovine tuberculosis (bTB) infection in cattle is one of the most complex and persistent problems faced by the cattle industry in Great Britain today. While a number of factors have been identified as increasing the risk of infection, there has been little analysis on the causes of persistent infection within farms. In this article, we use the Cattle Tracing System to examine changes in herd size and VetNet data to correlate herd size with clearance of bTB. We find that the number of active farms fell by 16.3% between 2002 and 2007. The average farm size increased by 17.9% between 2002 and 2005. Using a measure similar to the Critical Community Size, the VetNet data reveal that herd size is positively correlated with disease persistence. Since economic policy and subsidies have been shown to influence farm size, we used a simple financial model for ideal farm size which includes disease burden to conclude that increasing herd size for efficiency gains may contribute to increased disease incidence.

British Columbia's fish health regulatory framework's contribution to sustainability goals related to salmon aquaculture.

PubMed

Stephen, Craig; Dicicco, Emiliano; Munk, Brandon

2008-12-01

Salmon farming is a significant contribution to the global seafood market to which the goal of sustainability is often applied. Diseases related to farms are perhaps the most contentious issues associated with sustainable salmon farming. We reviewed literature and policies in British Columbia, Canada, as well as interviewed key informants to examine how fish health regulations do or could support sustainability goals. We found four main obstacles to the development and application of a sustainability-based health management system. First, salmon farming faced the same challenges as other industries when trying to establish an operational definition of sustainability that captures all stakeholders' interests. Second, there was no program responsible for integrating the various regulations, responsible departments, and monitoring efforts to develop a comprehensive view of sustainability. Third, there was inadequate research base and social consensus on the criteria that should be used to track health outcomes for sustainability purposes. Fourth, the regulatory and management paradigm for salmon farming has been focused on diseases and pathogens as opposed to embracing a more inclusive health promotion model that includes biotic, abiotic, and social determinants of health. A transparent and inclusive participatory process that effectively links expert views with community and industry concerns should serve as the foundation for the next generation of health management regulations for salmon farming.

Research on Collection System Optimal Design of Wind Farm with Obstacles

NASA Astrophysics Data System (ADS)

Huang, W.; Yan, B. Y.; Tan, R. S.; Liu, L. F.

2017-05-01

To the collection system optimal design of offshore wind farm, the factors considered are not only the reasonable configuration of the cable and switch, but also the influence of the obstacles on the topology design of the offshore wind farm. This paper presents a concrete topology optimization algorithm with obstacles. The minimal area rectangle encasing box of the obstacle is obtained by using the method of minimal area encasing box. Then the optimization algorithm combining the advantages of Dijkstra algorithm and Prim algorithm is used to gain the scheme of avoidance obstacle path planning. Finally a fuzzy comprehensive evaluation model based on the analytic hierarchy process is constructed to compare the performance of the different topologies. Case studies demonstrate the feasibility of the proposed algorithm and model.

A novel iterative mixed model to remap three complex orthopedic traits in dogs

PubMed Central

Huang, Meng; Hayward, Jessica J.; Corey, Elizabeth; Garrison, Susan J.; Wagner, Gabriela R.; Krotscheck, Ursula; Hayashi, Kei; Schweitzer, Peter A.; Lust, George; Boyko, Adam R.; Todhunter, Rory J.

2017-01-01

Hip dysplasia (HD), elbow dysplasia (ED), and rupture of the cranial (anterior) cruciate ligament (RCCL) are the most common complex orthopedic traits of dogs and all result in debilitating osteoarthritis. We reanalyzed previously reported data: the Norberg angle (a quantitative measure of HD) in 921 dogs, ED in 113 cases and 633 controls, and RCCL in 271 cases and 399 controls and their genotypes at ~185,000 single nucleotide polymorphisms. A novel fixed and random model with a circulating probability unification (FarmCPU) function, with marker-based principal components and a kinship matrix to correct for population stratification, was used. A Bonferroni correction at p<0.01 resulted in a P< 6.96 ×10−8. Six loci were identified; three for HD and three for RCCL. An associated locus at CFA28:34,369,342 for HD was described previously in the same dogs using a conventional mixed model. No loci were identified for RCCL in the previous report but the two loci for ED in the previous report did not reach genome-wide significance using the FarmCPU model. These results were supported by simulation which demonstrated that the FarmCPU held no power advantage over the linear mixed model for the ED sample but provided additional power for the HD and RCCL samples. Candidate genes for HD and RCCL are discussed. When using FarmCPU software, we recommend a resampling test, that a positive control be used to determine the optimum pseudo quantitative trait nucleotide-based covariate structure of the model, and a negative control be used consisting of permutation testing and the identical resampling test as for the non-permuted phenotypes. PMID:28614352

IBSEM: An Individual-Based Atlantic Salmon Population Model

PubMed Central

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A.

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

Technical- and environmental-efficiency analysis of irrigated cotton-cropping systems in Punjab, Pakistan using data envelopment analysis.

PubMed

Ullah, Asmat; Perret, Sylvain R

2014-08-01

Cotton cropping in Pakistan uses substantial quantities of resources and adversely affects the environment with pollutants from the inputs, particularly pesticides. A question remains regarding to what extent the reduction of such environmental impact is possible without compromising the farmers' income. This paper investigates the environmental, technical, and economic performances of selected irrigated cotton-cropping systems in Punjab to quantify the sustainability of cotton farming and reveal options for improvement. Using mostly primary data, our study quantifies the technical, cost, and environmental efficiencies of different farm sizes. A set of indicators has been computed to reflect these three domains of efficiency using the data envelopment analysis technique. The results indicate that farmers are broadly environmentally inefficient; which primarily results from poor technical inefficiency. Based on an improved input mix, the average potential environmental impact reduction for small, medium, and large farms is 9, 13, and 11 %, respectively, without compromising the economic return. Moreover, the differences in technical, cost, and environmental efficiencies between small and medium and small and large farm sizes were statistically significant. The second-stage regression analysis identifies that the entire farm size significantly affects the efficiencies, whereas exposure to extension and training has positive effects, and the sowing methods significantly affect the technical and environmental efficiencies. Paradoxically, the formal education level is determined to affect the efficiencies negatively. This paper discusses policy interventions that can improve the technical efficiency to ultimately increase the environmental efficiency and reduce the farmers' operating costs.

From Invention to Innovation: Risk Analysis to Integrate One Health Technology in the Dairy Farm

PubMed Central

Lombardo, Andrea; Boselli, Carlo; Amatiste, Simonetta; Ninci, Simone; Frazzoli, Chiara; Dragone, Roberto; De Rossi, Alberto; Grasso, Gerardo; Mantovani, Alberto; Brajon, Giovanni

2017-01-01

Current Hazard Analysis Critical Control Points (HACCP) approaches mainly fit for food industry, while their application in primary food production is still rudimentary. The European food safety framework calls for science-based support to the primary producers’ mandate for legal, scientific, and ethical responsibility in food supply. The multidisciplinary and interdisciplinary project ALERT pivots on the development of the technological invention (BEST platform) and application of its measurable (bio)markers—as well as scientific advances in risk analysis—at strategic points of the milk chain for time and cost-effective early identification of unwanted and/or unexpected events of both microbiological and toxicological nature. Health-oriented innovation is complex and subject to multiple variables. Through field activities in a dairy farm in central Italy, we explored individual components of the dairy farm system to overcome concrete challenges for the application of translational science in real life and (veterinary) public health. Based on an HACCP-like approach in animal production, the farm characterization focused on points of particular attention (POPAs) and critical control points to draw a farm management decision tree under the One Health view (environment, animal health, food safety). The analysis was based on the integrated use of checklists (environment; agricultural and zootechnical practices; animal health and welfare) and laboratory analyses of well water, feed and silage, individual fecal samples, and bulk milk. The understanding of complex systems is a condition to accomplish true innovation through new technologies. BEST is a detection and monitoring system in support of production security, quality and safety: a grid of its (bio)markers can find direct application in critical points for early identification of potential hazards or anomalies. The HACCP-like self-monitoring in primary production is feasible, as well as the biomonitoring of live food producing animals as sentinel population for One Health. PMID:29218304

Odour assessment in the vicinity of a pig-fatting farm using field inspections (EN 16841-1) and dispersion modelling

NASA Astrophysics Data System (ADS)

Oettl, Dietmar; Kropsch, Michael; Mandl, Michael

2018-05-01

The assessment of odour annoyance varies vastly among countries even within the European Union. Using so-called odour-hour frequencies offers the distinct possibility for either applying dispersion models or field inspections, both generally assumed to be equivalent. In this study, odour-hours based on field inspections according to the European standard EN 16841-1 (2017) in the vicinity of a pig-fattening farm have been compared with modelled ones using the Lagrangian particle model GRAL, which uses odour-concentration variances for computing odour hours as recently proposed by Oettl and Ferrero (2017). Using a threshold of 1 ou m-3 (ou = odour units) for triggering odour hours in the model, as prescribed by the German guideline for odour assessment, led to reasonable agreements between the two different methodologies. It is pointed out that the individual odour sensitivity of qualified panel members, who carry out field inspections, is of crucial importance for selecting a proper odour-hour model. Statistical analysis of a large number of data stemming from dynamic olfactometry (EN 13725, 2003), that cover a wide range of odorants, suggests that the prescribed method in Germany for modelling odour hours may likely result in an overestimation, and hence, equivalence with field inspections is not given. The dataset is freely available on request.

A Comparative Study on Physicochemical Characteristics of Raw Goat Milk Collected from Different Farms in Malaysia.

PubMed

Jaafar, Syarifah Hazirah Syd; Hashim, Roshada; Hassan, Zaiton; Arifin, Norlelawati

2018-03-01

This study was conducted to determine the physical and chemical composition of goat milk produced by eight local farms located in the central region of Malaysia. Farms 1 to 4 (F1-SC, F2-SP, F3-SP, F4-SBC) reared Saanen-type goats while farms 5 to 8 (F5-JK, F6-JPEC, F7-JTC, F8-JC), Jamnapari-type goats. The common feedstuffs used in all farms comprised of fresh or silage from Napier grass, feed pellets, and brans while two farms, F5-JK and F6-JPEC supplemented the feeds with soybean-based product. The total solid content, dry matter, and proximate composition of goat milk and feedstuffs from the different farms were determined and the results analysed using principal component analysis. Total solid content of goat milk from the Jamnapari crossbreed had the highest solid content ranging from 11.81% to 17.54% compared to milk from farms with Saanen and Saanen crossbreed (10.95% to 14.63%). Jamnapari-type goats from F5-JK, F6-JPEC, and F8-JC had significantly higher ( p < 0.05) milk fat and protein contents (7.36%, 7.14%, and 6.59% fat; 5.08%, 6.19%, and 4.23% protein, respectively) than milk from other farms but, milk produced by Saanen-type goats from F4-SBC contained similar protein content (4.34%) to that from F8-JC. Total ash and carbohydrate contents in milk ranged between 0.67% to 0.86% and 3.26% to 4.71%, respectively, regardless of goat breed. Feeding soybean-based products appear to have a positive influence on milk fat and protein content in Jamnaparitype goats.

A Comparative Study on Physicochemical Characteristics of Raw Goat Milk Collected from Different Farms in Malaysia

PubMed Central

Jaafar, Syarifah Hazirah Syd; Hashim, Roshada; Hassan, Zaiton; Arifin, Norlelawati

2018-01-01

This study was conducted to determine the physical and chemical composition of goat milk produced by eight local farms located in the central region of Malaysia. Farms 1 to 4 (F1-SC, F2-SP, F3-SP, F4-SBC) reared Saanen-type goats while farms 5 to 8 (F5-JK, F6-JPEC, F7-JTC, F8-JC), Jamnapari-type goats. The common feedstuffs used in all farms comprised of fresh or silage from Napier grass, feed pellets, and brans while two farms, F5-JK and F6-JPEC supplemented the feeds with soybean-based product. The total solid content, dry matter, and proximate composition of goat milk and feedstuffs from the different farms were determined and the results analysed using principal component analysis. Total solid content of goat milk from the Jamnapari crossbreed had the highest solid content ranging from 11.81% to 17.54% compared to milk from farms with Saanen and Saanen crossbreed (10.95% to 14.63%). Jamnapari-type goats from F5-JK, F6-JPEC, and F8-JC had significantly higher (p < 0.05) milk fat and protein contents (7.36%, 7.14%, and 6.59% fat; 5.08%, 6.19%, and 4.23% protein, respectively) than milk from other farms but, milk produced by Saanen-type goats from F4-SBC contained similar protein content (4.34%) to that from F8-JC. Total ash and carbohydrate contents in milk ranged between 0.67% to 0.86% and 3.26% to 4.71%, respectively, regardless of goat breed. Feeding soybean-based products appear to have a positive influence on milk fat and protein content in Jamnaparitype goats. PMID:29644024

Genetic characterization of a betanodavirus isolated from a clinical disease outbreak in farm-raised tilapia Oreochromis niloticus (L.) in Thailand.

PubMed

Keawcharoen, J; Techangamsuwan, S; Ponpornpisit, A; Lombardini, E D; Patchimasiri, T; Pirarat, N

2015-01-01

Betanodavirus infection was diagnosed in larvae of farm-raised tilapia Oreochromis niloticus (L.), in central Thailand. Extensive vacuolar degeneration and neuronal necrosis were observed in histological sections with positive immunohistochemical staining for betanodavirus. Molecular phylogenetic analysis was performed based on the nucleotide sequences (1333 bases) of the capsid protein gene. The virus strain was highly homologous (93.07-93.88%) and closely related to red-spotted grouper nervous necrosis virus (RGNNV). © 2013 John Wiley & Sons Ltd.

Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

2017-12-01

Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

Current use of impact models for agri-environment schemes and potential for improvements of policy design and assessment.

PubMed

Primdahl, Jørgen; Vesterager, Jens Peter; Finn, John A; Vlahos, George; Kristensen, Lone; Vejre, Henrik

2010-06-01

Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES. (c) 2009 Elsevier Ltd. All rights reserved.

Measuring wind turbine wakes and unsteady loading in a micro wind farm model

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Meneveau, Charles; Meyers, Johan

2014-11-01

Very large wind farms, approximating the ``infinite'' asymptotic limit, are often studied with LES using periodic boundary conditions. In order to create an experimental realization of such large wind-turbine arrays in a wind tunnel experiment including over 100 turbines, a very small-scale turbine model based on a 3 cm diameter porous disk is designed. The porous disc matches a realistic thrust coefficient between 0.75--0.85, and the far wake flow characteristics of a rotating wind turbine. As a first step, we characterize the properties of a single model turbine. Hot-wire measurements are performed for uniform inflow conditions with different background turbulence intensity levels. Strain gage measurements are used to measure the mean value and power spectra of the thrust force, power output and wind velocity in front of the turbine. The dynamics of the wind turbine are modeled making it possible to measure force spectra at least up to the natural frequency of the model. This is shown by reproducing the -5/3 spectrum from the incoming flow and the vortex shedding signatures of an upstream obstruction. An array with a large number of these instrumented model turbines is placed in JHU's Corrsin wind tunnel, to study effects of farm layout on total power output and turbine loading. Work supported by ERC (ActiveWindFarms, Grant No: 306471), and by NSF (CBET-113380 and IIA-1243482).

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

Diffusion of a Sustainable Farming Technique in Sri Lanka: An Agent-Based Modeling Approach

NASA Astrophysics Data System (ADS)

Jacobi, J. H.; Gilligan, J. M.; Carrico, A. R.; Truelove, H. B.; Hornberger, G.

2012-12-01

We live in a changing world - anthropogenic climate change is disrupting historic climate patterns and social structures are shifting as large scale population growth and massive migrations place unprecedented strain on natural and social resources. Agriculture in many countries is affected by these changes in the social and natural environments. In Sri Lanka, rice farmers in the Mahaweli River watershed have seen increases in temperature and decreases in precipitation. In addition, a government led resettlement project has altered the demographics and social practices in villages throughout the watershed. These changes have the potential to impact rice yields in a country where self-sufficiency in rice production is a point of national pride. Studies of the climate can elucidate physical effects on rice production, while research on social behaviors can illuminate the influence of community dynamics on agricultural practices. Only an integrated approach, however, can capture the combined and interactive impacts of these global changes on Sri Lankan agricultural. As part of an interdisciplinary team, we present an agent-based modeling (ABM) approach to studying the effects of physical and social changes on farmers in Sri Lanka. In our research, the diffusion of a sustainable farming technique, the system of rice intensification (SRI), throughout a farming community is modeled to identify factors that either inhibit or promote the spread of a more sustainable approach to rice farming. Inputs into the ABM are both physical and social and include temperature, precipitation, the Palmer Drought Severity Index (PDSI), community trust, and social networks. Outputs from the ABM demonstrate the importance of meteorology and social structure on the diffusion of SRI throughout a farming community.

Responses of two marine top predators to an offshore wind farm.

PubMed

Vallejo, Gillian C; Grellier, Kate; Nelson, Emily J; McGregor, Ross M; Canning, Sarah J; Caryl, Fiona M; McLean, Nancy

2017-11-01

Quantifying the likely effects of offshore wind farms on wildlife is fundamental before permission for development can be granted by any Determining Authority. The effects on marine top predators from displacement from important habitat are key concerns during offshore wind farm construction and operation. In this respect, we present evidence for no significant displacement from a UK offshore wind farm for two broadly distributed species of conservation concern: common guillemot ( Uria aalge ) and harbor porpoise ( Phocoena phocoena ). Data were collected during boat-based line transect surveys across a 360 km 2 study area that included the Robin Rigg offshore wind farm. Surveys were conducted over 10 years across the preconstruction, construction, and operational phases of the development. Changes in guillemot and harbor porpoise abundance and distribution in response to offshore wind farm construction and operation were estimated using generalized mixed models to test for evidence of displacement. Both common guillemot and harbor porpoise were present across the Robin Rigg study area throughout all three development phases. There was a significant reduction in relative harbor porpoise abundance both within and surrounding the Robin Rigg offshore wind farm during construction, but no significant difference was detected between the preconstruction and operational phases. Relative common guillemot abundance remained similar within the Robin Rigg offshore wind farm across all development phases. Offshore wind farms have the potential to negatively affect wildlife, but further evidence regarding the magnitude of effect is needed. The empirical data presented here for two marine top predators provide a valuable addition to the evidence base, allowing future decision making to be improved by reducing the uncertainty of displacement effects and increasing the accuracy of impact assessments.

An Adaptive Coordinated Control for an Offshore Wind Farm Connected VSC Based Multi-Terminal DC Transmission System

NASA Astrophysics Data System (ADS)

Kumar, M. Ajay; Srikanth, N. V.

2015-01-01

The voltage source converter (VSC) based multiterminal high voltage direct current (MTDC) transmission system is an interesting technical option to integrate offshore wind farms with the onshore grid due to its unique performance characteristics and reduced power loss via extruded DC cables. In order to enhance the reliability and stability of the MTDC system, an adaptive neuro fuzzy inference system (ANFIS) based coordinated control design has been addressed in this paper. A four terminal VSC-MTDC system which consists of an offshore wind farm and oil platform is implemented in MATLAB/ SimPowerSystems software. The proposed model is tested under different fault scenarios along with the converter outage and simulation results show that the novel coordinated control design has great dynamic stabilities and also the VSC-MTDC system can supply AC voltage of good quality to offshore loads during the disturbances.

Risk-based methods for fish and terrestrial animal disease surveillance.

PubMed

Oidtmann, Birgit; Peeler, Edmund; Lyngstad, Trude; Brun, Edgar; Bang Jensen, Britt; Stärk, Katharina D C

2013-10-01

Over recent years there have been considerable methodological developments in the field of animal disease surveillance. The principles of risk analysis were conceptually applied to surveillance in order to further develop approaches and tools (scenario tree modelling) to design risk-based surveillance (RBS) programmes. In the terrestrial animal context, examples of risk-based surveillance have demonstrated the substantial potential for cost saving, and a similar benefit is expected also for aquatic animals. RBS approaches are currently largely absent for aquatic animal diseases. A major constraint in developing RBS designs in the aquatic context is the lack of published data to assist in the design of RBS: this applies to data on (i) the relative risk of farm sites becoming infected due to the presence or absence of a given risk factor; (ii) the sensitivity of diagnostic tests (specificity is often addressed by follow-up investigation and re-testing and therefore less of a concern); (iii) data on the variability of prevalence of infection for fish within a holding unit, between holding units and at farm level. Another constraint is that some of the most basic data for planning surveillance are missing, e.g. data on farm location and animal movements. In Europe, registration or authorisation of fish farms has only recently become a requirement under EU Directive 2006/88. Additionally, the definition of the epidemiological unit (at site or area level) in the context of aquaculture is a challenge due to the often high level of connectedness (mainly via water) of aquaculture facilities with the aquatic environment. This paper provides a review of the principles, methods and examples of RBS in terrestrial, farmed and wild animals. It discusses the special challenges associated with surveillance for aquatic animal diseases (e.g. accessibility of animals for inspection and sampling, complexity of rearing systems) and provides an overview of current developments relevant for the design of RBS for fish diseases. Suggestions are provided on how the current constraints to applying RBS to fish diseases can be overcome. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Development of methane conversion factor models for Zebu beef cattle fed low-quality crop residues and by-products in tropical regions.

PubMed

Kaewpila, Chatchai; Sommart, Kritapon

2016-10-01

The enteric methane conversion factor ( Y m ) is an important country-specific value for the provision of precise enteric methane emissions inventory reports. The objectives of this meta-analysis were to develop and evaluate the empirical Y m models for the national level and the farm level for tropical developing countries according to the IPCC's categorization. We used datasets derived from 18 in vivo feeding experiments from 1999 to 2015 of Zebu beef cattle breeds fed low-quality crop residues and by-products. We found that the observed Y m value was 8.2% gross energy (GE) intake (~120 g methane emission head -1  day -1 ) and ranged from 4.8% to 13.7% GE intake. The IPCC default model (tier 2, Y m  = 6.5% ± 1.0% GE intake) underestimated the Y m values by up to 26.1% compared with its refinement of 8.4% ± 0.4% GE intake for the national-level estimate. Both the IPCC default model and the refined model performed worse in predicting Y m trends at the farm level (root mean square prediction error [MSPE] = 15.1%-23.1%, concordance correlation coefficient [CCC] = 0.16-0.18, R 2  = .32). Seven of the extant Y m models based on a linear regression approach also showed inaccurately estimated Y m values (root MSPE = 16.2%-36.0%, CCC = 0.02-0.27, R 2  < .37). However, one of the developed models, which related to the complexity of the energy use efficiencies of the diet consumed to Y m , showed adequate accuracy at the farm level (root MSPE = 9.1%, CCC = 0.75, R 2  = .67). Our results thus suggest a new Y m model and future challenges for estimating Zebu beef cattle production in tropical developing countries.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanlon, Edward; Capece, John

Hendry County Sustainable Bio-Fuels Center (HCSBC) is introduced and its main components are explained. These primarily include (1) farming systems, (2) sustainability analysis, (3) economic analysis and (4) educational components. Each of these components is discussed in further details, main researchers and their responsibility areas and introduced. The main focus of this presentation is a new farming concept. The proposed new farming concept is an alternative to the current "two sides of the ditch" model, in which on one side are yield-maximizing, input-intensive, commodity price-dependent farms, while on the other side are publicly-financed, nutrient-removing treatment areas and water reservoirs tryingmore » to mitigate the externalized costs of food production systems and other human-induced problems. The proposed approach is rental of the land back to agriculture corporations during the restoration transition period in order to increase water storage (allowing for greater water flow-through and/or water storage on farms), preventing issues such as nutrients removal, using flood-tolerant crops and reducing soil subsidence. Various pros and cons of the proposed agricultural eco-services are discussed - the advantages include flexibility for participating farmers to achieve environmental outcomes with reduced costs and using innovative incentives; the minuses include the fact that the potential markets are not developed yet or that existing regulations may prevent agricultural producers from selling their services.« less

Statistical modeling to support power system planning

NASA Astrophysics Data System (ADS)

Staid, Andrea

This dissertation focuses on data-analytic approaches that improve our understanding of power system applications to promote better decision-making. It tackles issues of risk analysis, uncertainty management, resource estimation, and the impacts of climate change. Tools of data mining and statistical modeling are used to bring new insight to a variety of complex problems facing today's power system. The overarching goal of this research is to improve the understanding of the power system risk environment for improved operation, investment, and planning decisions. The first chapter introduces some challenges faced in planning for a sustainable power system. Chapter 2 analyzes the driving factors behind the disparity in wind energy investments among states with a goal of determining the impact that state-level policies have on incentivizing wind energy. Findings show that policy differences do not explain the disparities; physical and geographical factors are more important. Chapter 3 extends conventional wind forecasting to a risk-based focus of predicting maximum wind speeds, which are dangerous for offshore operations. Statistical models are presented that issue probabilistic predictions for the highest wind speed expected in a three-hour interval. These models achieve a high degree of accuracy and their use can improve safety and reliability in practice. Chapter 4 examines the challenges of wind power estimation for onshore wind farms. Several methods for wind power resource assessment are compared, and the weaknesses of the Jensen model are demonstrated. For two onshore farms, statistical models outperform other methods, even when very little information is known about the wind farm. Lastly, chapter 5 focuses on the power system more broadly in the context of the risks expected from tropical cyclones in a changing climate. Risks to U.S. power system infrastructure are simulated under different scenarios of tropical cyclone behavior that may result from climate change. The scenario-based approach allows me to address the deep uncertainty present by quantifying the range of impacts, identifying the most critical parameters, and assessing the sensitivity of local areas to a changing risk. Overall, this body of work quantifies the uncertainties present in several operational and planning decisions for power system applications.

Integration of Wind Turbines with Compressed Air Energy Storage

NASA Astrophysics Data System (ADS)

Arsie, I.; Marano, V.; Rizzo, G.; Moran, M.

2009-08-01

Some of the major limitations of renewable energy sources are represented by their low power density and intermittent nature, largely depending upon local site and unpredictable weather conditions. These problems concur to increase the unit costs of wind power, so limiting their diffusion. By coupling storage systems with a wind farm, some of the major limitations of wind power, such as a low power density and an unpredictable nature, can be overcome. After an overview on storage systems, the Compressed Air Energy Storage (CAES) is analyzed, and the state of art on such systems is discussed. A Matlab/Simulink model of a hybrid power plant consisting of a wind farm coupled with CAES is then presented. The model has been successfully validated starting from the operating data of the McIntosh CAES Plant in Alabama. Time-series neural network-based wind speed forecasting are employed to determine the optimal daily operation strategy for the storage system. A detailed economic analysis has been carried out: investment and maintenance costs are estimated based on literature data, while operational costs and revenues are calculated according to energy market prices. As shown in the paper, the knowledge of the expected available energy is a key factor to optimize the management strategies of the proposed hybrid power plant, allowing to obtain environmental and economic benefits.

An individual-based population dynamic model for estimating biomass yield and nutrient fluxes through an off-shore mussel ( Mytilus galloprovincialis) farm

NASA Astrophysics Data System (ADS)

Brigolin, Daniele; Maschio, Gabriele Dal; Rampazzo, Federico; Giani, Michele; Pastres, Roberto

2009-04-01

The fluxes of carbon, nitrogen and phosphorus through an off-shore long-line Mytilus galloprovincialis farm during a typical rearing cycle were estimated by combining a simple population dynamic model, based on a new individual model, and a set of field data, concerning the composition of the seston, as well as that of mussel meat and faeces. The individual model, based on an energy budget, was validated against a set of original field data, which were purposely collected from July 2006 to May 2007 in the North-Western Adriatic Sea (Italy) and was further tested using historical data. The model was upscaled to the population level by means of a set of Monte Carlo simulations, which were used for estimating the size structure of the population. The daily fluxes of C, N and P associated with mussel filtration, excretion and faeces and pseudo-faeces production were integrated over the 10-month-long rearing cycle and compared with the total amount of C, N and P removed by harvesting. The results indicate that the individual model compares well with an existing literature model and provides reliable estimations of the growth of mussel specimen over a range of trophic conditions which are typical of the Northern Adriatic Sea coastal area. The results of the budget calculation indicate that, even though the harvest represents a net removal of phosphorus and nitrogen from the ecosystem, the mussel farm increases the retention time of both nutrients in the coastal area, via the deposition of faeces and pseudo-faeces on the sea-bed. In fact, the amount of nitrogen associated with deposition is approximately twice the harvested one and the amount of phosphorus is approximately five times higher. These findings are in qualitative agreement with the results of literature budget and model calculations carried out in a temperate coastal embayment. This agreement suggests that the proper assessment of the overall effect of long-line mussel farming on both the benthic and pelagic ecosystem asks for an integrated modelling approach, which should include the dynamic of early diagenesis processes, as well as of that of nutrients released from the surface sediment.

Structure and performance of Awassi and Assaf dairy sheep farms in northwestern Spain.

PubMed

Milán, M J; Caja, G; González-González, R; Fernández-Pérez, A M; Such, X

2011-02-01

Data of 69 dairy sheep farms (70% Assaf and 30% Awassi crossbred), located in the Spanish Autonomous Community of Castilla y León and grouped for receiving technical advice, were used to study their structure and performance. Farm surface was 55.4ha, on average. Approximately 25% of the farms did not have cultivation land, and the other 75% had, on average, 73ha (from which 67% were devoted to forage). Farms used 2.1 annual work units (familiar, 90%), 493 ewes, and yielded 147,000 L/yr of milk. Farmers were tenant (84%), younger than 45 yr (70%), had new houses, and were grouped in cooperatives (83%). Sheep were fed indoors (occasional grazing only) in modern loose stalls and had machine milking. Planned mating (summer to fall) was done in 91% of farms (hormonal treatment, 54%) but artificial insemination was scarce (23%). Annual milk sales averaged 309 L/ewe (fat, 6.5%; protein, 5.3%; log(10) somatic cell count, 5.7), and milk was sent to local dairy industries for cheese production, and 1.35 lambs/ewe were harvested as milk-fed lambs (lechazo). Artificial lamb rearing was done in 38% of farms (automatic, 81%; manual, 19%). Total mixed rations were used in 33% of farms, and the rest used rationed concentrate (including self-produced cereals) according to physiological stage of the ewes (0.45 to 1.97 kg/d) and ad libitum forage (dehydrated, 70%; hay, 68%; fresh, 25%; silage, 12%). The concentrate-to-forage ratio ranged between 32 and 61%. In total, 68% of farms bought more than half of the forage, and 87% of them bought more than half of the required concentrates. According to structural, productive, and managerial traits, 4 types of farms were differentiated by using multiple correspondence analysis and cluster analysis. Type groups were: 1) large-surface farms, devoted to cereal and forage production, predominantly with Awassi crossbreed sheep and a high level of self-consumed commodities (12% of the farms); 2) large flocks with intermediate farm surfaces devoted to forage production and predominantly with Assaf sheep (30% of the farms); 3) high-yielding farms, with intermediate sized flocks of Assaf sheep and very intensive management (42% of the farms); and, 4) no-land farms predominantly with Assaf sheep (16% of the farms). In conclusion, the dairy sheep farms studied showed more adoption of intensive production systems than traditional farms, which resulted in higher milk and lamb yields. Despite all of them being based on familiar units, as traditional farms, they were highly dependent on external resources and became more vulnerable, faced with future uncertainties of the market. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems.

PubMed

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N

2013-05-01

A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were <10% for all variables, and concordance correlation coefficients over 0.80 for annual pasture utilisation, yields of milk and milk solids (MS; fat plus protein), and of 0.69 and 0.48 for LW and BCS, respectively. A simulation of two contrasting dairy systems is presented to show the practical use of the model. The model can be used to explore the effects of feeding level and genetic merit and their interactions for grazing dairy systems, evaluating the trade-offs between profit and the associated risk.

Monitoring, modeling and mitigating impacts of wind farms on local meteorology

NASA Astrophysics Data System (ADS)

Baidya Roy, Somnath; Traiteur, Justin; Kelley, Neil

2010-05-01

Wind power is one of the fastest growing sources of energy. Most of the growth is in the industrial sector comprising of large utility-scale wind farms. Recent modeling studies have suggested that such wind farms can significantly affect local and regional weather and climate. In this work, we present observational evidence of the impact of wind farms on near-surface air temperatures. Data from perhaps the only meteorological field campaign in an operational wind farm shows that downwind temperatures are lower during the daytime and higher at night compared to the upwind environment. Corresponding radiosonde profiles at the nearby Edwards Air Force Base WMO meteorological station show that the diurnal environment is unstable while the nocturnal environment is stable during the field campaign. This behavior is consistent with the hypothesis proposed by Baidya Roy et al. (JGR 2004) that states that turbulence generated in the wake of rotors enhance vertical mixing leading to a warming/cooling under positive/negative potential temperature lapse rates. We conducted a set of 306 simulations with the Regional Atmospheric Modeling System (RAMS) to test if regional climate models can capture the thermal effects of wind farms. We represented wind turbines with a subgrid parameterization that assumes rotors to be sinks of momentum and sources of turbulence. The simulated wind farms consistently generated a localized warming/cooling under positive/negative lapse rates as hypothesized. We found that these impacts are inversely correlated with background atmospheric boundary layer turbulence. Thus, if the background turbulence is high due to natural processes, the effects of additional turbulence generated by wind turbine rotors are likely to be small. We propose the following strategies to minimize impacts of wind farms: • Engineering solution: design rotors that generate less turbulence in their wakes. Sensitivity simulations show that these turbines also increase the productivity of wind farms and reduce damages to downwind rotors. • Siting solution: develop wind farms in regions where ABL turbulence is naturally high. Since, turbulence data is not widely recorded, we use surface KE dissipation rate as a proxy for ABL turbulence. Indeed, in our simulations, these 2 parameters are strongly positively correlated (P<0.99). Using the JRA25 dataset, comprising of 25-year long 6-hourly global meteorological data, we identify such regions in the world. These regions that include the Midwest and Great Plains as well as large parts of northern Europe and western China are appropriate sites for low-impact wind farms.

Dairy farms testing positive for Mycobacterium avium ssp. paratuberculosis have poorer hygiene practices and are less cautious when purchasing cattle than test-negative herds.

PubMed

Wolf, R; Barkema, H W; De Buck, J; Orsel, K

2016-06-01

Mycobacterium avium ssp. paratuberculosis (MAP), the causative agent of Johne's disease, is present on most dairy farms in Alberta, causing economic losses and presenting a potential public health concern. The objective of this cross-sectional study was to identify risk factors for Alberta dairy herds being MAP-positive based on environmental samples (ES). Risk assessments were conducted and ES were collected on 354 Alberta dairy farms (62% of eligible producers) voluntarily participating in the Alberta Johne's Disease Initiative. In univariate logistic regression, risk factors addressing animal and pen hygiene, as well as the use of feeding equipment to remove manure and manure application on pastures, were all associated with the number of positive ES. Furthermore, based on factor analysis, risk factors were clustered and could be summarized as 4 independent factors: (1) animal, pen, and feeder contamination; (2) shared equipment and pasture contamination; (3) calf diet; and (4) cattle purchase. Using these factor scores as independent variables in multivariate logistic regression models, a 1-unit increase in animal, pen, and feeder contamination resulted in 1.31 times higher odds of having at least 1 positive ES. Furthermore, a 1-unit increase in cattle purchase also resulted in 1.31 times the odds of having at least 1 positive ES. Finally, a 100-cow increase in herd size resulted in an odds ratio of 2.1 for having at least 1 positive ES. In conclusion, cleanliness of animals, pens, and feeders, as well as cattle purchase practices, affected risk of herd infection with MAP. Therefore, improvements in those management practices should be the focus of effective tools to control MAP on dairy farms. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Retrospective analysis of antibiotic treatments against piscirickettsiosis in farmed Atlantic salmon Salmo salar in Chile.

PubMed

Price, Derek; Stryhn, Henrik; Sánchez, Javier; Ibarra, Rolando; Tello, Alfredo; St-Hilaire, Sophie

2016-03-30

Piscirickettsiosis is the most prevalent salt-water infectious disease in farmed salmonids in Chile. Antimicrobials are used to treat this disease; however, there is growing concern about the poor response to therapeutants on some fish farms. The objective of this study was to assess whether factors such as type of antibiotic used, average fish weight, temperature at the beginning of the treatment, and mortality at the time of treatment administration affect the probability of treatment failure against piscirickettsiosis. Pen-level treatment and production information for the first treatment event from 2014 pens on 118 farms was used in a logistic mixed model to assess treatment failure. We defined a failed treatment as when the average mortality 3 wk after the treatment was above 0.1%. Farm and company were included in the model as random effects. We found that the antibiotic product, mortality level before the treatment, and fish weight at the start of the treatment all had a significant effect on treatment outcome. Our results suggest that antibiotic treatment success is higher if the treatment is administered when mortality associated with piscirickettsiosis is relatively low. We discuss the effect of weight on treatment success and its potential relationships with husbandry practices and drug pharmacokinetics.

A process-based model for cattle manure compost windrows: Model performance and application

USDA-ARS?s Scientific Manuscript database

A model was developed and incorporated in the Integrated Farm System Model (IFSM, v.4.3) that simulates important processes occurring during windrow composting of manure. The model, documented in an accompanying paper, predicts changes in windrow properties and conditions and the resulting emissions...

Towards an inventory of methane emissions from manure management that is responsive to changes on Canadian farms

NASA Astrophysics Data System (ADS)

VanderZaag, A. C.; MacDonald, J. D.; Evans, L.; Vergé, X. P. C.; Desjardins, R. L.

2013-09-01

Methane emissions from manure management represent an important mitigation opportunity, yet emission quantification methods remain crude and do not contain adequate detail to capture changes in agricultural practices that may influence emissions. Using the Canadian emission inventory methodology as an example, this letter explores three key aspects for improving emission quantification: (i) obtaining emission measurements to improve and validate emission model estimates, (ii) obtaining more useful activity data, and (iii) developing a methane emission model that uses the available farm management activity data. In Canada, national surveys to collect manure management data have been inconsistent and not designed to provide quantitative data. Thus, the inventory has not been able to accurately capture changes in management systems even between manure stored as solid versus liquid. To address this, we re-analyzed four farm management surveys from the past decade and quantified the significant change in manure management which can be linked to the annual agricultural survey to create a continuous time series. In the dairy industry of one province, for example, the percentage of manure stored as liquid increased by 300% between 1991 and 2006, which greatly affects the methane emission estimates. Methane emissions are greatest from liquid manure, but vary by an order of magnitude depending on how the liquid manure is managed. Even if more complete activity data are collected on manure storage systems, default Intergovernmental Panel on Climate Change (IPCC) guidance does not adequately capture the impacts of management decisions to reflect variation among farms and regions in inventory calculations. We propose a model that stays within the IPCC framework but would be more responsive to farm management by generating a matrix of methane conversion factors (MCFs) that account for key factors known to affect methane emissions: temperature, retention time and inoculum. This MCF matrix would be populated using a mechanistic emission model verified with on-farm emission measurements. Implementation of these MCF values will require re-analysis of farm surveys to quantify liquid manure emptying frequency and timing, and will rely on the continued collection of this activity data in the future. For model development and validation, emission measurement campaigns will be needed on representative farms over at least one full year, or manure management cycle (whichever is longer). The proposed approach described in this letter is long-term, but is required to establish baseline data for emissions from manure management systems. With these improvements, the manure management emission inventory will become more responsive to the changing practices on Canadian livestock farms.

The consideration of atmospheric stability within wind farm AEP calculations

NASA Astrophysics Data System (ADS)

Schmidt, Jonas; Chang, Chi-Yao; Dörenkämper, Martin; Salimi, Milad; Teichmann, Tim; Stoevesandt, Bernhard

2016-09-01

The annual energy production of an existing wind farm including thermal stratification is calculated with two different methods and compared to the average of three years of SCADA data. The first method is based on steady state computational fluid dynamics simulations and the assumption of Reynolds-similarity at hub height. The second method is a wake modelling calculation, where a new stratification transformation model was imposed on the Jensen an Ainslie wake models. The inflow states for both approaches were obtained from one year WRF simulation data of the site. Although all models underestimate the mean wind speed and wake effects, the results from the phenomenological wake transformation are compatible with high-fidelity simulation results.

Agroforestry versus farm mosaic systems - Comparing land-use efficiency, economic returns and risks under climate change effects.

PubMed

Paul, Carola; Weber, Michael; Knoke, Thomas

2017-06-01

Increasing land-use conflicts call for the development of land-use systems that reconcile agricultural production with the provisioning of multiple ecosystem services, including climate change mitigation. Agroforestry has been suggested as a global solution to increase land-use efficiency, while reducing environmental impacts and economic risks for farmers. Past research has often focused on comparing tree-crop combinations with agricultural monocultures, but agroforestry has seldom been systematically compared to other forms of land-use diversification, including a farm mosaic. This form of diversification mixes separate parcels of different land uses within the farm. The objective of this study was to develop a modelling approach to compare the performance of the agroforestry and farm mosaic diversification strategies, accounting for tree-crop interaction effects and economic and climate uncertainty. For this purpose, Modern Portfolio Theory and risk simulation were coupled with the process-based biophysical simulation model WaNuLCAS 4.0. For an example application, we used data from a field trial in Panama. The results show that the simulated agroforestry systems (Taungya, alley cropping and border planting) could outperform a farm mosaic approach in terms of cumulative production and return. Considering market and climate uncertainty, agroforestry showed an up to 21% higher economic return at the same risk level (i.e. standard deviation of economic returns). Farm compositions with large shares of land allocated to maize cultivation were also more severely affected by an increasing drought frequency in terms of both risks and returns. Our study demonstrates that agroforestry can be an economically efficient diversification strategy, but only if the design allows for economies of scope, beneficial interactions between trees and crops and higher income diversification compared to a farm mosaic. The modelling approach can make an important contribution to support land-use decisions at the farm level and reduce land-use conflicts at the landscape level. Copyright © 2017 Elsevier B.V. All rights reserved.

Exploring agent-level calculations of risk and returns in relation to observed land-use changes in the US Great Plains, 1870–1940

PubMed Central

Sylvester, Kenneth M.; Brown, Daniel G.; Leonard, Susan H.; Merchant, Emily; Hutchins, Meghan

2015-01-01

Land-use change in the U.S. Great Plains since agricultural settlement in the second half of the nineteenth century has been well documented. While aggregate historical trends are easily tracked, the decision-making of individual farmers is difficult to reconstruct. We use an agent-based model to tell the history of the settlement of the West by simulating farm-level agricultural decision making based on historical data about prices, yields, farming costs, and environmental conditions. The empirical setting for the model is the period between 1875 and 1940 in two townships in Kansas, one in the shortgrass region and the other in the mixed grass region. Annual historical data on yields and prices determine profitability of various land uses and thereby inform decision-making, in conjunction with the farmer’s previous experience and randomly assigned levels of risk aversion. Results illustrating the level of agreement between model output and unique and detailed household-level records of historical land use and farm size suggest that economic behavior and natural endowments account for land change processes to some degree, but are incomplete. Discrepancies are examined to identify missing processes through model experiments, in which we adjust input and output prices, crop yields, agent memory, and risk aversion. These analyses demonstrate how agent-based modeling can be a useful laboratory for thinking about social and economic behavior in the past. PMID:25729323

Farming for a Better Climate by Improving Nitrogen Use Efficiency and Reducing Greenhouse Gas Emissions (FarmClim)

NASA Astrophysics Data System (ADS)

Amon, Barbara; Winiwarter, Wilfried; Schröck, Andrea; Zechmeister-Boltenstern, Sophie; Kasper, Martina; Sigmund, Elisabeth; Schaller, Lena; Moser, Tobias; Baumgarten, Andreas; Dersch, Georg; Zethner, Gerhard; Anderl, Michael; Kitzler, Barbara

2014-05-01

The project FarmClim (Farming for a better climate) assesses impacts of agriculture on N and GHG fluxes in Austria and proposes measures for improving N efficiency and mitigating emissions, including their economic assessment. This paper focuses on animal husbandry and crop production measures, and on N2O emissions from soils. FarmClim applies national inventory reporting methods to assess Austrian NH3 and GHG fluxes in order to develop flux estimates with implementation of mitigation measures. Based on scientific literature and on the outcome of the Austrian working group agriculture and climate protection a list of potential mitigation measures has been produced: phase feeding, dairy cattle diet, biogas production. Data cover resulting production levels as well as GHG mitigation. In crop production, an optimisation potential remains with respect to N fertilization and nutrient uptake efficiency. Projected regional yield data and information on the N content of arable crops have been delivered from field experiments. These data complement official statistics and allow assessing the effect of increasing proportions of legume crops in crop rotations and reducing fertilizer input on a regional scale. Economic efficiency of measures is a crucial factor for their future implementation on commercial farms. The economic model evaluates investment costs as well as changes in direct costs, labour costs and economic yield. Biophysical modelling with Landscape DNDC allows establishing a framework to move from the current approach of applying the IPCC default emission factor for N2O emissions from soils. We select two Austrian model regions to calculate N fluxes taking into account region and management practices. Hot spots and hot moments as well as mitigation strategies are identified. Two test regions have been identified for soil emission modelling. The Marchfeld is an intensively used agricultural area in North-East Austria with very fertile soils and dry climate. The area of central Upper-Austria is characterized by heavy gley soils and higher annual precipitation (890mm). Based on site parameters, vegetation characteristics, management and meteorology, the model is able to predict C and N bio-geo-chemistry in agricultural ecosystems at site and regional scale. This is the basis for assessing further mitigation specifically focussing on the hot spots and hot moments of N emissions on a regional scale. The list of mitigation measures resulting from the project activities has been tailored to fit Austrian conditions in order to be attractive to stakeholders and farmers. Providing information on economic impacts to farms adds to the transparency of the approach taken. We expect that understanding the interest and the worries of farmers from the beginning supports creation of realistic output that can provide a strong incentive to urgently needed actions on improving farm N efficiencies.

Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wharton, S.; Bulaevskaya, V.; Irons, Z.

The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resourcemore » areas in the U.S. and are representative of typical wind farms found in their respective areas.« less

Evaluating the new soil erosion map of Hungary

NASA Astrophysics Data System (ADS)

Waltner, István; Centeri, Csaba; Takács, Katalin; Pirkó, Béla; Koós, Sándor; László, Péter; Pásztor, László

2017-04-01

With growing concerns on the effects of climate change and land use practices on our soil resources, soil erosion by water is becoming a significant issue internationally. Since the 1964 publication of the first soil erosion map of Hungary, there have been several attempts to provide a countrywide assessment of erosion susceptibility. However, there has been no up-to-date map produced in the last decade. In 2016, a new, 1:100 000 scale soil erosion map was published, based on available soil, elevation, land use and meteorological data for the extremely wet year of 2010. The map utilized combined outputs for two spatially explicit methods: the widely used empirical Universal Soil Loss Equation (USLE) and the process-based Pan-European Soil Erosion Risk Assessment (PESERA) models. The present study aims to provide a detailed analysis of the model results. In lieu of available national monitoring data, information from other sources were used. The Soil Degradation Subsystem (TDR) of the National Environmental Information System (OKIR) is a digital database based on a soil survey and farm dairy data collected from representative farms in Hungary. During the survey all kind of degradation forms - including soil erosion - were considered. Agricultural and demographic data was obtained from the Hungarian Central Statistical Office (KSH). Data from an interview-based survey was also used in an attempt to assess public awareness of soil erosion risks. Point-based evaluation of the model results was complemented with cross-regional assessment of soil erosion estimates. This, combined with available demographic information provides us with an opportunity to address soil erosion on a community level, with the identification of regions with the highest risk of being affected by soil erosion.

Review of transmission routes of 24 infectious diseases preventable by biosecurity measures and comparison of the implementation of these measures in pig herds in six European countries.

PubMed

Filippitzi, M E; Brinch Kruse, A; Postma, M; Sarrazin, S; Maes, D; Alban, L; Nielsen, L R; Dewulf, J

2018-04-01

This study aimed to review the transmission routes of important infectious pig diseases and to translate these into biosecurity measures preventing or reducing the transmission between and within pig herds. Furthermore, it aimed to identify the level of implementation of these measures in different European countries and discuss the observed variations to identify potentials for improvement. First, a literature review was performed to show which direct and indirect transmission routes of 24 infectious pig diseases can be prevented through different biosecurity measures. Second, a quantitative analysis was performed using the Biocheck.UGent™, a risk-based scoring system to evaluate biosecurity in pig herds, to obtain an insight into the implementation of these biosecurity measures. The database contained farm-specific biosecurity data from 574 pig farms in Belgium, Denmark, France, Germany, the Netherlands and Sweden, entered between January 2014 and January 2016. Third, a qualitative analysis based on a review of literature and other relevant information resources was performed for every subcategory of internal and external biosecurity in the Biocheck.UGent™ questionnaire. The quantitative analysis indicated that at the level of internal, external and overall biosecurity, Denmark had a significantly distinct profile with higher external biosecurity scores and less variation than the rest of the countries. This is likely due to a widely used specific pathogen-free (SPF) system with extensive focus on biosecurity since 1971 in Denmark. However, the observed pattern may also be attributed to differences in data collection methods. The qualitative analysis identified differences in applied policies, legislation, disease status, pig farm density, farming culture and habits between countries that can be used for shaping country-specific biosecurity advice to attain improved prevention and control of important pig diseases in European pig farms. © 2017 Blackwell Verlag GmbH.

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

PubMed

De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

2014-12-01

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

The Farm Process Version 2 (FMP2) for MODFLOW-2005 - Modifications and Upgrades to FMP1

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, R.T.

2009-01-01

The ability to dynamically simulate the integrated supply-and-demand components of irrigated agricultural is needed to thoroughly understand the interrelation between surface water and groundwater flow in areas where the water-use by vegetation is an important component of the water budget. To meet this need, the computer program Farm Process (FMP1) was updated and refined for use with the U.S. Geological Survey's MODFLOW-2005 groundwater-flow model, and is referred to as MF2005-FMP2. The updated program allows the simulation, analysis, and management of nearly all components of human and natural water use. MF2005-FMP2 represents a complete hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for water consumption of irrigated agriculture, but also of urban use, and of natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, the MF2005-FMP2 has the unique set of capabilities to simulate and analyze historical, present, and future conditions. MF2005-FMP2 facilitates the analysis of agricultural water use where little data is available for pumpage, land use, or agricultural information. The features presented in this new version of FMP2 along with the linkages to the Streamflow Routing (SFR), Multi-Node Well (MNW), and Unsaturated Zone Flow (UZF) Packages prevents mass loss to an open system and helps to account for 'all of the water everywhere and all of the time'. The first version, FMP1 for MODFLOW-2000, is limited to (a) transpiration uptake from unsaturated root zones, (b) on-farm efficiency defined solely by farm and not by crop type, (c) a simulation of water use and returnflows related only to irrigated agriculture and not also to non-irrigated vegetation, (d) a definition of consumptive use as potential crop evapotranspiration, (e) percolation being instantly recharged to the uppermost active aquifer, (f) automatic routing of returnflow from runoff either to reaches of tributary stream segments adjacent to a farm or to one reach nearest to the farm's lowest elevation, (g) farm-well pumping from cell locations regardless of whether an irrigation requirement from these cells exists or not, and (h) specified non-routed water transfers from an undefined source outside the model domain. All of these limitations are overcome in MF2005-FMP2. The new features include (a) simulation of transpiration uptake from variably saturated, fully saturated, or ponded root zones (for example, for crops like rice or riparian vegetation), (b) definition of on-farm efficiency not only by farm but also by crop, (c) simulation of water use and returnflow from non-irrigated vegetation (for example, rain-fed agriculture or native vegetation), (d) use of crop coefficients and reference evapotranspiration, (e) simulation of the delay between percolation from farms through the unsaturated zone and recharge into the uppermost active aquifer by linking FMP2 to the UZF Package, (f) an option to manually control the routing of returnflow from farm runoff to streams, (g) an option to limit pumping to wells located only in cells where an irrigation requirement exists, and (h) simulation of water transfers to farms from a series of well fields (for example, recovery well field of an aquifer-storage-and-recovery system, ASR). In addition to the output of an economic budget for each farm between irrigation demand and supply ('Farm Demand and Supply Budget' in FMP1), a new output option called 'Farm Budget' was created for FMP2, which allows the user to track all physical flows into and out of a water accounting unit at all times. Such a unit can represent individual farms, farming districts, natural areas, or urban areas. The example model demonstrates the application of MF2005-FMP2 with delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in de

Dynamic wake model with coordinated pitch and torque control of wind farms for power tracking

NASA Astrophysics Data System (ADS)

Shapiro, Carl; Meyers, Johan; Meneveau, Charles; Gayme, Dennice

2017-11-01

Control of wind farm power production, where wind turbines within a wind farm coordinate to follow a time-varying power set point, is vital for increasing renewable energy participation in the power grid. Previous work developed a one-dimensional convection-diffusion equation describing the advection of the velocity deficit behind each turbine (wake) as well the turbulent mixing of the wake with the surrounding fluid. Proof-of-concept simulations demonstrated that a receding horizon controller built around this time-dependent model can effectively provide power tracking services by modulating the thrust coefficients of individual wind turbines. In this work, we extend this model-based controller to include pitch angle and generator torque control and the first-order dynamics of the drive train. Including these dynamics allows us to investigate control strategies for providing kinetic energy reserves to the grid, i.e. storing kinetic energy from the wind in the rotating mass of the wind turbine rotor for later use. CS, CM, and DG are supported by NSF (ECCS-1230788, CMMI 1635430, and OISE-1243482, the WINDINSPIRE project). JM is supported by ERC (ActiveWindFarms, 306471). This research was conducted using computational resources at MARCC.

Sea lice and salmon population dynamics: effects of exposure time for migratory fish.

PubMed

Krkosek, Martin; Morton, Alexandra; Volpe, John P; Lewis, Mark A

2009-08-07

The ecological impact of parasite transmission from fish farms is probably mediated by the migration of wild fishes, which determines the period of exposure to parasites. For Pacific salmon and the parasitic sea louse, Lepeophtheirus salmonis, analysis of the exposure period may resolve conflicting observations of epizootic mortality in field studies and parasite rejection in experiments. This is because exposure periods can differ by 2-3 orders of magnitude, ranging from months in the field to hours in experiments. We developed a mathematical model of salmon-louse population dynamics, parametrized by a study that monitored naturally infected juvenile salmon held in ocean enclosures. Analysis of replicated trials indicates that lice suffer high mortality, particularly during pre-adult stages. The model suggests louse populations rapidly decline following brief exposure of juvenile salmon, similar to laboratory study designs and data. However, when the exposure period lasts for several weeks, as occurs when juvenile salmon migrate past salmon farms, the model predicts that lice accumulate to abundances that can elevate salmon mortality and depress salmon populations. The duration of parasite exposure is probably critical to salmon-louse population dynamics, and should therefore be accommodated in coastal planning and management where fish farms are situated on wild fish migration routes.

Modelling-based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling.

PubMed

Hutchison, M L; Taylor, M J; Tchòrzewska, M A; Ford, G; Madden, R H; Knowles, T G

2017-05-01

To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses. The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on-farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and defeathering stages of processing and the numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame. Changes in farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions. Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost-effective and suitable for adoption into established farms and commercial processing. © 2017 The Authors. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

A Programmed Enterprise Analysis Teaching Guide for Selected Farm Enterprises in North Dakota: Prepared as Part of the Farm Management Education In-Service Workshop.

ERIC Educational Resources Information Center

North Dakota State Board for Vocational Education, Bismarck.

The series of programmed teaching guides for the enterprise analysis of selected enterprises was prepared by the participants in a Farm Management Education In-Service Workshop at North Dakota State University. The guide should be useful to teachers of adult Farm Managment classes in helping to teach farmers to make a thorough analysis of the…

An empirical analysis of the cost of rearing dairy heifers from birth to first calving and the time taken to repay these costs.

PubMed

Boulton, A C; Rushton, J; Wathes, D C

2017-08-01

Rearing quality dairy heifers is essential to maintain herds by replacing culled cows. Information on the key factors influencing the cost of rearing under different management systems is, however, limited and many farmers are unaware of their true costs. This study determined the cost of rearing heifers from birth to first calving in Great Britain including the cost of mortality, investigated the main factors influencing these costs across differing farming systems and estimated how long it took heifers to repay the cost of rearing on individual farms. Primary data on heifer management from birth to calving was collected through a survey of 101 dairy farms during 2013. Univariate followed by multivariable linear regression was used to analyse the influence of farm factors and key rearing events on costs. An Excel spreadsheet model was developed to determine the time it took for heifers to repay the rearing cost. The mean±SD ages at weaning, conception and calving were 62±13, 509±60 and 784±60 days. The mean total cost of rearing was £1819±387/heifer with a mean daily cost of £2.31±0.41. This included the opportunity cost of the heifer and the mean cost of mortality, which ranged from £103.49 to £146.19/surviving heifer. The multivariable model predicted an increase in mean cost of rearing of £2.87 for each extra day of age at first calving and a decrease in mean cost of £6.06 for each percentile increase in time spent at grass. The model also predicted a decrease in the mean cost of rearing in autumn and spring calving herds of £273.20 and £288.56, respectively, compared with that in all-year-round calving herds. Farms with herd sizes⩾100 had lower mean costs of between £301.75 and £407.83 compared with farms with <100 milking cows. The mean gross margin per heifer was £441.66±304.56 (range £367.63 to £1120.08), with 11 farms experiencing negative gross margins. Most farms repaid the cost of heifer rearing in the first two lactations (range 1 to 6 lactations) with a mean time from first calving until breaking even of 530±293 days. The results of the economic analysis suggest that management decisions on key reproduction events and grazing policy significantly influence the cost of rearing and the time it takes for heifers to start making a profit for the farm.

Economic evaluation of the Programs Rede Farmácia de Minas do SUS versus Farmácia Popular do Brasil.

PubMed

Garcia, Marina Morgado; Guerra, Augusto Afonso; Acúrcio, Francisco de Assis

2017-01-01

We conducted an economic assessment of the Pharmaceutical Assistance - Rede Farmácia de Minas Gerais-RFMG and Farmácia Popular do Brasil-FPB to ascertain which of the two models stands out as the most efficient. To do this, a model, which consisted of a study of incurred costs in both programs, up to the dispensing of medicine to citizens, was developed. The uncertainties of the proposed model were tested using the Monte Carlo method. If the entire population initially estimated in the RFMG were attended in the FPB, there would be an additional cost of R$ 139,324,050.19. The sensitivity analysis appeared to be favorable to the RFMG. A total of 10000 simulations were carried out, resulting in a median value of R$ 114,053,709.99 for the RFMG and R$ 254,106,120.65 for the FPB. The current National Drug Policy emphasizes the need to strengthen pharmaceutical services beyond the mere acquisition and delivery of pharmaceutical products. The public healthcare service model, consistent with the principles and guidelines of the SUS, seems to be more appropriate in ensuring complete and universal quality healthcare services to the citizens. The economic study conducted reinforces this fact, as it appears to be a more efficient alternative of the direct use of resources in the public health network.

Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

ScienceCinema

Danuso, Francesco

2017-12-22

A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

Evaluating the impact of farm scale innovation at catchment scale

NASA Astrophysics Data System (ADS)

van Breda, Phelia; De Clercq, Willem; Vlok, Pieter; Querner, Erik

2014-05-01

Hydrological modelling lends itself to other disciplines very well, normally as a process based system that acts as a catalogue of events taking place. These hydrological models are spatial-temporal in their design and are generally well suited for what-if situations in other disciplines. Scaling should therefore be a function of the purpose of the modelling. Process is always linked with scale or support but the temporal resolution can affect the results if the spatial scale is not suitable. The use of hydrological response units tends to lump area around physical features but disregards farm boundaries. Farm boundaries are often the more crucial uppermost resolution needed to gain more value from hydrological modelling. In the Letaba Catchment of South Africa, we find a generous portion of landuses, different models of ownership, different farming systems ranging from large commercial farms to small subsistence farming. All of these have the same basic right to water but water distribution in the catchment is somewhat of a problem. Since water quantity is also a problem, the water supply systems need to take into account that valuable production areas not be left without water. Clearly hydrological modelling should therefore be sensitive to specific landuse. As a measure of productivity, a system of small farmer production evaluation was designed. This activity presents a dynamic system outside hydrological modelling that is generally not being considered inside hydrological modelling but depends on hydrological modelling. For sustainable development, a number of important concepts needed to be aligned with activities in this region, and the regulatory actions also need to be adhered to. This study aimed at aligning the activities in a region to the vision and objectives of the regulatory authorities. South Africa's system of socio-economic development planning is complex and mostly ineffective. There are many regulatory authorities involved, often with unclear responsibilities and inadequate procedures of implementing objectives. Planning for development in South Africa needs to take various factors into account. Economic and green economic growth is pursued, while social imbalances are addressed and the environment is protected against unreasonable exploitation. The term Sustainable Development is a neutral concept in the vision of many of the regulating authorities; however, the implementation of sustainability is difficult. This study considers an approach which aligns activities in a specified region to the vision and objectives of the applicable regulatory authorities, as an alternative to achieving objectives strictly through enforcing regulations. It was determined whether objectives of development planning were realistic in terms of water availability. It was established that the position of a farm in the landscape is a determining factor of the impact it has on the catchment area's water supply. For this purpose, hydrological modelling (SWAT and SIMGRO) was done for the Letaba catchment of the Limpopo Province, on two scales to also accommodate small-scale farming communities more accurately. Parallel to the modelling, the National Development Plan (NDP), the National Framework for Sustainable Development (NFSD), the Integrated Sustainable Rural Development Strategy (ISRDS) and the principles of Water Allocation Reform (WAR) were regarded. For regional categorisation, the relevant municipal Integrated Development Plan (IDP), Spatial Development Framework (SDF), Local Economic Development (LED) plan and the applicable Catchment Management Strategy (CMS) were considered. The developed Integrated Evaluation Model combined all the visions and objectives of the mentioned strategic documents to specifically assess the contribution a small-scale farm makes. The evaluation results provided insight into the alignment of activities to the ideals of a region and can be useful when formulating actions to reach a common vision. Small-scale farms are well-aligned to the objectives of WAR, the CMS and ISRDS. The farms have a limited contribution to the ideals of the NDP and NFSD and results against the IDP, the SDF and the LED differ considerably for each farm. Furthermore, the results of the farms' alignment with regional objectives do not correspond to the hydrologically ideal locations. Therefore, the development of small-scale farming should take hydrological information into consideration. The Integrated Evaluation Model proves to be valuable, understandable and applicable to evaluate the alignment of small-scale farms to the visions of regulatory authorities. It is also foreseen that the Evaluation model be linked to the hydrological model. The work was also kindly supported and executed in the framework of the EU project EAU4Food.

Farm Business Management Analysis: Analyzing the Farm Business. Unit II. Volume 13, Number 7.

ERIC Educational Resources Information Center

Denker, Robert; And Others

Intended for use by Missouri vocational agricultural instructors in Farm Business Management Analysis programs for young and adult farmers, this curriculum guide contains 10 lessons in analyzing records. Each lesson is a self-contained instructional package and includes materials for monthly classroom sessions and monthly on-the-farm instructional…

Development of Farming Diversification with Implementation Plant Patterns as a Strategy of Economic Strengthening

NASA Astrophysics Data System (ADS)

Anwar, S.; Setyohadi, D. P. S.; Utami, M. M. D.; Damanhuri; Hariono, B.

2018-01-01

Bojonegoro, Tulungagung, and Ponorogo districts are an agrarian area and become one of the leading food crops producers in East Java Province. Diversification of farming in this region is done by applying season-based cropping pattern, which is cultivating various commodities in rotation. Farmers need diversification programs wetland cannot provide an optimal contribution to the income of farmers caused because farmers are not able to cultivate high value-added commodities due to limited capital. This research is to identify the characteristics of farming and to analyse the farming system to know the pattern of planting suggestion and prospect. The research used descriptive method, profit farming analysis, and SWOT. The results showed that each region has a specific planting pattern with rice as the main commodity grown in the rainy season followed by crops and horticultural crops and a suggested planting pattern that needs to be implemented by farmers to increase their income. The prospect of diversification of farming development through the implementation of the proposed planting pattern is very suitable with the character of the region and the market demand.

An analysis of inputs cost for carp farming sector in 2001 in Iran.

PubMed

Salehi, Hassan

2007-11-01

Carp is widely sold and used in its fresh in Iran, however, recently a range of value additions may also be observed. It is essential to the sustainable development of a carp farm to know the production costs and their contribution. Warm-water fish farming is mainly based on common, silver, grass and bighead carp and the common carp and the three Chinese species are often reared in poly culture in Iran. Since, the 1970s carp farming has spread around the Caspian coast and farmed production reached a peak in 2006 with production of more than 73,400 tons. A study of production, costs and profitability of carp farming sector was carried out to help clarify carp production costs and their difference with location in 2001. A total of 101 farms from the three main carp farming provinces, Guilan, Mazandaran and Khuzestan were randomly selected, classified and studied. The results of the survey showed that the various producer provinces have different cost structures. Overall, feed and fertilizer with the highest level of variation accounted for 23% of total costs, followed by seed and labor and salary with 23 and 17%, respectively. On average, benefit-cost ratio and the rate of farm income were closely related to location. This result suggests that farmers practice more efficiently and have better conditions in Mazandaran, followed by Guilan province.

Large Eddy Simulation of Vertical Axis Wind Turbines

NASA Astrophysics Data System (ADS)

Hezaveh, Seyed Hossein

Due to several design advantages and operational characteristics, particularly in offshore farms, vertical axis wind turbines (VAWTs) are being reconsidered as a complementary technology to horizontal axial turbines (HAWTs). However, considerable gaps remain in our understanding of VAWT performance since they have been significantly less studied than HAWTs. This thesis examines the performance of isolated VAWTs based on different design parameters and evaluates their characteristics in large wind farms. An actuator line model (ALM) is implemented in an atmospheric boundary layer large eddy simulation (LES) code, with offline coupling to a high-resolution blade-scale unsteady Reynolds-averaged Navier-Stokes (URANS) model. The LES captures the turbine-to-farm scale dynamics, while the URANS captures the blade-to-turbine scale flow. The simulation results are found to be in good agreement with existing experimental datasets. Subsequently, a parametric study of the flow over an isolated VAWT is carried out by varying solidities, height-to-diameter aspect ratios, and tip speed ratios. The analyses of the wake area and power deficits yield an improved understanding of the evolution of VAWT wakes, which in turn enables a more informed selection of turbine designs for wind farms. One of the most important advantages of VAWTs compared to HAWTs is their potential synergistic interactions that increase their performance when placed in close proximity. Field experiments have confirmed that unlike HAWTs, VAWTs can enhance and increase the total power production when placed near each other. Based on these experiments and using ALM-LES, we also present and test new approaches for VAWT farm configuration. We first design clusters with three turbines then configure farms consisting of clusters of VAWTs rather than individual turbines. The results confirm that by using a cluster design, the average power density of wind farms can be increased by as much as 60% relative to regular arrays. Finally, the thesis conducts an investigation of the influence of farm length (parallel to the wind) to assess the fetch needed for equilibrium to be reached, as well as the origin of the kinetic energy extracted by the turbines.

Whole-farm phosphorus loss from grazing-based dairy farms

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) loss from agricultural farms persists as a water quality impairment issue. For dairy farms, P can be lost from cropland, pastures, and open-air lots. We used interview surveys to document land use, cattle herd characteristics, and manure management for four grazing-based dairy farms i...

Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms

PubMed Central

Ssematimba, Amos; Hagenaars, Thomas J.; de Jong, Mart C. M.

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km. PMID:22348042

Modelling the wind-borne spread of highly pathogenic avian influenza virus between farms.

PubMed

Ssematimba, Amos; Hagenaars, Thomas J; de Jong, Mart C M

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km.

Analysis of swine movements in a province in Northern Vietnam and application in the design of surveillance strategies for infectious diseases

PubMed Central

Baudon, Eugénie; Fournié, Guillaume; Hiep, Dao Thi; Pham, Thi Thanh Hoa; Duboz, Raphael; Gély, Marie; Peiris, Malik; Cowling, Benjamin J.; Ton, Vu Dinh; Peyre, Marisa

2015-01-01

Summary While swine production is rapidly growing in South-East Asia, the structure of the swine industry and the dynamic of pig movements have not been well-studied. However, this knowledge is a pre-requisite for understanding the dynamic of disease transmission in swine populations and designing cost-effective surveillance strategies for infectious diseases. In this study, we assessed the farming and trading practices in the Vietnamese swine familial farming sector, which accounts for most pigs in Vietnam, and for which disease surveillance is a major challenge. Farmers from two communes of a Red River Delta province (Northern Vietnam) were interviewed, along with traders involved in pig transactions. Major differences in the trade structure were observed between the two communes. One commune had mainly transversal trades, i.e. between farms of equivalent sizes, whereas the other had pyramidal trades, i.e. from larger to smaller farms. Companies and large familial farrow-to-finish farms were likely to act as major sources of disease spread through pig sales, demonstrating their importance for disease control. Familial fattening farms with high pig purchases were at greater risk of disease introduction and should be targeted for disease detection as part of a risk-based surveillance. In contrast, many other familial farms were isolated or weakly connected to the swine trade network limiting their relevance for surveillance activities. However, some of these farms used boar hiring for breeding, increasing the risk of disease spread. Most familial farms were slaughtering pigs at the farm or in small local slaughterhouses, making the surveillance at the slaughterhouse inefficient. In terms of spatial distribution of the trades, the results suggested that Northern provinces were highly connected and showed some connection with Central and Southern provinces. These results are useful to develop risk-based surveillance protocols for disease detection in the swine familial sector, and to make recommendations for disease control. PMID:26040303

Analysis of Swine Movements in a Province in Northern Vietnam and Application in the Design of Surveillance Strategies for Infectious Diseases.

PubMed

Baudon, E; Fournié, G; Hiep, D T; Pham, T T H; Duboz, R; Gély, M; Peiris, M; Cowling, B J; Ton, V D; Peyre, M

2017-04-01

While swine production is rapidly growing in South-East Asia, the structure of the swine industry and the dynamic of pig movements have not been well-studied. However, this knowledge is a prerequisite for understanding the dynamic of disease transmission in swine populations and designing cost-effective surveillance strategies for infectious diseases. In this study, we assessed the farming and trading practices in the Vietnamese swine familial farming sector, which accounts for most pigs in Vietnam, and for which disease surveillance is a major challenge. Farmers from two communes of a Red River Delta Province (northern Vietnam) were interviewed, along with traders involved in pig transactions. Major differences in the trade structure were observed between the two communes. One commune had mainly transversal trades, that is between farms of equivalent sizes, whereas the other had pyramidal trades, that is from larger to smaller farms. Companies and large familial farrow-to-finish farms were likely to act as major sources of disease spread through pig sales, demonstrating their importance for disease control. Familial fattening farms with high pig purchases were at greater risk of disease introduction and should be targeted for disease detection as part of a risk-based surveillance. In contrast, many other familial farms were isolated or weakly connected to the swine trade network limiting their relevance for surveillance activities. However, some of these farms used boar hiring for breeding, increasing the risk of disease spread. Most familial farms were slaughtering pigs at the farm or in small local slaughterhouses, making the surveillance at the slaughterhouse inefficient. In terms of spatial distribution of the trades, the results suggested that northern provinces were highly connected and showed some connection with central and southern provinces. These results are useful to develop risk-based surveillance protocols for disease detection in the swine familial sector and to make recommendations for disease control. © 2015 Blackwell Verlag GmbH.

ATMOSPHERIC AMMONIA EMISSIONS FROM THE LIVESTOCK SECTOR: DEVELOPMENT AND EVALUATION OF A PROCESS-BASED MODELING APPROACH

EPA Science Inventory

We propose multi-faceted research to enhance our understanding of NH3 emissions from livestock feeding operations. A process-based emissions modeling approach will be used, and we will investigate ammonia emissions from the scale of the individual farm out to impacts on region...

A multi-event capture-recapture analysis of Toxoplasma gondii seroconversion dynamics in farm cats.

PubMed

Simon, Julie Alice; Pradel, Roger; Aubert, Dominique; Geers, Régine; Villena, Isabelle; Poulle, Marie-Lazarine

2018-06-08

Domestic cats play a key role in the epidemiology of the parasite Toxoplasma gondii by excreting environmentally-resistant oocysts that may infect humans and other warm-blooded animals. The dynamics of Toxoplasma gondii seroconversion, used as a proxy for primo-infection dynamics, was investigated in five cat populations living on farms. Serological tests on blood samples from cats were performed every three months over a period of two years, for a total of 400 serological tests performed on 130 cats. Variations in seroconversion rates and associated factors were investigated using a multi-event capture-recapture modelling approach that explicitly accounted for uncertainties in cat age and serological status. Seroprevalence varied between farms, from 15 to 73%, suggesting differential exposure of cats to T. gondii. In farms with high exposure, cats could become infected before reaching the age of six months. Seroconversion rates varied from 0.42 to 0.96 seroconversions per cat per year and were higher in autumn and winter than in spring and summer. Our results suggest inter-farm and seasonal variations in the risks of exposure to T. gondii oocysts for humans and livestock living on farms. The paper also discusses the role of young cats in the maintenance of environmental contamination by T. gondii oocysts on farms.

Optimal control of energy extraction in LES of large wind farms

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay; Munters, Wim

2014-11-01

We investigate the use of optimal control combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large ``infinite'' wind farms and in finite farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with an actuator-disk representation of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in the actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. In a first infinite wind-farm case, we find that farm power is increases by approximately 16% over one hour of operation. This comes at the cost of a deceleration of the outer layer of the boundary layer. A detailed analysis of energy balances is presented, and a comparison is made between infinite and finite farm cases, for which boundary layer entrainment plays an import role. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Govern.

Integrated Farm System Model Version 4.3 and Dairy Gas Emissions Model Version 3.3 Software development and distribution

USDA-ARS?s Scientific Manuscript database

Modeling routines of the Integrated Farm System Model (IFSM version 4.2) and Dairy Gas Emission Model (DairyGEM version 3.2), two whole-farm simulation models developed and maintained by USDA-ARS, were revised with new components for: (1) simulation of ammonia (NH3) and greenhouse gas emissions gene...

Multi-Objective Random Search Algorithm for Simultaneously Optimizing Wind Farm Layout and Number of Turbines

NASA Astrophysics Data System (ADS)

Feng, Ju; Shen, Wen Zhong; Xu, Chang

2016-09-01

A new algorithm for multi-objective wind farm layout optimization is presented. It formulates the wind turbine locations as continuous variables and is capable of optimizing the number of turbines and their locations in the wind farm simultaneously. Two objectives are considered. One is to maximize the total power production, which is calculated by considering the wake effects using the Jensen wake model combined with the local wind distribution. The other is to minimize the total electrical cable length. This length is assumed to be the total length of the minimal spanning tree that connects all turbines and is calculated by using Prim's algorithm. Constraints on wind farm boundary and wind turbine proximity are also considered. An ideal test case shows the proposed algorithm largely outperforms a famous multi-objective genetic algorithm (NSGA-II). In the real test case based on the Horn Rev 1 wind farm, the algorithm also obtains useful Pareto frontiers and provides a wide range of Pareto optimal layouts with different numbers of turbines for a real-life wind farm developer.

Social Networks and Welfare in Future Animal Management.

PubMed

Koene, Paul; Ipema, Bert

2014-03-17

It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

Operationalizing Principle-Based Standards for Animal Welfare-Indicators for Climate Problems in Pig Houses.

PubMed

Vermeer, Herman M; Hopster, Hans

2018-03-23

The Dutch animal welfare law includes so-called principle-based standards. This means that the objective is described in abstract terms, enabling farmers to comply with the law in their own way. Principle-based standards are, however, difficult for the inspection agency to enforce because strict limits are missing. This pilot project aimed at developing indicators (measurements) to assess the climate in pig houses, thus enabling the enforcement of principle-based standards. In total, 64 farms with weaners and 32 farms with growing-finishing pigs were visited. On each farm, a set of climate-related measurements was collected in six pens. For each of these measurements, a threshold value was set, and exceeding this threshold indicated a welfare risk. Farm inspections were carried out during winter and spring, thus excluding situations with heat stress. Assessment of the variation and correlation between measurements reduced the dataset from 39 to 12 measurements. Using a principal components analysis helped to select five major measurements as warning signals. The number of exceeded thresholds per pen and per farm was calculated for both the large (12) and small (five) sets of measurements. CO₂ and NH₃ concentrations were related to the outside temperature. On colder days, there was less ventilation, and thus CO₂ and NH₃ concentrations increased. Air quality, reflected in the CO₂ and NH₃ concentrations, was associated with respiratory problems. Eye scores were positively correlated with both pig and pen fouling, and pig and pen fouling were closely related. We selected five signal indicators: CO₂, NH₃, and tail and eye score for weaners and finishers, and added ear score for weaners and pig fouling for growing-finishing pigs. The results indicate that pig farms can be ranked based on five signal indicators related to reduced animal welfare caused by climatic conditions. This approach could be adopted to other principle-based standards for pigs as well as for other species.

Marine environmental impact assessment of abalone, Haliotis discus hannai, cage farm in Wan-do, Republic of Korea

NASA Astrophysics Data System (ADS)

Oh, Hyun-Taik; Jung, Rae-Hong; Cho, Yoon-Sik; Hwang, Dong-Woon; Yi, Yong-Min

2015-12-01

To assess the marine environmental impacts of abalone, Haliotis discus hannai, cage farms in Wan-do, we monitored the benthic environment on top of the sediment underneath cage farm stations and reference stations. We applied two methods for this assessment. One was the A- and B-investigation of the MOM system (Modeling-On fish farm-Monitoring) developed in Norway. The other was a general environmental monitoring method which is widely used. In this study, we found benthic animals in all samples that belonged to condition 1 which were based on group 1(presence of macrofauna) of the B-investigation method. The values of redox potential (group 2-pH, redox potential) in all samples were above +65 mV belonging to condition 1. Based on sensory results (group 3-gas, color, odor, thickness of deposits), five out of seven experiment samples showed condition 1 while stations 2 and 7 showed condition 2, which have been cultured for 10 years in semi-closed waters. As group 2 takes precedence over group 3, the level of the conditions for B-investigation results consequently showed condition 1 in all stations. We found that pollutants and trace metals in the sediment underneath cage farms were lower than the pollution standard. This led us to conclude that the environmental impacts of the cage farms in this study were not significant.

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets

PubMed Central

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E.; Feldman, Mark; Forstner, Michael R. J.

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions. PMID:26407157

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets.

PubMed

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E; Feldman, Mark; Forstner, Michael R J

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions.

Food quality, effects on health and sustainability today: a model case report.

PubMed

Borroni, Vittorio Natale; Fargion, Silvia; Mazzocchi, Alessandra; Giachetti, Marco; Lanzarini, Achille; Dall'Asta, Margherita; Scazzina, Francesca; Agostoni, Carlo

2017-02-01

The Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico is a five-century institution that, besides the unique clinical role in the center of Milan, may rely on benefactor donations such as fields and farming houses not far from the city, for a total of 8500 ha, all managed by the "Sviluppo Ca' Granda' Foundation". Presently, the main products of these fields are represented by rice and cow's milk. During the latest years, farmers and managers have developed a model of sustainable food production, with great attention to the product quality based on compositional analysis and functional nutritional characteristics. This experience represents a new holistic model of food production and consumption, taking great care of both sustainability and health.

Dairy farm cost efficiency in leading milk-producing regions in Poland.

PubMed

Sobczyński, T; Klepacka, A M; Revoredo-Giha, C; Florkowski, W J

2015-12-01

This paper examines the cost efficiency of dairy farms in 2 important regions of commercial milk production in Poland (i.e., Wielkopolskie and Podlaskie). Both regions gained importance following the market-driven resource allocation mechanism adopted after Poland's transition to the market economy in 1989 and accession to the European Union (EU) in 2004. The elimination of the dairy quota system in the EU in 2015 offers new expansion opportunities. The analysis of trends in cow numbers, milk production, and yield per cow shows different patterns of expansion of the dairy sector in the 2 regions. We selected dairy farm data from the Farm Accounts Data Network database for both regions and applied the cost frontier estimation model to calculate the relative cost-efficiency index for the period 2004 to 2009. The indexes compare each farm in the sample to the most efficient dairy farm in each region separately. Additionally, the top 5% of dairy farms with the highest relative cost efficiency index from each region were compared in terms of production costs with published results from a study using the representative farm approach. The comparison of results from 2 different studies permits a conclusion that Wielkopolskie and Podlaskie dairy farms are able to compete with farms from the 4 largest milk-producing countries in the EU. Although both regions can improve yields per cow, especially Podlaskie, both regions are likely to take advantage of the expansion opportunities offered by the 2015 termination of the milk quota system. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Canadian Whole-Farm Model Holos - Development, Stakeholder Involvement, and Model Application

NASA Astrophysics Data System (ADS)

Kroebel, R.; Janzen, H.; Beauchemin, K. A.

2017-12-01

Agriculture and Agri-Food Canada's Holos model, based mostly on emission factors, aims to explore the effect of management on Canadian whole-farm greenhouse gas emissions. The model includes 27 commonly grown annual and perennial crops, summer fallow, grassland, and 8 types of tree plantings, along with beef, dairy, sheep, swine and other livestock or poultry operations. Model outputs encompass net emissions of CO2, CH4, and N2O (in CO2 equivalents), calculated for various farm components. Where possible, algorithms are drawn from peer-reviewed publications. For consistency, Holos is aligned with the Canadian sustainability indicator and national greenhouse gas inventory objectives. Although primarily an exploratory tool for research, the model's design makes it accessible and instructive also to agricultural producers, educators, and policy makers. Model development, therefore, proceeds iteratively, with extensive stakeholder feedback from training sessions or annual workshops. To make the model accessible to diverse users, the team developed a multi-layered interface, with general farming scenarios for general use, but giving access to detailed coefficients and assumptions to researchers. The model relies on extensive climate, soil, and agronomic databases to populate regionally-applicable default values thereby minimizing keyboard entries. In an initial application, the model was used to assess greenhouse gas emissions from the Canadian beef production system; it showed that enteric methane accounted for 63% of total GHG emissions and that 84% of emissions originated from the cow-calf herd. The model further showed that GHG emission intensity per kg beef, nationally, declined by 14% from 1981 to 2011, owing to gains in production efficiency. Holos is now being used to consider further potential advances through improved rations or other management options. We are now aiming to expand into questions of grazing management, and are developing a novel carbon modelling approach based on the ICBM model. Also under development are sub-models to predict ammonia volatilization and water budgets. Development of Holos is expected to continue, forging an interactive link between ongoing research and the interests of stakeholders in an ever-changing agricultural environment.

Dutch dairy farms after milk quota abolition: Economic and environmental consequences of a new manure policy.

PubMed

Klootwijk, C W; Van Middelaar, C E; Berentsen, P B M; de Boer, I J M

2016-10-01

The abolition of the Dutch milk quota system has been accompanied by the introduction of a new manure policy to limit phosphate production (i.e., excretion via manure) on expanding dairy farms. The objective of this study was to evaluate the effect of these recent policy changes on the farm structure, management, labor income, nitrogen and phosphate surpluses, and greenhouse gas emissions of an average Dutch dairy farm. The new manure policy requires that any increase in phosphate production be partly processed and partly applied to additional farmland. In addition, phosphate quotas have been introduced. Herein, we used a whole-farm optimization model to simulate an average farm before and after quota abolition and introduction of the new manure policy. The objective function of the model maximized labor income. We combined the model with a farm nutrient balance and life-cycle assessment to determine environmental impact. Based on current prices, increasing the number of cows after quota abolition was profitable until manure processing or additional land was required to comply with the new manure policy. Manure processing involved treatment so that phosphate was removed from the national manure market. Farm intensity in terms of milk per hectare increased by about 4%, from 13,578kg before quota abolition to 14,130kg after quota abolition. Labor income increased by €505/yr. When costs of manure processing decreased from €13 to €8/t of manure or land costs decreased from €1,187 to €573/ha, farm intensity could increase up to 20% until the phosphate quota became limiting. Farms that had already increased their barn capacity to prepare for expansion after milk quota abolition could benefit from purchasing extra phosphate quota to use their full barn capacity. If milk prices increased from €355 to €420/t, farms could grow unlimited, provided that the availability of external inputs such as labor, land, barn capacity, feed, and phosphate quota at current prices were also unlimited. The milk quota abolition, accompanied by a new manure policy, will slightly increase nutrient losses per hectare, due to an increase in farm intensity. Greenhouse gas emissions per unit of milk will hardly change, so at a given milk production per cow, total greenhouse gas emissions will increase linearly with an increase in the number of cows. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Mukhabarah as Sharia Financing Model in Beef Cattle Farm Entrepise

NASA Astrophysics Data System (ADS)

Asnawi, A.; Amrawaty, A. A.; Nirwana

2018-02-01

Financing constraints on beef cattle farm nowadays have received attention by the government through distributed various assistance programs and program loans through implementing banks. The existing financing schemes are all still conventional yet sharia-based. The purpose of this research is to formulate financing pattern for sharia beef cattle farm. A qualitative and descriptive approach is used to formulate the pattern by considering the profit-sharing practices of the beef cattle farmers. The results of this study have formulated a financing pattern that integrates government, implementing banks, beef cattle farmers group and cooperative as well as breeders as its members. This pattern of financing is very accommodating of local culture that develops in rural communities. It is expected to be an input, especially in formulating a business financing policy Sharia-based beef cattle breeding.

Description and typology of intensive Chios dairy sheep farms in Greece.

PubMed

Gelasakis, A I; Valergakis, G E; Arsenos, G; Banos, G

2012-06-01

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

[Epidemiological and financial considerations for the control of Neospora caninum on Swiss dairy farms].

PubMed

Häsler, B; Stärk, K; Gottstein, B; Reist, M

2008-06-01

Neospora caninum is widely recognized as one of the most important abortifacients in cattle and causes substantial financial losses to bovine livestock production. This study aimed to calculate the losses caused by N. caninum on Swiss dairy farms and to evaluate the efficacy and profitability of the control strategies culling, not breeding replacements and chemotherapy of calves on farm level. Three different farm sizes with high, medium and low herd prevalences were defined. Epidemiological and financial models were used to simulate the effect of control strategies on the prevalence over time and to perform a cost-benefit analysis. The median annual losses on farm level ranged between CHF 3094.- (= Euro 1875; 60 dairy cattle, high prevalence) and CHF 134.- (= Euro 81; 15 dairy cattle, low prevalence). Culling of animals that had any abortion or a N. caninum abortion, or not breeding replacements from such animals, respectively, were neither effective nor profitable. Only the strategy "not breeding replacements from N. caninum seropositive cows" on farms with a high prevalence was financially attractive. The strategy "chemotherapy of calves" should be re-evaluated as soon as new data regarding the efficacy of treatment and a corresponding protocol have been scientifically validated.

Measuring and explaining multi-directional inefficiency in the Malaysian dairy industry.

PubMed

Mohd Suhaimi, Nurul Aisyah Binti; de Mey, Yann; Oude Lansink, Alfons

2017-01-01

The purpose of this paper is to measure the technical inefficiency of dairy farms and subsequently investigate the factors affecting technical inefficiency in the Malaysian dairy industry. This study uses multi-directional efficiency analysis to measure the technical inefficiency scores on a sample of 200 farm observations and single-bootstrap truncated regression model to define factors affecting technical inefficiency. Managerial and program inefficiency scores are presented for intensive and semi-intensive production systems. The results reveal marked differences in the inefficiency scores across inputs and between production systems. Intensive systems generally have lowest managerial and program inefficiency scores in the Malaysian dairy farming sector. Policy makers could use this information to advise dairy farmers to convert their farming system to the intensive system. The results suggest that the Malaysian Government should redefine its policy for providing farm finance and should target young farmers when designing training and extension programs in order to improve the performance of the dairy sector. The existing literature on Southeast Asian dairy farming has neither focused on investigating input-specific efficiency nor on comparing managerial and program efficiency. This paper aims to fill this gap.

Risk factors for infection with highly pathogenic influenza A virus (H5N1) in commercial chickens in Bangladesh.

PubMed

Biswas, P K; Christensen, J P; Ahmed, S S U; Barua, H; Das, A; Rahman, M H; Giasuddin, M; Hannan, A S M A; Habib, A M; Debnath, N C

2009-06-13

A matched case-control study was carried out to identify risk factors for highly pathogenic avian influenza A virus (subtype H5N1) infection in commercial chickens in Bangladesh. A total of 33 commercial farms diagnosed with H5N1 before September 9, 2007, were enrolled as cases, and 99 geographically matched unaffected farms were enrolled as control farms. Farm data were collected using a pretested questionnaire, and analysed by matched-pair analysis and multivariate conditional logistic regression. Two factors independently and positively associated with H5N1 infection remained in the final model. They were 'farm accessible to feral and wild animals' (odds ratio [OR] 5.71, 95 per cent confidence interval [CI] 1.81 to 18.0, P=0.003) and 'footbath at entry to farm/shed' (OR 4.93, 95 per cent CI 1.61 to 15.1, P=0.005). The use of a designated vehicle for sending eggs to a vendor or market appeared to be a protective factor (OR 0.14, 95 per cent CI 0.02 to 0.88, P=0.036).

Power Flow Simulations of a More Renewable California Grid Utilizing Wind and Solar Insolation Forecasting

NASA Astrophysics Data System (ADS)

Hart, E. K.; Jacobson, M. Z.; Dvorak, M. J.

2008-12-01

Time series power flow analyses of the California electricity grid are performed with extensive addition of intermittent renewable power. The study focuses on the effects of replacing non-renewable and imported (out-of-state) electricity with wind and solar power on the reliability of the transmission grid. Simulations are performed for specific days chosen throughout the year to capture seasonal fluctuations in load, wind, and insolation. Wind farm expansions and new wind farms are proposed based on regional wind resources and time-dependent wind power output is calculated using a meteorological model and the power curves of specific wind turbines. Solar power is incorporated both as centralized and distributed generation. Concentrating solar thermal plants are modeled using local insolation data and the efficiencies of pre-existing plants. Distributed generation from rooftop PV systems is included using regional insolation data, efficiencies of common PV systems, and census data. The additional power output of these technologies offsets power from large natural gas plants and is balanced for the purposes of load matching largely with hydroelectric power and by curtailment when necessary. A quantitative analysis of the effects of this significant shift in the electricity portfolio of the state of California on power availability and transmission line congestion, using a transmission load-flow model, is presented. A sensitivity analysis is also performed to determine the effects of forecasting errors in wind and insolation on load-matching and transmission line congestion.

Farmers and Bankers Are Interested in F.B.P.A. (Farm Business Planning and Analysis)

ERIC Educational Resources Information Center

Borton, John L.

1974-01-01

A successful Farm Business Planning and Analysis program is being taught by the Upper Sandusky, Ohio, Vocational Agriculture Department fo farm operators, farm couples, bankers, and vocational agriculture teachers and students. The F.B.P.A. program consists of developing a record system, summarizing and analyzing the system, and planning future…

Comparing crop rotations between organic and conventional farming.

PubMed

Barbieri, Pietro; Pellerin, Sylvain; Nesme, Thomas

2017-10-23

Cropland use activities are major drivers of global environmental changes and of farming system resilience. Rotating crops is a critical land-use driver, and a farmers' key strategy to control environmental stresses and crop performances. Evidence has accumulated that crop rotations have been dramatically simplified over the last 50 years. In contrast, organic farming stands as an alternative production way that promotes crop diversification. However, our understanding of crop rotations is surprisingly limited. In order to understand if organic farming would result in more diversified and multifunctional landscapes, we provide here a novel, systematic comparison of organic-to-conventional crop rotations at the global scale based on a meta-analysis of the scientific literature, paired with an independent analysis of organic-to-conventional land-use. We show that organic farming leads to differences in land-use compared to conventional: overall, crop rotations are 15% longer and result in higher diversity and evener crop species distribution. These changes are driven by a higher abundance of temporary fodders, catch and cover-crops, mostly to the detriment of cereals. We also highlighted differences in organic rotations between Europe and North-America, two leading regions for organic production. This increased complexity of organic crop rotations is likely to enhance ecosystem service provisioning to agroecosystems.

Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Xu, Pao; Yang, Runqing

2018-02-01

To genetically analyse growth traits in genetically improved farmed tilapia (GIFT), the body weight (BWE) and main morphological traits, including body length (BL), body depth (BD), body width (BWI), head length (HL) and length of the caudal peduncle (CPL), were measured six times in growth duration on 1451 fish from 45 mixed families of full and half sibs. A random regression model (RRM) was used to model genetic changes of the growth traits with days of age and estimate the heritability for any growth point and genetic correlations between pairwise growth points. Using the covariance function based on optimal RRMs, the heritabilities were estimated to be from 0.102 to 0.662 for BWE, 0.157 to 0.591 for BL, 0.047 to 0.621 for BD, 0.018 to 0.577 for BWI, 0.075 to 0.597 for HL and 0.032 to 0.610 for CPL between 60 and 140 days of age. All genetic correlations exceeded 0.5 between pairwise growth points. Moreover, the traits at initial days of age showed less correlation with those at later days of age. With phenotypes observed repeatedly, the model choice showed that the optimal RRMs could more precisely predict breeding values at a specific growth time than repeatability models or multiple trait animal models, which enhanced the efficiency of selection for the BWE and main morphological traits.

Characterization and typification of small ruminant farms providing fuelbreak grazing services for wildfire prevention in Andalusia (Spain).

PubMed

Mena, Y; Ruiz-Mirazo, J; Ruiz, F A; Castel, J M

2016-02-15

Several wildfire prevention programs in Spain are using grazing livestock to maintain fuelbreaks with low levels of biomass. Even though shepherds are remunerated for these services, many of their farms are hardly viable in the current socio-economic context. By analyzing 54 small ruminant farms participating in the Grazed Fuelbreak Network in Andalusia (southern Spain), this research aimed to identify the main types and characteristics of such farms and, considering the challenges they are facing, propose strategies to improve both their economic viability and their effectiveness in fuelbreak grazing. Based on data collected through a survey on key farm management aspects, a multivariate analysis was performed and four main types of farm were identified: two clusters of dairy goat farms and two composed mostly of meat-purpose sheep farms. Farms in all clusters could benefit from improvements in the feeding and reproductive management of livestock, either to enhance their productivity or to make better use of the pasture resources available. Dairy goat farms remain more dependent on external animal feed to ensure a better lactation, therefore they should either diminish their workforce costs per animal or sell transformed products directly to consumers to improve their economic viability. Best fuelbreak grazing results were related to larger flocks combining sheep and goats, lower ratios of fuelbreak surface area per animal, and longer (year-long) grazing periods on fuelbreaks. Therefore, such farm features and adjusted fuelbreak assignments should be favored in wildfire prevention programs using grazing services. Copyright © 2015 Elsevier B.V. All rights reserved.

"Advances in Coupled Air Quality, Farm Management and ...

EPA Pesticide Factsheets

A cropland farm management modeling system for regional air quality and field-scale applications of bi-directional ammonia exchange was presented at ITM XXI. The goal of this research is to improve estimates of nitrogen deposition to terrestrial and aquatic ecosystems and ambient ammonium aerosol particle concentrations injurious to human health. These concepts have been implemented and have been released as options in CMAQ 5.01. This presentation will summarize the integration of these two models and will present model performance results relative to wet deposition measurements, ambient ammonium aerosol and ambient ammonia observations. Results indicate a shift in the timing of current U.S. agricultural emission inventories and improved CMAQ model performance. Comparison to annual wet deposition observations suggests remaining bias may be attributable primarily to precipitation model errors. Preliminary results of CMAQ deposition and ambient ammonia response to interannual variability in farm management activities will also be presented. The USEPA Office of Air and Radiation is currently considering the recommendation of the coupled model for use in standard setting activities and applications are being developed in collaboration with USEPA Office of Water and Regional Offices. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the envi

Multiscale effects of management, environmental conditions, and land use on nitrate leaching in dairy farms.

PubMed

Oenema, Jouke; Burgers, Saskia; Verloop, Koos; Hooijboer, Arno; Boumans, Leo; ten Berge, Hein

2010-01-01

Nitrate leaching in intensive grassland- and silage maize-based dairy farming systems on sandy soil is a main environmental concern. Here, statistical relationships are presented between management practices and environmental conditions and nitrate concentration in shallow groundwater (0.8 m depth) at farm, field, and point scales in The Netherlands, based on data collected in a participatory approach over a 7-yr period at one experimental and eight pilot commercial dairy farms on sandy soil. Farm milk production ranged from 10 to 24 Mg ha(-1). Soil and hydrological characteristics were derived from surveys and weather conditions from meteorological stations. Statistical analyses were performed with multiple regression models. Mean nitrate concentration at farm scale decreased from 79 mg L(-1) in 1999 to 63 in 2006, with average nitrate concentration in groundwater decreasing under grassland but increasing under maize land over the monitoring period. The effects of management practices on nitrate concentration varied with spatial scale. At farm scale, nitrogen surplus, grazing intensity, and the relative areas of grassland and maize land significantly contributed to explaining the variance in nitrate concentration in groundwater. Mean nitrate concentration was negatively correlated to the concentration of dissolved organic carbon in the shallow groundwater. At field scale, management practices and soil, hydrological, and climatic conditions significantly contributed to explaining the variance in nitrate concentration in groundwater under grassland and maize land. We conclude that, on these intensive dairy farms, additional measures are needed to comply with the European Union water quality standard in groundwater of 50 mg nitrate L(-1). The most promising measures are omitting fertilization of catch crops and reducing fertilization levels of first-year maize in the rotation.

Managing variability in decision making in swine growing-finishing units.

PubMed

Agostini, Piero da Silva; Manzanilla, Edgar Garcia; de Blas, Carlos; Fahey, Alan G; da Silva, Caio Abercio; Gasa, Josep

2015-01-01

Analysis of data collected from pig farms may be useful to understand factors affecting pig health and productive performance. However, obtaining these data and drawing conclusions from them can be done at different levels and presents several challenges. In the present study, information from 688 batches of growing-finishing (GF) pigs (average initial and final body weight of 19.1 and 108.5 kg respectively) from 404 GF farms integrated in 7 companies was obtained between July 2008 and July 2010 in Spain by survey. Management and facility factors associated with feed conversion ratio (FCR) and mortality were studied by multiple linear regression analysis in each single company (A to G) and in an overall database (OD). Factors studied were geographic location of the farm, trimester the pigs entered the farm, breed of sire and sex segregation in pens (BREGENSEG), use of circovirus vaccine, number of origins the pigs were obtained from, age of the farm, percentage of slatted floor, type of feeder, drinker and ventilation, number of phases and form of feed, antibiotic administration system, water source, and number and initial weight of pigs. In two or more companies studied and/or in OD, the trimester when pigs were placed in the farm, BREGENSEG, number of origins of the pigs, age of the farm and initial body weight were factors associated with FCR. Regarding mortality, trimester of placement, number of origins of the pigs, water source in the farm, number of pigs placed and the initial body weight were relevant factors. Age of the farm, antibiotic administration system, and water source were only provided by some of the studied companies and were not included in the OD model, however, when analyzed in particular companies these three variables had an important effect and may be variables of interest in companies that do not record them. Analysing data collected from farms at different levels helps better understand factors associated with productive performance of pig herds. Out of the studied factors trimester of placement and number of origins of the pigs were the most relevant factors associated with FCR and mortality.

Differences in Lepeophtheirus salmonis abundance levels on Atlantic salmon farms in the Broughton Archipelago, British Columbia, Canada.

PubMed

Saksida, S; Karreman, G A; Constantine, J; Donald, A

2007-06-01

Sea lice data collected from Atlantic salmon farms in the Broughton Archipelago between 2003 and 2005 were examined for inter-regional differences in mobile Lepeophtheirus salmonis (Krøyer) abundance using the generalized linear model procedure. Factors such as age of the salmon populations, location of farms and time of year had a significant effect on the abundance of the mobile stages of L. salmonis whereas water temperature and salinity did not. Separate evaluation of SLICE treatment data found no significant difference in treatment frequency among the areas but did show that there were significantly lower numbers of farm treatments during the summer months when compared with other seasons. The role of environment and wild fish in influencing sea lice abundance on the farmed salmon is discussed. The findings suggest that effective management programmes for sea lice should not only be based on geographical location but should take into account other factors which could influence lice abundance levels.

Drivers and risk factors for circulating African swine fever virus in Uganda, 2012-2013.

PubMed

Kabuuka, T; Kasaija, P D; Mulindwa, H; Shittu, A; Bastos, A D S; Fasina, F O

2014-10-01

We explored observed risk factors and drivers of infection possibly associated with African swine fever (ASF) epidemiology in Uganda. Representative sub-populations of pig farms and statistics were used in a case-control model. Indiscriminate disposal of pig viscera and waste materials after slaughter, including on open refuse dumps, farm-gate buyers collecting pigs and pig products from within a farm, and retention of survivor pigs were plausible risk factors. Wire mesh-protected windows in pig houses were found to be protective against ASF infection. Sighting engorged ticks on pigs, the presence of a lock for each pig pen and/or a gate at the farm entrance were significantly associated with infection/non-infection; possible explanations were offered. Strict adherence to planned within-farm and community-based biosecurity, and avoidance of identified risk factors is recommended to reduce infection. Training for small-scale and emerging farmers should involve multidimensional and multidisciplinary approaches to reduce human-related risky behaviours driving infection. Copyright © 2014. Published by Elsevier Ltd.

Integrated Farm System Model Version 4.1 and Dairy Gas Emissions Model Version 3.1 software release and distribution

USDA-ARS?s Scientific Manuscript database

Animal facilities are significant contributors of gaseous emissions including ammonia (NH3) and nitrous oxide (N2O). Previous versions of the Integrated Farm System Model (IFSM version 4.0) and Dairy Gas Emissions Model (DairyGEM version 3.0), two whole-farm simulation models developed by USDA-ARS, ...

Disease spread models to estimate highly uncertain emerging diseases losses for animal agriculture insurance policies: an application to the U.S. farm-raised catfish industry.

PubMed

Zagmutt, Francisco J; Sempier, Stephen H; Hanson, Terril R

2013-10-01

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks. © 2013 Society for Risk Analysis.

Turbulent flow and scalar transport in a large wind farm

NASA Astrophysics Data System (ADS)

Porte-Agel, F.; Markfort, C. D.; Zhang, W.

2012-12-01

Wind energy is one of the fastest growing sources of renewable energy world-wide, and it is expected that many more large-scale wind farms will be built and cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer and converting it to electricity, wind farms may affect the transport of momentum, heat, moisture and trace gases (e.g. CO_2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interaction is complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics, and atmospheric thermal stability. A wind farm of finite length may be modeled as an added roughness or as a canopy in large-scale weather and climate models. However, it is not clear which analogy is physically more appropriate. Also, surface scalar flux is affected by wind farms and needs to be properly parameterized in meso-scale and/or high-resolution numerical models. Experiments involving model wind farms, with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a thermally-controlled boundary-layer wind tunnel. A neutrally stratified turbulent boundary layer was developed with a surface heat source. Measurements of the turbulent flow and fluxes over and through the wind farm were made using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors far within the quasi-developed region of the wind-farm. The turbulence statistics exhibit similar properties to those of canopy-type flows, but retain some characteristics of surface-layer flows in a limited region above the wind farms as well. The flow equilibrates faster and the overall momentum absorption is higher for the staggered compared to the aligned farm, which is consistent with canopy scaling and leads to a larger effective roughness. Although the overall surface heat flux change produced by the wind farms is found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero change for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. This comprehensive first wind-tunnel dataset on turbulent flow and scalar transport in wind farms will be further used to develop and validate new parameterizations of surface fluxes in numerical models.