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.

Estimating the sensitivity of passive surveillance for HPAI H5N1 in Bayelsa state, Nigeria.

PubMed

Ojimelukwe, Agatha E; Prakarnkamanant, Apisit; Rushton, Jonathan

2016-07-01

This study identified characteristics of poultry farming with a focus on practices that affect the detection of HPAI; and estimated the system sensitivity of passive surveillance for HPAI H5N1 in commercial and backyard chicken farms in Bayelsa-State, Nigeria. Field studies were carried out in Yenegoa and Ogbia local government areas in Bayelsa state. Willingness to report HPAI was highest in commercial poultry farms (13/13) than in Backyard farms (8/13). Poor means of dead bird disposal was common to both commercial and backyard farms. Administering some form of treatment to sick birds without prior consultation with a professional was higher in backyard farms (8/13) than in commercial farms (4/13). Consumption of sick birds was reported in 4/13 backyard farms and sale of dead birds was recorded in one commercial farm. The sensitivity of passive surveillance for HPAI was assessed using scenario tree modelling. A scenario tree model was developed and applied to estimate the sensitivity, i.e. the probability of detecting one or more infected chicken farms in Bayelsa state at different levels of disease prevalence. The model showed a median sensitivity of 100%, 67% and 23% for detecting HPAI by passive surveillance at a disease prevalence of 0.1%, a minimum of 10 and 3 infected poultry farms respectively. Passive surveillance system sensitivity at a design prevalence of 10 infected farms is increasable up to 86% when the disease detection in backyard chicken farms is enhanced. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Analysis and model on space-time characteristics of wind power output based on the measured wind speed data

NASA Astrophysics Data System (ADS)

Shi, Wenhui; Feng, Changyou; Qu, Jixian; Zha, Hao; Ke, Dan

2018-02-01

Most of the existing studies on wind power output focus on the fluctuation of wind farms and the spatial self-complementary of wind power output time series was ignored. Therefore the existing probability models can’t reflect the features of power system incorporating wind farms. This paper analyzed the spatial self-complementary of wind power and proposed a probability model which can reflect temporal characteristics of wind power on seasonal and diurnal timescales based on sufficient measured data and improved clustering method. This model could provide important reference for power system simulation incorporating wind farms.

Assessing regional differences in nitrogen losses from U.S. dairy farms using the integrated farm systems model

USDA-ARS?s Scientific Manuscript database

Nitrogen (N) enters and leaves a dairy production system through many pathways and in many forms: undergoing numerous transformations as it passes from feed to animal to milk or manure and back again. Due to the complexity of the dairy system, estimates of N flows and losses require the use of model...

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.

Modeling emissions of volatile organic compounds from silage storages and feed lanes

USDA-ARS?s Scientific Manuscript database

An initial volatile organic compound (VOC) emission model for silage sources, developed using experimental data from previous studies, was incorporated into the Integrated Farm System Model (IFSM), a whole-farm simulation model used to assess the performance, environmental impacts, and economics of ...

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

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.

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.

Advanced Modeling System for Optimization of Wind Farm Layout and Wind Turbine Sizing Using a Multi-Level Extended Pattern Search Algorithm

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

DuPont, Bryony; Cagan, Jonathan; Moriarty, Patrick

This paper presents a system of modeling advances that can be applied in the computational optimization of wind plants. These modeling advances include accurate cost and power modeling, partial wake interaction, and the effects of varying atmospheric stability. To validate the use of this advanced modeling system, it is employed within an Extended Pattern Search (EPS)-Multi-Agent System (MAS) optimization approach for multiple wind scenarios. The wind farm layout optimization problem involves optimizing the position and size of wind turbines such that the aerodynamic effects of upstream turbines are reduced, which increases the effective wind speed and resultant power at eachmore » turbine. The EPS-MAS optimization algorithm employs a profit objective, and an overarching search determines individual turbine positions, with a concurrent EPS-MAS determining the optimal hub height and rotor diameter for each turbine. Two wind cases are considered: (1) constant, unidirectional wind, and (2) three discrete wind speeds and varying wind directions, each of which have a probability of occurrence. Results show the advantages of applying the series of advanced models compared to previous application of an EPS with less advanced models to wind farm layout optimization, and imply best practices for computational optimization of wind farms with improved accuracy.« less

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

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

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

2017-01-01

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

How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?

PubMed

Hutchings, N J; Özkan Gülzari, Ş; de Haan, M; Sandars, D

2018-01-09

The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.

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.

Effect of inter-annual variability in pasture growth and irrigation response on farm productivity and profitability based on biophysical and farm systems modelling.

PubMed

Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel

2016-09-15

Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

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.

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.

Spatial organization of agricultural landscape, farming activities and hydrological risk assessment

NASA Astrophysics Data System (ADS)

Viaud, V.; Merot, P.

2003-04-01

Agriculture intensification is considered as a major cause of water pollution since it has gone both with an increasing use of fertilisers and significant changes in land-use patterns. Among the prescriptions for pollution control, the management of buffer zones at the landscape scale is supported by the environmental policies, but often without consideration of the systems of human activities they are aimed at. Agricultural landscapes, with fields potentially source of pollution and buffer zones, are spatially organized and managed by farming activities. In a perspective of sustainable management, an integrating approach of environmental issues and farming activities is thus required. This approach was applied to bocage landscapes (landscapes with cultivated fields surrounded by hedgerow systems) in Brittany (Western France). Bocage landscapes are frequently encountered, especially in Europe, and many studies put forward their hydrological and hydrochemical buffer functions. Those results provide informations on the link between spatial organization of hedgerow systems and their environmental effectiveness. They enable to design models of functional bocage landscapes. The objective of this work was to pick out, among those theoretical models, the models compatible with the farming activities. The results will be presented and the additional constraints for the farming systems created by a functional landscape, from a hydrological and hydrochemical perspective, will be discussed.

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.

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

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

Volume sharing of reservoir water

NASA Astrophysics Data System (ADS)

Dudley, Norman J.

1988-05-01

Previous models optimize short-, intermediate-, and long-run irrigation decision making in a simplified river valley system characterized by highly variable water supplies and demands for a single decision maker controlling both reservoir releases and farm water use. A major problem in relaxing the assumption of one decision maker is communicating the stochastic nature of supplies and demands between reservoir and farm managers. In this paper, an optimizing model is used to develop release rules for reservoir management when all users share equally in releases, and computer simulation is used to generate an historical time sequence of announced releases. These announced releases become a state variable in a farm management model which optimizes farm area-to-irrigate decisions through time. Such modeling envisages the use of growing area climatic data by the reservoir authority to gauge water demand and the transfer of water supply data from reservoir to farm managers via computer data files. Alternative model forms, including allocating water on a priority basis, are discussed briefly. Results show lower mean aggregate farm income and lower variance of aggregate farm income than in the single decision-maker case. This short-run economic efficiency loss coupled with likely long-run economic efficiency losses due to the attenuated nature of property rights indicates the need for quite different ways of integrating reservoir and farm management.

Weather Research and Forecasting model simulation of an onshore wind farm: assessment against LiDAR and SCADA data

NASA Astrophysics Data System (ADS)

Santoni, Christian; Garcia-Cartagena, Edgardo J.; Zhan, Lu; Iungo, Giacomo Valerio; Leonardi, Stefano

2017-11-01

The integration of wind farm parameterizations into numerical weather prediction models is essential to study power production under realistic conditions. Nevertheless, recent models are unable to capture turbine wake interactions and, consequently, the mean kinetic energy entrainment, which are essential for the development of power optimization models. To address the study of wind turbine wake interaction, one-way nested mesoscale to large-eddy simulation (LES) were performed using the Weather Research and Forecasting model (WRF). The simulation contains five nested domains modeling the mesoscale wind on the entire North Texas Panhandle region to the microscale wind fluctuations and turbine wakes of a wind farm located at Panhandle, Texas. The wind speed, direction and boundary layer profile obtained from WRF were compared against measurements obtained with a sonic anemometer and light detection and ranging system located within the wind farm. Additionally, the power production were assessed against measurements obtained from the supervisory control and data acquisition system located in each turbine. Furthermore, to incorporate the turbines into very coarse LES, a modification to the implementation of the wind farm parameterization by Fitch et al. (2012) is proposed. This work was supported by the NSF, Grants No. 1243482 (WINDINSPIRE) and IIP 1362033 (WindSTAR), and TACC.

Economic assessments of potato production systems in Maine

USDA-ARS?s Scientific Manuscript database

Using an integrated enterprise and whole-farm budget model for a 324-ha medium-sized potato farm, the profitability of potatoes grown in combination with fifteen common potato rotation crops in Maine are evaluated. Enterprise budgets for all sixteen crops are calculated while a whole-farm budget syn...

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.

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.

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.

Guest Editorial Modeling and Advanced Control of Wind Turbines/Wind Farms

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

Hu, J.; Hou, Y.; Zhu, Z.

2017-09-01

The papers in this special section brings together papers focused on the recent advancements and breakthroughs in the technology of modeling and enhanced active/reactive power control of wind power conversion systems, ranging from components of wind turbines to wind farms.

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.

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.

Local infestation or long-distance migration? The seasonal recolonization of dairy farms by Stomoxys calcitrans (Diptera: Muscidae) in south central Ontario, Canada.

PubMed

Beresford, D V; Sutcliffe, J F

2009-04-01

Stable fly (Diptera: Muscidae) populations in south central Ontario, Canada, first occur on dairy farms in late spring, grow exponentially throughout the summer, and are frozen back each autumn. We examined the extent of overwinter persistence on 22 dairy farms in a 55- by 60-km region north of Lake Ontario that spans four climatic zones. Our overwintering sampling of larval habitat identified three farms located in the southern section of the study region as potential overwintering refugia. Using sticky trap catches to identify the timing of first spring appearance at each farm, we then tested two models of how local farm populations are reestablished annually: 1) stable flies disperse from local climatic refuges and colonize neighboring farms (the local source model); and 2) stable flies are carried into the study region by frontal weather systems (the distant source model). The timing of when stable flies first occurred at these farms supported a local source of dispersing colonists from a small proportion of local refuge farms. We discuss our results in terms of how yearly fluctuation in climate would affect refuge farm density in the region and how this, in turn, would shift the recolonization dynamic. Implications for controlling stable flies also are discussed.

Nitrogen food-print: N use and N cascade from livestock systems in relation to pork, beef and milk supply to Paris

NASA Astrophysics Data System (ADS)

Chatzimpiros, P.; Barles, S.

2012-02-01

A bottom-up approach is constructed to determine N losses from livestock farming systems and to relate these losses to the supply of fresh milk, pig and beef to Paris. First, the three products are expressed in terms of their nitrogen content; then, their fodder equivalent is determined by modelling feed formulas for swine, beef and dairy cows to meet their energy and protein requirements. Fodder deficits in livestock farms are determined by comparing the nutrient requirements of the livestock with the fodder production on the livestock farms. This allowed determining the geography of the livestock systems according to the imports of fodder to the livestock farms from external crop farms. Then we assessed the "farm-gate" N budgets in all crop and livestock farms of the entire livestock systems using data on total N fertilization, atmospheric deposition and manure management practices to finally derive N losses in relation to fodder cultivation and to manure management. Measured in N, the supply of milk, beef and pig to Paris sum 1.85 kg N/cap and the corresponding N losses from the farming systems total 8.9 kg N/cap. N losses per unit of product differ among the three livestock systems according to where and how the fodder is grown and to what densities the livestock is reared.

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.

Coupling dairy manure storage with injection to improve nitrogen management: whole-farm simulation using the integrated farm system Model

USDA-ARS?s Scientific Manuscript database

Application of livestock manure to farm soils represents a priority nutrient management concern in the Chesapeake Bay Watershed. Historically strong emphasis has been placed on adding manure storage to dairy operations, and, there has been recognition that manure application methods can be improved....

Emergy evaluation and economic analysis of three wetland fish farming systems in Nansi Lake area, China.

PubMed

Zhang, L X; Ulgiati, S; Yang, Z F; Chen, B

2011-03-01

Emergy and economic methods were used to evaluate and compare three fish production models, i.e., cage fish farming system, pond intensive fish rearing system and semi-natural extensive pond fish rearing system, in Nansi Lake area in China in the year 2007. The goal of this study was to understand the benefits and driving forces of selected fish production models from ecological and economic points of view. The study considered input structure, production efficiency, environmental impacts, economic viability and sustainability. Results show that the main difference among the three production systems was the emergy cost for fish feed associated with their feeding system, i.e., feeding on natural biomass such as plankton and grass or on commercial feedstock. As indicated by EYR, ELR and ESI, it can be clearly shown that the intensive production model with commercial feed is not a sustainable pattern. However, the point is that more environmentally sound patterns do not seem able to provide a competitive net profit in the short run. The intensive pond fish farming system had a net profit of 2.57E+03 $/ha, much higher than 1.27E+03 $/ha for cage fish farming system and slightly higher than 2.37E+03 $/ha for semi-natural fish farming system. With regard to the drivers of local farmer's decisions, the accessibility of land for the required use and investment ability determine the farmer's choice of the production model and the scale of operation, while other factors seem to have little effect. Theoretically, the development of environmentally sustainable production patterns, namely water and land conservation measures, greener feed as well as low waste systems is urgently needed, to keep production activities within the carrying capacity of ecosystems. Coupled emergy and economic analyses can provide better insight into the environmental and economic benefits of fish production systems and help solve the problems encountered during policy making. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

Trade-offs between pasture production and farmland bird conservation: exploration of options using a dynamic farm model.

PubMed

Sabatier, R; Teillard, F; Rossing, W A H; Doyen, L; Tichit, M

2015-05-01

In European grassland landscapes, grazing and mowing play a key role for the maintenance of high-quality habitats that host important bird populations. As grasslands are also key resources for cattle feeding, there is a need to develop management strategies that achieve the double objective of production and biodiversity conservation. The objective of this study was to use a modelling approach to generate recognisable patterns of bird dynamics in farms composed of different land use proportions, and to compare their production and ecological dimensions. We developed a dynamic model, which linked grassland management to bird population dynamics at the field and farm levels. The model was parameterised for two types of suckling farms corresponding to contrasting levels of grassland intensification and for two bird species of high conservation value. A viability algorithm was used to define and assess viable management strategies for production and ecological performance so as to draw the shape of the relationship between both types of performances for the two types of farms. Our results indicated that, at the farm level, there was a farming system effect with a negative and non-linear relationship linking performance. Improving bird population maintenance was less costly in extensive farms compared with intensive farms. At the field level, the model predicted the timing and intensity of land use, maximising either production or ecological performance. The results suggested that multi-objective grassland management would benefit from public policies that consider levels of organisation higher than the field level, such as the farm or the landscape.

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

Effects of irrigation water supply variations on limited resource farming in Conejos County, Colorado

NASA Astrophysics Data System (ADS)

Eckert, Jerry B.; Wang, Erda

1993-02-01

Farms in NE Conejos County, Colorado, are characterized by limited resources, uncertain surface flow irrigation systems, and mixed crop-livestock enterprise combinations which are dependent on public grazing resources. To model decision making on these farms, a linear program is developed stressing enterprise choices under conditions of multiple resource constraints. Differential access to grazing resources and irrigation water is emphasized in this research. Regarding the water resource, the model reflects farms situated alternatively on high-, medium-, and low-priority irrigation ditches within the Alamosa-La Jara river system, each with and without supplemental pumping. Differences are found in optimum enterprise mixes, net returns, choice of cropping technology, level of marketings, and other characteristics in response to variations in the availability of irrigation water. Implications are presented for alternative improvement strategies.

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.

Soil erosion measurements under organic and conventional land use treatments and different tillage systems using micro-scale runoff plots and a portable rainfall simulator

NASA Astrophysics Data System (ADS)

Seitz, Steffen; Goebes, Philipp; Song, Zhengshan; Wittwer, Raphaël; van der Heijden, Marcel; Scholten, Thomas

2015-04-01

Soil erosion is a major environmental problem of our time and negatively affects soil organic matter (SOM), aggregate stability or nutrient availability for instance. It is well known that agricultural practices have a severe influence on soil erosion by water. Several long-term field trials show that the use of low input strategies (e.g. organic farming) instead of conventional high-input farming systems leads to considerable changes of soil characteristics. Organic farming relies on crop rotation, absence of agrochemicals, green manure and weed control without herbicides. As a consequence, SOM content in the top soil layer is usually higher than on arable land under conventional use. Furthermore, the soil surface is better protected against particle detachment and overland flow due to a continuous vegetation cover and a well-developed root system increases soil stability. Likewise, tillage itself can cause soil erosion on arable land. In this respect, conservation and reduced tillage systems like No-Till or Ridge-Till provide a protecting cover from the previous year's residue and reduce soil disturbance. Many studies have been carried out on the effect of farming practices on soil erosion, but with contrasting results. To our knowledge, most of those studies rely on soil erosion models to calculate soil erosion rates and replicated experimental field measurement designs are rarely used. In this study, we performed direct field assessment on a farming system trial in Rümlang, Switzerland (FAST: Farming System and Tillage experiment Agroscope) to investigate the effect of organic farming practises and tillage systems on soil erosion. A portable single nozzle rainfall simulator and a light weight tent have been used with micro-scale runoff plots (0.4 m x 0.4 m). Four treatments (Conventional/Tillage, Conventional/No-Tillage, Organic/Tillage, Organic/Reduced-tillage) have been sampled with 8 replications each for a total of 32 runoff plots. All plots have been distributed randomly within the treatments. Linear mixed effect modelling was used to examine the effects of the treatments on sediment discharge and surface runoff. Results were compared with recent findings from erosion models and laboratory studies. Results show that sediment discharge is significantly higher (59 %, p=0.018) on conventional treatments (31.8 g/m2/h) than on organic treatments (20.0 g/m2/h). This finding supports results from several studies, which found soil erosion rates from 18 % to 184 % higher on conventional than on organic treatments. Under both farming systems, ploughed treatments show higher sediment discharge (conventional farming: 104 %, organic farming: 133 %, p=0.004) than treatments with reduced or no tillage. Runoff volume did not show significant effects in our treatments. An interaction between the farming practice and the tillage system could not be found, which strengthens the importance of both. With the help of a well-replicated micro-scale runoff plot design and a portable rainfall simulator we were able to gather reliable soil erosion data in situ in short term and without external parameterization. Our field assessment shows that organic farming and reduced tillage practices protect agricultural land best against soil erosion.

Projecting carbon footprint of Canadian dairy farms under future climate conditions with the integrated farm system model

USDA-ARS?s Scientific Manuscript database

Dairy farms are an important sector of Canadian agriculture, and there is an on-going effort to assess their environmental impact. In Canada, like many northern areas of the world, climate change is expected to increase agricultural productivity. This will likely come along with changes in environme...

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.

Evaluation in Appalachian pasture systems of the 1996 (update 2000) National Research Council model for weaning cattle.

PubMed

Whetsell, M S; Rayburn, E B; Osborne, P I

2006-05-01

This study was conducted to evaluate the accuracy of the National Research Council's (2000) Nutrient Requirements of Beef Cattle computer model when used to predict calf performance during on-farm pasture or dry-lot weaning and backgrounding. Calf performance was measured on 22 farms in 2002 and 8 farms in 2003 that participated in West Virginia Beef Quality Assurance Sale marketing pools. Calves were weaned on pasture (25 farms) or dry-lot (5 farms) and fed supplemental hay, haylage, ground shell corn, soybean hulls, or a commercial concentrate. Concentrates were fed at a rate of 0.0 to 1.5% of BW. The National Research Council (2000) model was used to predict ADG of each group of calves observed on each farm. The model error was measured by calculating residuals (the difference between predicted ADG minus observed ADG). Predicted animal performance was determined using level 1 of the model. Results show that, when using normal on-farm pasture sampling and forage analysis methods, the model error for ADG is high and did not accurately predict the performance of steers or heifers fed high-forage pasture-based diets; the predicted ADG was lower (P < 0.05) than the observed ADG. The estimated intake of low-producing animals was similar to the expected DMI, but for the greater-producing animals it was not. The NRC (2000) beef model may more accurately predict on-farm animal performance in pastured situations if feed analysis values reflect the energy value of the feed, account for selective grazing, and relate empty BW and shrunk BW to NDF.

Evaluation of a whole-farm model for pasture-based dairy systems.

PubMed

Beukes, P C; Palliser, C C; Macdonald, K A; Lancaster, J A S; Levy, G; Thorrold, B S; Wastney, M E

2008-06-01

In the temperate climate of New Zealand, animals can be grazed outdoors all year round. The pasture is supplemented with conserved feed, with the amount being determined by seasonal pasture growth, genetics of the herd, and stocking rate. The large number of factors that affect production makes it impractical and expensive to use field trials to explore all the farm system options. A model of an in situ-grazed pasture system has been developed to provide a tool for developing and testing novel farm systems; for example, different levels of bought-in supplements and different levels of nitrogen fertilizer application, to maintain sustainability or environmental integrity and profitability. It consists of a software framework that links climate information, on a daily basis, with dynamic, mechanistic component-models for pasture growth and animal metabolism, as well as management policies. A unique feature is that the component models were developed and published by other groups, and are retained in their original software language. The aim of this study was to compare the model, called the whole-farm model (WFM) with a farm trial that was conducted over 3 yr and in which data were collected specifically for evaluating the WFM. Data were used from the first year to develop the WFM and data from the second and third year to evaluate the model. The model predicted annual pasture production, end-of-season cow liveweight, cow body condition score, and pasture cover across season with relative prediction error <20%. Milk yield and milksolids (fat + protein) were overpredicted by approximately 30% even though both annual and monthly pasture and supplement intake were predicted with acceptable accuracy, suggesting that the metabolic conversion of feed to fat, protein, and lactose in the mammary gland needs to be refined. Because feed growth and intake predictions were acceptable, economic predictions can be made using the WFM, with an adjustment for milk yield, to test different management policies, alterations in climate, or the use of genetically improved animals, pastures, or crops.

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

PubMed

Capalbo, Susan M; Antle, John M; Seavert, Clark

2017-07-01

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

Modelling the interactions between C and N farm balances and GHG emissions from confinement dairy farms in northern Spain.

PubMed

Del Prado, A; Mas, K; Pardo, G; Gallejones, P

2013-11-01

There is world-wide concern for the contribution of dairy farming to global warming. However, there is still a need to improve the quantification of the C-footprint of dairy farming systems under different production systems and locations since most of the studies (e.g. at farm-scale or using LCA) have been carried out using too simplistic and generalised approaches. A modelling approach integrating existing and new sub-models has been developed and used to simulate the C and N flows and to predict the GHG burden of milk production (from the cradle to the farm gate) from 17 commercial confinement dairy farms in the Basque Country (northern Spain). We studied the relationship between their GHG emissions, and their management and economic performance. Additionally, we explored some of the effects on the GHG results of the modelling methodology choice. The GHG burden values resulting from this study (0.84-2.07 kg CO2-eq kg(-l) milk ECM), although variable, were within the range of values of existing studies. It was evidenced, however, that the methodology choice used for prediction had a large effect on the results. Methane from the rumen and manures, and N2O emissions from soils comprised most of the GHG emissions for milk production. Diet was the strongest factor explaining differences in GHG emissions from milk production. Moreover, the proportion of feed from the total cattle diet that could have directly been used to feed humans (e.g. cereals) was a good indicator to predict the C-footprint of milk. Not only were some other indicators, such as those in relation with farm N use efficiency, good proxies to estimate GHG emissions per ha or per kg milk ECM (C-footprint of milk) but they were also positively linked with farm economic performance. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic milking systems, farm size, and milk production.

PubMed

Rotz, C A; Coiner, C U; Soder, K J

2003-12-01

Automatic milking systems (AMS) offer relief from the demanding routine of milking. Although many AMS are in use in Europe and a few are used in the United States, the potential benefit for American farms is uncertain. A farm-simulation model was used to determine the long-term, whole-farm effect of implementing AMS on farm sizes of 30 to 270 cows. Highest farm net return to management and unpaid factors was when AMS were used at maximal milking capacity. Adding stalls to increase milking frequency and possibly increase production generally did not improve net return. Compared with new traditional milking systems, the greatest potential economic benefit was a single-stall AMS on a farm size of 60 cows at a moderate milk production level (8600 kg/cow). On other farm sizes using single-stall type robotic units, losses in annual net return of 0 dollars to 300 dollars/cow were projected, with the greatest losses on larger farms and at high milk production (10,900 kg/cow). Systems with one robot serving multiple stalls provided a greater net return than single-stall systems, and this net return was competitive with traditional parlors for 50- to 130-cow farm sizes. The potential benefit of AMS was improved by 100 dollars/cow per year if the AMS increased production an additional 5%. A 20% reduction in initial equipment cost or doubling milking labor cost also improved annual net return of an AMS by up to 100 dollars/cow. Annual net return was reduced by 110 dollars/cow, though, if the economic life of the AMS was reduced by 3 yr for a more rapid depreciation than that normally used with traditional milking systems. Thus, under current assumptions, the economic return for an AMS was similar to that of new parlor systems on smaller farms when the milking capacity of the AMS was well matched to herd size and milk production level.

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.

Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

NASA Astrophysics Data System (ADS)

Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

with information to improve their crop's vigor has been a major topic of interest. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, the efficiency of farming must increase to meet future food requirements and to make farming a sustainable occupation for the farmer. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The goal is to increase farm revenue by increasing crop yield and decreasing applications of costly chemical and water treatments. In addition, this methodology will decrease the environmental costs of farming, i.e., reduce air, soil, and water pollution. Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now available. Commercial satellite systems can image (multi-spectral) the Earth with a resolution of approximately 2.5 m. Variable precision dispensing systems using GPS are available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been formulated. Personal computers and internet access are in place in most farm homes and can provide a mechanism to periodically disseminate, e.g. bi-weekly, advice on what quantities of water and chemicals are needed in individual regions of the field. What is missing is a model that fuses the disparate sources of information on the current states of the crop and soil, and the remaining resource levels available with the decisions farmers are required to make. This must be a product that is easy for the farmer to understand and to implement. A "Constrained Optimization Feed-back Control Model" to fill this void will be presented. The objective function of the model will be used to maximize the farmer's profit by increasing yields while decreasing environmental costs and decreasing application of costly treatments. This model will incorporate information from remote sensing, in-situ weather sources, soil measurements, crop models, and tacit farmer knowledge of the relative productivity of the selected control regions of the farm to provide incremental advice throughout the growing season on water and chemical treatments. Genetic and meta-heuristic algorithms will be used to solve the constrained optimization problem that possesses complex constraints and a non-linear objective function. *

Evaluating mountain goat dairy systems for conversion to the organic model, using a multicriteria method.

PubMed

Mena, Y; Nahed, J; Ruiz, F A; Sánchez-Muñoz, J B; Ruiz-Rojas, J L; Castel, J M

2012-04-01

Organic farming conserves natural resources, promotes biodiversity, guarantees animal welfare and obtains healthy products from raw materials through natural processes. In order to evaluate possibilities of increasing organic animal production, this study proposes a farm-scale multicriteria method for assessing the conversion of dairy goat systems to the organic model. In addition, a case study in the Northern Sierra of Seville, southern Spain, is analysed. A consensus of expert opinions and a field survey are used to validate a list of potential indicators and issues for assessing the conversion, which consider not only the European Community regulations for organic livestock farming, but also agroecological principles. As a result, the method includes 56 variables integrated in nine indicators: Nutritional management, Sustainable pasture management, Soil fertility and contamination, Weed and pest control, Disease prevention, Breeds and reproduction, Animal welfare, Food safety and Marketing and management. The nine indicators are finally integrated in a global index named OLPI (Organic Livestock Proximity Index). Application of the method to a case study with 24 goat farms reveals an OLPI value of 46.5% for dairy goat farms located in mountain areas of southern Spain. The aspects that differ most from the agroecological model include soil management, animal nutrition and product marketing. Results of the case study indicate that the proposed method is easy to implement and is useful for quantifying the approximation of conventional farms to an organic model.

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.

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...

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia.

PubMed

Godde, Cécile M; Thorburn, Peter J; Biggs, Jody S; Meier, Elizabeth A

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil-climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model's outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat-chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC.

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.

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.

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.

A system-level cost-of-energy wind farm layout optimization with landowner modeling

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

Chen, Le; MacDonald, Erin

This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustiy. The system-level cost-of-energy (COE) optimization model is also tested under twomore » land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability. (C) 2013 Elsevier Ltd. All rights reserved.« less

A scenario tree model for the Canadian Notifiable Avian Influenza Surveillance System and its application to estimation of probability of freedom and sample size determination.

PubMed

Christensen, Jette; Stryhn, Henrik; Vallières, André; El Allaki, Farouk

2011-05-01

In 2008, Canada designed and implemented the Canadian Notifiable Avian Influenza Surveillance System (CanNAISS) with six surveillance activities in a phased-in approach. CanNAISS was a surveillance system because it had more than one surveillance activity or component in 2008: passive surveillance; pre-slaughter surveillance; and voluntary enhanced notifiable avian influenza surveillance. Our objectives were to give a short overview of two active surveillance components in CanNAISS; describe the CanNAISS scenario tree model and its application to estimation of probability of populations being free of NAI virus infection and sample size determination. Our data from the pre-slaughter surveillance component included diagnostic test results from 6296 serum samples representing 601 commercial chicken and turkey farms collected from 25 August 2008 to 29 January 2009. In addition, we included data from a sub-population of farms with high biosecurity standards: 36,164 samples from 55 farms sampled repeatedly over the 24 months study period from January 2007 to December 2008. All submissions were negative for Notifiable Avian Influenza (NAI) virus infection. We developed the CanNAISS scenario tree model, so that it will estimate the surveillance component sensitivity and the probability of a population being free of NAI at the 0.01 farm-level and 0.3 within-farm-level prevalences. We propose that a general model, such as the CanNAISS scenario tree model, may have a broader application than more detailed models that require disease specific input parameters, such as relative risk estimates. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Building a stakeholder's vision of an offshore wind-farm project: A group modeling approach.

PubMed

Château, Pierre-Alexandre; Chang, Yang-Chi; Chen, Hsin; Ko, Tsung-Ting

2012-03-15

This paper describes a Group Model Building (GMB) initiative that was designed to discuss the various potential effects that an offshore wind-farm may have on its local ecology and socioeconomic development. The representatives of various organizations in the study area, Lu-Kang, Taiwan, have held several meetings, and structured debates have been organized to promote the emergence of a consensual view on the main issues and their implications. A System Dynamics (SD) model has been built and corrected iteratively with the participants through the GMB process. The diverse interests within the group led the process toward the design of multifunctional wind-farms with different modalities. The scenario analyses, using the SD model under various policies, including no wind-farm policy, objectively articulates the vision of the local stakeholders. The results of the SD simulations show that the multifunctional wind-farms may have superior economic effects and the larger wind-farms with bird corridors could reduce ecological impact. However, the participants of the modeling process did not appreciate any type of offshore wind-farm development when considering all of the identified key factors of social acceptance. The insight gained from the study can provide valuable information to actualize feasible strategies for the green energy technique to meet local expectations. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Let's put this in perspective: using dynamic simulation modelling to assess the impacts of farm-scale land management change on catchment-scale water quality

NASA Astrophysics Data System (ADS)

Rivers, Mark; Clarendon, Simon; Coles, Neil

2013-04-01

Natural Resource Management and Agri-industry development groups in Australia have invested considerable resources into the investigation of the economic, social and, particularly, environmental impacts of varying farming activities in a "catchment context". This research has resulted in the development of a much-improved understanding of the likely impacts of changed management practices at the farm-scale as well as the development of a number of conceptual models which place farming within this broader catchment context. The project discussed in this paper transformed a conceptual model of dairy farm phosphorus (P) management and transport processes into a more temporally and spatially dynamic model. This was then loaded with catchment-specific data and used as a "policy support tool" to allow the Australian dairy industry to examine the potential farm and catchment-scale impacts of varying dairy farm management practices within some key dairy farming regions. Models were developed, validated and calibrated using "STELLA©" dynamic modelling software for three catchments in which dairy is perceived as a significant land use. The models describe P movement and cycling within and through dairy farms in great detail and also estimate P transport through major source, sink and flow sectors of the catchments. A series of scenarios were executed for all three catchments which examined three main "groups" of tests: changes to farm P input rates; implementation of perceived environmental "Best Management Practices" (BMPs), and; changes to land use mosaics. Modifications to actual P input rates into dairy farms (not surprisingly) had a major effect on nutrient transport within and from the farms with a significant rise in nutrient loss rates at all scales with increasing fertiliser use. More surprisingly, however, even extensive environmental BMP implementation did not have marked effects on off-farm nutrient loss rates. On and off-farm riparian management implemented over entire catchments, for example, only reduced P losses by approximately 20%. Most importantly, changes to land use mosaics within the catchments provided great insight into the relative roles within the catchment P system of the various land uses. While dairying uses large amounts of P, the effects that dairy farm management can have at the catchment scale when these farms represent only a small proportion of the landscape are limited. The most important conclusions from the research are that: • While State and regional environmental management and regulatory agencies continue to set optimistic goals for water quality protection, this research shows that these targets are not achievable within current landscape paradigms even after broadscale BMP implementation, and that either these targets must be re-considered or that significant land use change (rather than simply improved management within current systems) must occur to meet the targets. • Catchment-scale effects of P losses at the farm scale are a complex function of P-use efficiency, landscape position and landscape footprint. Simply targetting those landuses perceived to have high nutrient loss rates does not adequately address the problem. • Catchment P management must be considered in a more inclusive and holistic way, and these assessments should be used to inform future planning policies and development plans if environmental goals as well as community expectations about the productive use of agricultural land are to be met.

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.

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

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

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.

The BaBar Data Reconstruction Control System

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

Ceseracciu, A

2005-04-20

The BaBar experiment is characterized by extremely high luminosity and very large volume of data produced and stored, with increasing computing requirements each year. To fulfill these requirements a Control System has been designed and developed for the offline distributed data reconstruction system. The control system described in this paper provides the performance and flexibility needed to manage a large number of small computing farms, and takes full benefit of OO design. The infrastructure is well isolated from the processing layer, it is generic and flexible, based on a light framework providing message passing and cooperative multitasking. The system ismore » distributed in a hierarchical way: the top-level system is organized in farms, farms in services, and services in subservices or code modules. It provides a powerful Finite State Machine framework to describe custom processing models in a simple regular language. This paper describes the design and evolution of this control system, currently in use at SLAC and Padova on {approx}450 CPUs organized in 9 farms.« less

The BaBar Data Reconstruction Control System

NASA Astrophysics Data System (ADS)

Ceseracciu, A.; Piemontese, M.; Tehrani, F. S.; Pulliam, T. M.; Galeazzi, F.

2005-08-01

The BaBar experiment is characterized by extremely high luminosity and very large volume of data produced and stored, with increasing computing requirements each year. To fulfill these requirements a control system has been designed and developed for the offline distributed data reconstruction system. The control system described in this paper provides the performance and flexibility needed to manage a large number of small computing farms, and takes full benefit of object oriented (OO) design. The infrastructure is well isolated from the processing layer, it is generic and flexible, based on a light framework providing message passing and cooperative multitasking. The system is distributed in a hierarchical way: the top-level system is organized in farms, farms in services, and services in subservices or code modules. It provides a powerful finite state machine framework to describe custom processing models in a simple regular language. This paper describes the design and evolution of this control system, currently in use at SLAC and Padova on /spl sim/450 CPUs organized in nine farms.

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.

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.

Improving Environmental Management on Small-scale Farms: Perspectives of Extension Educators and Horse Farm Operators

NASA Astrophysics Data System (ADS)

Rebecca, Perry-Hill; Linda, Prokopy

2015-01-01

Although the number of small-scale farms is increasing in North America and Europe, few studies have been conducted to better understand environmental management in this sector. We investigate this issue by examining environmental management on horse farms from both the perspective of the "expert" extension educator and horse farm operator. We conducted a Delphi survey and follow-up interviews with extension educators in Indiana and Kentucky. We also conducted interviews and farm assessments with 15 horse farm operators in the two states. Our results suggest a disconnection between the perceptions of extension educators and horse farm operators. Extension educators believed that operators of small horse farms are unfamiliar with conservation practices and their environmental benefits and they found it difficult to target outreach to this audience. In the interviews with horse farm operators, we found that the majority were somewhat familiar with conservation practices like rotational grazing, soil testing, heavy use area protection, and manure composting. It was not common, however, for practices to be implemented to generally recognized standards. The horse farm respondents perceived these practices as interrelated parts of a system of farm management that has developed over time to best deal with the physical features of the property, needs of the horses, and available resources. Because conservation practices must be incorporated into a complex farm management system, traditional models of extension (i.e., diffusion of innovations) may be inappropriate for promoting better environmental management on horse farms.

Improving environmental management on small-scale farms: perspectives of extension educators and horse farm operators.

PubMed

Rebecca, Perry-Hill; Linda, Prokopy

2015-01-01

Although the number of small-scale farms is increasing in North America and Europe, few studies have been conducted to better understand environmental management in this sector. We investigate this issue by examining environmental management on horse farms from both the perspective of the "expert" extension educator and horse farm operator. We conducted a Delphi survey and follow-up interviews with extension educators in Indiana and Kentucky. We also conducted interviews and farm assessments with 15 horse farm operators in the two states. Our results suggest a disconnection between the perceptions of extension educators and horse farm operators. Extension educators believed that operators of small horse farms are unfamiliar with conservation practices and their environmental benefits and they found it difficult to target outreach to this audience. In the interviews with horse farm operators, we found that the majority were somewhat familiar with conservation practices like rotational grazing, soil testing, heavy use area protection, and manure composting. It was not common, however, for practices to be implemented to generally recognized standards. The horse farm respondents perceived these practices as interrelated parts of a system of farm management that has developed over time to best deal with the physical features of the property, needs of the horses, and available resources. Because conservation practices must be incorporated into a complex farm management system, traditional models of extension (i.e., diffusion of innovations) may be inappropriate for promoting better environmental management on horse farms.

Sensors and Clinical Mastitis—The Quest for the Perfect Alert

PubMed Central

Hogeveen, Henk; Kamphuis, Claudia; Steeneveld, Wilma; Mollenhorst, Herman

2010-01-01

When cows on dairy farms are milked with an automatic milking system or in high capacity milking parlors, clinical mastitis (CM) cannot be adequately detected without sensors. The objective of this paper is to describe the performance demands of sensor systems to detect CM and evaluats the current performance of these sensor systems. Several detection models based on different sensors were studied in the past. When evaluating these models, three factors are important: performance (in terms of sensitivity and specificity), the time window and the similarity of the study data with real farm data. A CM detection system should offer at least a sensitivity of 80% and a specificity of 99%. The time window should not be longer than 48 hours and study circumstances should be as similar to practical farm circumstances as possible. The study design should comprise more than one farm for data collection. Since 1992, 16 peer-reviewed papers have been published with a description and evaluation of CM detection models. There is a large variation in the use of sensors and algorithms. All this makes these results not very comparable. There is a also large difference in performance between the detection models and also a large variation in time windows used and little similarity between study data. Therefore, it is difficult to compare the overall performance of the different CM detection models. The sensitivity and specificity found in the different studies could, for a large part, be explained in differences in the used time window. None of the described studies satisfied the demands for CM detection models. PMID:22163637

Sensors and clinical mastitis--the quest for the perfect alert.

PubMed

Hogeveen, Henk; Kamphuis, Claudia; Steeneveld, Wilma; Mollenhorst, Herman

2010-01-01

When cows on dairy farms are milked with an automatic milking system or in high capacity milking parlors, clinical mastitis (CM) cannot be adequately detected without sensors. The objective of this paper is to describe the performance demands of sensor systems to detect CM and evaluats the current performance of these sensor systems. Several detection models based on different sensors were studied in the past. When evaluating these models, three factors are important: performance (in terms of sensitivity and specificity), the time window and the similarity of the study data with real farm data. A CM detection system should offer at least a sensitivity of 80% and a specificity of 99%. The time window should not be longer than 48 hours and study circumstances should be as similar to practical farm circumstances as possible. The study design should comprise more than one farm for data collection. Since 1992, 16 peer-reviewed papers have been published with a description and evaluation of CM detection models. There is a large variation in the use of sensors and algorithms. All this makes these results not very comparable. There is a also large difference in performance between the detection models and also a large variation in time windows used and little similarity between study data. Therefore, it is difficult to compare the overall performance of the different CM detection models. The sensitivity and specificity found in the different studies could, for a large part, be explained in differences in the used time window. None of the described studies satisfied the demands for CM detection models.

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

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.

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.

Teaching Diversified Organic Crop Production Using the Community Supported Agriculture Farming System Model

ERIC Educational Resources Information Center

Falk, Constance L.; Pao, Pauline; Cramer, Christopher S.

2005-01-01

An organic garden operated as a community supported agriculture (CSA) venture on the New Mexico State University (NMSU) main campus was begun in January 2002. Students enroll in an organic vegetable production class during spring and fall semesters to help manage and work on the project. The CSA model of farming involves the sale of shares to…

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.

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

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

Organic farming benefits local plant diversity in vineyard farms located in intensive agricultural landscapes.

PubMed

Nascimbene, Juri; Marini, Lorenzo; Paoletti, Maurizio G

2012-05-01

The majority of research on organic farming has considered arable and grassland farming systems in Central and Northern Europe, whilst only a few studies have been carried out in Mediterranean agro-systems, such as vineyards, despite their economic importance. The main aim of the study was to test whether organic farming enhances local plant species richness in both crop and non-crop areas of vineyard farms located in intensive conventional landscapes. Nine conventional and nine organic farms were selected in an intensively cultivated region (i.e. no gradient in landscape composition) in northern Italy. In each farm, vascular plants were sampled in one vineyard and in two non-crop linear habitats, grass strips and hedgerows, adjacent to vineyards and therefore potentially influenced by farming. We used linear mixed models to test the effect of farming, and species longevity (annual vs. perennial) separately for the three habitat types. In our intensive agricultural landscapes organic farming promoted local plant species richness in vineyard fields, and grassland strips while we found no effect for linear hedgerows. Differences in species richness were not associated to differences in species composition, indicating that similar plant communities were hosted in vineyard farms independently of the management type. This negative effect of conventional farming was probably due to the use of herbicides, while mechanical operations and mowing regime did not differ between organic and conventional farms. In grassland strips, and only marginally in vineyards, we found that the positive effect of organic farming was more pronounced for perennial than annual species.

Optimal management of on-farm resources in small-scale dairy systems of Central Mexico: model development and evaluation.

PubMed

Castelán-Ortega, Octavio Alonso; Martínez-García, Carlos Galdino; Mould, Fergus L; Dorward, Peter; Rehman, Tahir; Rayas-Amor, Adolfo Armando

2016-06-01

This study evaluates the available on-farm resources of five case studies typified as small-scale dairy systems in central Mexico. A comprehensive mixed-integer linear programming model was developed and applied to two case studies. The optimal plan suggested the following: (1) instruction and utilization of maize silage, (2) alfalfa hay making that added US$140/ha/cut to the total net income, (3) allocation of land to cultivated pastures in a ratio of 27:41(cultivated pastures/maize crop) rather than at the current 14:69, and dairy cattle should graze 12 h/day, (4) to avoid grazing of communal pastures because this activity represented an opportunity cost of family labor that reduced the farm net income, and (5) that the highest farm net income was obtained when liquid milk and yogurt sales were included in the optimal plan. In the context of small-scale dairy systems of central Mexico, the optimal plan would need to be implemented gradually to enable farmers to develop required skills and to change management strategies from reliance on forage and purchased concentrate to pasture-based and conserved forage systems.

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 Bayesian network approach to knowledge integration and representation of farm irrigation: 1. Model development

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Haines, C. L.

2009-02-01

Irrigation is important to many agricultural businesses but also has implications for catchment health. A considerable body of knowledge exists on how irrigation management affects farm business and catchment health. However, this knowledge is fragmentary; is available in many forms such as qualitative and quantitative; is dispersed in scientific literature, technical reports, and the minds of individuals; and is of varying degrees of certainty. Bayesian networks allow the integration of dispersed knowledge into quantitative systems models. This study describes the development, validation, and application of a Bayesian network model of farm irrigation in the Shepparton Irrigation Region of northern Victoria, Australia. In this first paper we describe the process used to integrate a range of sources of knowledge to develop a model of farm irrigation. We describe the principal model components and summarize the reaction to the model and its development process by local stakeholders. Subsequent papers in this series describe model validation and the application of the model to assess the regional impact of historical and future management intervention.

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.

Integrated watershed- and farm-scale modeling framework for targeting critical source areas while maintaining farm economic viability.

PubMed

Ghebremichael, Lula T; Veith, Tamie L; Hamlett, James M

2013-01-15

Quantitative risk assessments of pollution and data related to the effectiveness of mitigating best management practices (BMPs) are important aspects of nonpoint source pollution control efforts, particularly those driven by specific water quality objectives and by measurable improvement goals, such as the total maximum daily load (TMDL) requirements. Targeting critical source areas (CSAs) that generate disproportionately high pollutant loads within a watershed is a crucial step in successfully controlling nonpoint source pollution. The importance of watershed simulation models in assisting with the quantitative assessments of CSAs of pollution (relative to their magnitudes and extents) and of the effectiveness of associated BMPs has been well recognized. However, due to the distinct disconnect between the hydrological scale in which these models conduct their evaluation and the farm scale at which feasible BMPs are actually selected and implemented, and due to the difficulty and uncertainty involved in transferring watershed model data to farm fields, there are limited practical applications of these tools in the current nonpoint source pollution control efforts by conservation specialists for delineating CSAs and planning targeting measures. There are also limited approaches developed that can assess impacts of CSA-targeted BMPs on farm productivity and profitability together with the assessment of water quality improvements expected from applying these measures. This study developed a modeling framework that integrates farm economics and environmental aspects (such as identification and mitigation of CSAs) through joint use of watershed- and farm-scale models in a closed feedback loop. The integration of models in a closed feedback loop provides a way for environmental changes to be evaluated with regard to the impact on the practical aspects of farm management and economics, adjusted or reformulated as necessary, and revaluated with respect to effectiveness of environmental mitigation at the farm- and watershed-levels. This paper also outlines steps needed to extract important CSA-related information from a watershed model to help inform targeting decisions at the farm scale. The modeling framework is demonstrated with two unique case studies in the northeastern United States (New York and Vermont), with supporting data from numerous published, location-specific studies at both the watershed and farm scales. Using the integrated modeling framework, it can be possible to compare the costs (in terms of changes required in farm system components or financial compensations for retiring crop lands) and benefits (in terms of measurable water quality improvement goals) of implementing targeted BMPs. This multi-scale modeling approach can be used in the multi-objective task of mitigating CSAs of pollution to meet water quality goals while maintaining farm-level economic viability. Copyright © 2012 Elsevier Ltd. All rights reserved.

Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin.

PubMed

Dutreuil, M; Wattiaux, M; Hardie, C A; Cabrera, V E

2014-09-01

Greenhouse gas (GHG) emissions from dairy farms are a major concern. Our objectives were to assess the effect of mitigation strategies on GHG emissions and net return to management on 3 distinct farm production systems of Wisconsin. A survey was conducted on 27 conventional farms, 30 grazing farms, and 69 organic farms. The data collected were used to characterize 3 feeding systems scaled to the average farm (85 cows and 127ha). The Integrated Farm System Model was used to simulate the economic and environmental impacts of altering feeding and manure management in those 3 farms. Results showed that incorporation of grazing practices for lactating cows in the conventional farm led to a 27.6% decrease in total GHG emissions [-0.16kg of CO2 equivalents (CO2eq)/kg of energy corrected milk (ECM)] and a 29.3% increase in net return to management (+$7,005/yr) when milk production was assumed constant. For the grazing and organic farms, decreasing the forage-to-concentrate ratio in the diet decreased GHG emissions when milk production was increased by 5 or 10%. The 5% increase in milk production was not sufficient to maintain the net return; however, the 10% increase in milk production increased net return in the organic farm but not on the grazing farm. A 13.7% decrease in GHG emissions (-0.08kg of CO2eq/kg of ECM) was observed on the conventional farm when incorporating manure the day of application and adding a 12-mo covered storage unit. However, those same changes led to a 6.1% (+0.04kg of CO2eq/kg of ECM) and a 6.9% (+0.06kg of CO2eq/kg of ECM) increase in GHG emissions in the grazing and the organic farms, respectively. For the 3 farms, manure management changes led to a decrease in net return to management. Simulation results suggested that the same feeding and manure management mitigation strategies led to different outcomes depending on the farm system, and furthermore, effective mitigation strategies were used to reduce GHG emissions while maintaining profitability within each farm. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

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

An AgMIP framework for improved agricultural representation in integrated assessment models

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

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.« less

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

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.

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.

Reference Manual for the System Advisor Model's Wind Power Performance Model

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

Freeman, J.; Jorgenson, J.; Gilman, P.

2014-08-01

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface andmore » as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.« less

How to measure the agroecological performance of farming in order to assist with the transition process.

PubMed

Trabelsi, Meriam; Mandart, Elisabeth; Le Grusse, Philippe; Bord, Jean-Paul

2016-01-01

The use of plant protection products enables farmers to maximize economic performance and yields, but in return, the environment and human health can be greatly affected because of their toxicity. There are currently strong calls for farmers to reduce the use of these toxic products for the preservation of the environment and the human health, and it has become urgent to invest in more sustainable models that help reduce these risks. One possible solution is the transition toward agroecological production systems. These new systems must be beneficial economically, socially, and environmentally in terms of human health. There are many tools available, based on a range of indicators, for assessing the sustainability of agricultural systems on conventional farm holdings. These methods are little suitable to agroecological farms and do not measure the performance of agroecological transition farms. In this article, we therefore develop a model for the strategic definition, guidance, and assistance for a transition to agroecological practices, capable of assessing performance of this transition and simulating the consequences of possible changes. This model was built by coupling (i) a decision-support tool and a technico-economic simulator with (ii) a conceptual model built from the dynamics of agroecological practices. This tool is currently being tested in the framework of a Compte d'Affectation Spéciale pour le Développement Agricole et Rural (CASDAR) project (CASDAR: project launched in 2013 by the French Ministry of Agriculture, Food and Forestry, on the theme "collective mobilisation for agroecology," http://agriculture.gouv.fr/Appel-a-projets-CASDAR ) using data from farms, most of which are engaged in agroenvironmental process and reducing plant protection treatments since 2008.

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.

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.

Modelling farm vulnerability to flooding: A step toward vulnerability mitigation policies appraisal

NASA Astrophysics Data System (ADS)

Brémond, P.; Abrami, G.; Blanc, C.; Grelot, F.

2009-04-01

Recent catastrophic flood events such as Elbe in 2002 or Rhône in 2003 have shown limits of flood management policies relying on dykes protection: worsening of flood impacts downstream, increased damage by dykes rupture. Those events, among others, contributes to radical changes on the philosophy of flood prevention, with the promotion of new orientations for mitigating flood exposition. Two new trends may have a significant impact on rural areas: floodplain restoration and vulnerability mitigation. The Rhône River program, which is an contract of objectives signed between French Government and local collectivites, is highly illustrative of these new trends and their impact on agricultural sector. In this program, it appears that areas to be concerned by floodplain restoration are agricultural ones, because their supposed vulnerability to flood is expected to be less important to urban areas. As a consequence, agricultural sector is particularly concerned by planned actions on mitigation of assets vulnerability, an important part of the program (financial support of European Union of 7.5 Million euros). Mitigation of agricultural assets vulnerability reveals particularly interesting for two following reasons. Firstly, it is a way to maintain agricultural activities in floodplains yet existing, without promoting flood protection. Secondly, in case of floodplain restoration, vulnerability mitigation is a way for local authorities to compensate over-flooding impacts. In practice, local authorities may financially support farmers for implementing measures to mitigate their farm vulnerability. On the Rhône River, an important work has already been done to identify farm vulnerability to flooding, and propose measures to mitigate it. More than 3 000 farms exposed to flood risk have been identified representing 88 690 ha of agricultural areas which is estimated to generate damage between 400 and 800 Million euros depending on the season of occurrence for a catastrophic flood. In the case of farm activities, vulnerability mitigation consists in implementing measures which can be: physical (equipment or electric power system elevation), organizational (emergency or recovery plan) or financial (insurance). These measures aim at decreasing the total damage incurred by farmers in case of flooding. For instance, if equipment is elevated, it will not suffer direct damage such as degradation. As a consequence, equipment will be available to continue production or recovery tasks, thus, avoiding indirect damage such as delays, indebtedness… The effects of these policies on farms, in particular vulnerability mitigation cannot be appraised using current methodologies mainly because they do not consider farm as a whole and focus on direct damage at the land plot scale (loss of yield). Moreover, since vulnerability mitigation policies are quite recent, few examples of implementation exist and no feedback experience can be processed. Meanwhile, decision makers and financial actors require more justification of the efficiency of public fund by economic appraisal of the projects. On the Rhône River, decision makers asked for an economic evaluation of the program of farm vulnerability mitigation they plan to implement. This implies to identify the effects of the measures to mitigate farm vulnerability, and to classify them by comparing their efficacy (avoided damage) and their cost of implementation. In this presentation, we propose and discuss a conceptual model of vulnerability at the farm scale. The modelling, in Unified Modelling Language, enabled to represent the ties between spatial, organizational and temporal dimensions, which are central to understanding of farm vulnerability and resilience to flooding. Through this modelling, we encompass three goals: To improve the comprehension of farm vulnerability and create a framework that allow discussion with experts of different disciplines as well as with local farmers; To identify data which are needed to implement the model and to collect them, specifically using the focus group method; Based on the conceptual model, to program a mathematical model which will be used to simulate damage (direct and indirect) on farm due to flood. This last objective should enable us to appraise policy to mitigate vulnerability which is planned to be implemented on Rhône River at the individual and regional scale. Finally, we discuss the possibility to use the UML modelling to develop a multi-agent system approach which could be interesting to take into account ties between farmers (solidarity, loan of equipment) or systemic effects due to the damage incurred by economic partners (loss of market share). Keywords vulnerability, UML modelling, farming systems, flood, mitigation policy, economic valuation

Farm-system modeling to evaluate environmental losses, profitability, and best management practice cost-effectiveness

USDA-ARS?s Scientific Manuscript database

To meet Chesapeake Bay Total Maximum Daily Load requirements for agricultural pollution, conservation districts and farmers are tasked with implementing best management practices (BMPs) that reduce farm losses of nutrients and sediment. The importance of the agricultural industry to the regional eco...

Environmental assessment of a representative grass-finishing beef operation in southern Pennsylvania

USDA-ARS?s Scientific Manuscript database

The objective of this study was to quantify environmental impacts of a representative grass-finished beef operation in southeastern Pennsylvania. A farm-gate life cycle assessment was conducted using the Integrated Farm System Model to estimate greenhouse gas emissions, reactive nitrogen loss, and w...

"Advances in Coupled Air Quality, Farm Management and Biogeochemistry to address bidirectional ammonia flux"

EPA Science Inventory

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 ambien...

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.

Carbon farming economics: What have we learned?

PubMed

Tang, Kai; Kragt, Marit E; Hailu, Atakelty; Ma, Chunbo

2016-05-01

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society. Copyright © 2016 Elsevier Ltd. All rights reserved.

Risk factors associated with bulk tank standard plate count, bulk tank coliform count, and the presence of Staphylococcus aureus on organic and conventional dairy farms in the United States.

PubMed

Cicconi-Hogan, K M; Gamroth, M; Richert, R; Ruegg, P L; Stiglbauer, K E; Schukken, Y H

2013-01-01

The purpose of this study was to assess the association of bulk tank milk standard plate counts, bulk tank coliform counts (CC), and the presence of Staphylococcus aureus in bulk tank milk with various management and farm characteristics on organic and conventional dairy farms throughout New York, Wisconsin, and Oregon. Data from size-matched organic farms (n=192), conventional nongrazing farms (n=64), and conventional grazing farms (n=36) were collected at a single visit for each farm. Of the 292 farms visited, 290 bulk tank milk samples were collected. Statistical models were created using data from all herds in the study, as well as exclusively for the organic subset of herds. Because of incomplete data, 267 of 290 herds were analyzed for total herd modeling, and 173 of 190 organic herds were analyzed for the organic herd modeling. Overall, more bulk tanks from organic farms had Staph. aureus cultured from them (62% of organic herds, 42% conventional nongrazing herds, and 43% of conventional grazing herds), whereas fewer organic herds had a high CC, defined as ≥50 cfu/mL, than conventional farms in the study. A high standard plate count (×1,000 cfu/mL) was associated with decreased body condition score of adult cows and decreased milk production in both models. Several variables were significant only in the model created using all herds or only in organic herds. The presence of Staph. aureus in the bulk tank milk was associated with fewer people treating mastitis, increased age of housing, and a higher percentage of cows with 3 or fewer teats in both the organic and total herd models. The Staph. aureus total herd model also showed a relationship with fewer first-lactation animals, higher hock scores, and less use of automatic takeoffs at milking. High bulk tank CC was related to feeding a total mixed ration and using natural service in nonlactating heifers in both models. Overall, attentive management and use of outside resources were useful with regard to CC on organic farms. In all models except the organic CC model, we observed an association with the average reported somatic cell count from 3 mo before the herd visit, indicating that many of the regularly tested milk quality parameters are interconnected. In conclusion, we found that conventional and organic farms are similar in regard to overall herd management, but each grazing system faces unique challenges when managing milk quality. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Direct and indirect impacts of crop-livestock organization on mixed crop-livestock systems sustainability: a model-based study.

PubMed

Sneessens, I; Veysset, P; Benoit, M; Lamadon, A; Brunschwig, G

2016-11-01

Crop-livestock production is claimed more sustainable than specialized production systems. However, the presence of controversial studies suggests that there must be conditions of mixing crop and livestock productions to allow for higher sustainable performances. Whereas previous studies focused on the impact of crop-livestock interactions on performances, we posit here that crop-livestock organization is a key determinant of farming system sustainability. Crop-livestock organization refers to the percentage of the agricultural area that is dedicated to each production. Our objective is to investigate if crop-livestock organization has both a direct and an indirect impact on mixed crop-livestock (MC-L) sustainability. In that objective, we build a whole-farm model parametrized on representative French sheep and crop farming systems in plain areas (Vienne, France). This model permits simulating contrasted MC-L systems and their subsequent sustainability through the following indicators of performance: farm income, production, N balance, greenhouse gas (GHG) emissions (/kg product) and MJ consumption (/kg product). Two MC-L systems were simulated with contrasted crop-livestock organizations (MC20-L80: 20% of crops; MC80-L20: 80% of crops). A first scenario - constraining no crop-livestock interactions in both MC-L systems - permits highlighting that crop-livestock organization has a significant direct impact on performances that implies trade-offs between objectives of sustainability. Indeed, the MC80-L20 system is showing higher performances for farm income (+44%), livestock production (+18%) and crop GHG emissions (-14%) whereas the MC20-L80 system has a better N balance (-53%) and a lower livestock MJ consumption (-9%). A second scenario - allowing for crop-livestock interactions in both MC20-L80 and MC80-L20 systems - stated that crop-livestock organization has a significant indirect impact on performances. Indeed, even if crop-livestock interactions permit improving performances, crop-livestock organization influences the capacity of MC-L systems to benefit from crop-livestock interactions. As a consequence, we observed a decreasing performance trade-off between MC-L systems for farm income (-4%) and crop GHG emissions (-10%) whereas the gap increases for nitrogen balance (+23%), livestock production (+6%) - MJ consumption (+16%) - GHG emissions (+5%) and crop MJ consumption (+5%). However, the indirect impact of crop-livestock organization doesn't reverse the trend of trade-offs between objectives of sustainability determined by the direct impact of crop-livestock organization. As a conclusion, crop-livestock organization is a key factor that has to be taken into account when studying the sustainability of mixed crop-livestock systems.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Offshore Wind Energy

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

Strach-Sonsalla, Mareike; Stammler, Matthias; Wenske, Jan

In 1991, the Vindeby Offshore Wind Farm, the first offshore wind farm in the world, started feeding electricity to the grid off the coast of Lolland, Denmark. Since then, offshore wind energy has developed from this early experiment to a multibillion dollar market and an important pillar of worldwide renewable energy production. Unit sizes grew from 450 kW at Vindeby to the 7.5 MW-class offshore wind turbines (OWT ) that are currently (by October 2014) in the prototyping phase. This chapter gives an overview of the state of the art in offshore wind turbine (OWT) technology and introduces the principlesmore » of modeling and simulating an OWT. The OWT components -- including the rotor, nacelle, support structure, control system, and power electronics -- are introduced, and current technological challenges are presented. The OWT system dynamics and the environment (wind and ocean waves) are described from the perspective of OWT modelers and designers. Finally, an outlook on future technology is provided. The descriptions in this chapter are focused on a single OWT -- more precisely, a horizontal-axis wind turbine -- as a dynamic system. Offshore wind farms and wind farm effects are not described in detail in this chapter, but an introduction and further references are given.« less

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia

PubMed Central

Godde, Cécile M.; Thorburn, Peter J.; Biggs, Jody S.; Meier, Elizabeth A.

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil–climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model’s outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat–chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC. PMID:27242862

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.

Final Report DE-EE0005380: Assessment of Offshore Wind Farm Effects on Sea Surface, Subsurface and Airborne Electronic Systems

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

Ling, Hao; Hamilton, Mark F.; Bhalla, Rajan

2013-09-30

Offshore wind energy is a valuable resource that can provide a significant boost to the US renewable energy portfolio. A current constraint to the development of offshore wind farms is the potential for interference to be caused by large wind farms on existing electronic and acoustical equipment such as radar and sonar systems for surveillance, navigation and communications. The US Department of Energy funded this study as an objective assessment of possible interference to various types of equipment operating in the marine environment where offshore wind farms could be installed. The objective of this project was to conduct a baselinemore » evaluation of electromagnetic and acoustical challenges to sea surface, subsurface and airborne electronic systems presented by offshore wind farms. To accomplish this goal, the following tasks were carried out: (1) survey electronic systems that can potentially be impacted by large offshore wind farms, and identify impact assessment studies and research and development activities both within and outside the US, (2) engage key stakeholders to identify their possible concerns and operating requirements, (3) conduct first-principle modeling on the interactions of electromagnetic signals with, and the radiation of underwater acoustic signals from, offshore wind farms to evaluate the effect of such interactions on electronic systems, and (4) provide impact assessments, recommend mitigation methods, prioritize future research directions, and disseminate project findings. This report provides a detailed description of the methodologies used to carry out the study, key findings of the study, and a list of recommendations derived based the findings.« less

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.

Empirical Analysis of Farm Credit Risk under the Structure Model

ERIC Educational Resources Information Center

Yan, Yan

2009-01-01

The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…

Economic and environmental feasibility of a perennial cow dairy farm.

PubMed

Rotz, C A; Zartman, D L; Crandall, K L

2005-08-01

More efficient and economical production systems are needed to improve the sustainability of dairy farms. One concept to consider is using perennial cows. Perennial cows are those that maintain a relatively high milk production for >or=2 yr without going through the typical dry period followed by calving. Farm records show that some cows have produced over 20 kg/d after 4 yr of continuous lactation. A farm simulation model was used to evaluate the long-term performance, environmental impact, and economics of a conceptual perennial cow production system on a typical dairy farm in Pennsylvania. Compared with a traditional 100-cow farm with replacement heifers produced on the farm, a perennial herd of 100 cows and purchased replacements provided environmental benefit but sustained a substantial economic loss. However, increasing the perennial herd to 128 cows better utilized the feed produced on the farm. Compared with the traditional 100-cow farm, use of the perennial 128-cow herd reduced supplemental protein and mineral feed purchases by 38%, increased annual milk sales by 21%, reduced nitrogen losses by 17%, maintained a phosphorus balance, and increased annual net return to farm management by 3200 dollars. A traditional 120-cow dairy farm with purchased replacements also used a similar amount of farm-produced feed. Compared with this option, the farm with 128 perennial cows reduced protein and mineral feed purchases by 36%, maintained similar annual milk sales, increased manure production by 7%, reduced N losses by 10%, and increased annual net return by 12,700 dollars. The economic feasibility of the perennial-cow dairy farm was very sensitive to the milk production maintained by the perennial herd and market prices for milk and perennial replacement animals. The analysis was relatively insensitive to the assumed useful life of perennial cows as long as they could be maintained in the herd for at least 3 yr. Thus, a perennial cow production system can improve the economic and environmental sustainability of a traditional dairy farm if a similar level in annual milk production per cow can be maintained.

Modelling the fate of pesticides in paddy rice-fish pond farming system in Northern Vietnam

NASA Astrophysics Data System (ADS)

Lamers, M.; Nguyen, N.; Streck, T.

2012-04-01

During the last decade rice production in Vietnam has tremendously increased due to the introduction of new high yield, short duration rice varieties and an increased application of pesticides. Since pesticides are toxic by design, there is a natural concern on the possible impacts of their presence in the environment on human health and environment quality. In North Vietnam, lowland and upland rice fields were identified to be a major non-point source of agrochemical pollution to surface and ground water, which are often directly used for domestic purposes. Field measurements, however, are time consuming, costly and logistical demanding. Hence, quantification, forecast and risk assessment studies are hampered by a limited amount of field data. One potential way to cope with this shortcoming is the use of process-based models. In the present study we developed a model for simulating short-term pesticide dynamics in combined paddy rice field - fish pond farming systems under the specific environmental conditions of south-east Asia. Basic approaches and algorithms to describe the key underlying biogeochemical processes were mainly adopted from the literature to assure that the model reflects the current standard of scientific knowledge and commonly accepted theoretical background. The model was calibrated by means of the Gauss-Marquardt-Levenberg algorithm and validated against measured pesticide concentrations (dimethoate and fenitrothion) during spring and summer rice crop season 2008, respectively, of a paddy field - fish pond system typical for northern Vietnam. First simulation results indicate that our model is capable to simulate the fate of pesticides in such paddy - fish pond farming systems. The model efficiency for the period of calibration, for example, was 0.97 and 0.95 for dimethoate and fenitrothion, respectively. For the period of validation, however, the modeling efficiency slightly decreased to 0.96 and 0.81 for dimethoate and fenitrothion, respectively. In our presentation we will picture key model features and algorithms and demonstrate that our model provides a useful and appropriate tool for analyzing and quantifying the transport and behavior of pesticides in paddy rice farming systems.

Evaluation model of wind energy resources and utilization efficiency of wind farm

NASA Astrophysics Data System (ADS)

Ma, Jie

2018-04-01

Due to the large amount of abandoned winds in wind farms, the establishment of a wind farm evaluation model is particularly important for the future development of wind farms In this essay, consider the wind farm's wind energy situation, Wind Energy Resource Model (WERM) and Wind Energy Utilization Efficiency Model(WEUEM) are established to conduct a comprehensive assessment of the wind farm. Wind Energy Resource Model (WERM) contains average wind speed, average wind power density and turbulence intensity, which assessed wind energy resources together. Based on our model, combined with the actual measurement data of a wind farm, calculate the indicators using the model, and the results are in line with the actual situation. We can plan the future development of the wind farm based on this result. Thus, the proposed establishment approach of wind farm assessment model has application value.

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data.

PubMed

Groenendijk, Piet; Heinen, Marius; Klammler, Gernot; Fank, Johann; Kupfersberger, Hans; Pisinaras, Vassilios; Gemitzi, Alexandra; Peña-Haro, Salvador; García-Prats, Alberto; Pulido-Velazquez, Manuel; Perego, Alessia; Acutis, Marco; Trevisan, Marco

2014-11-15

The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessment was conducted by testing six detailed state-of-the-art models for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of the models: 1) a blind test for 2005-2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009-2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement, model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

The Impact of Input and Output Prices on The Household Economic Behavior of Rice-Livestock Integrated Farming System (Rlifs) and Non Rlifs Farmers

NASA Astrophysics Data System (ADS)

Lindawati, L.; Kusnadi, N.; Kuntjoro, S. U.; Swastika, D. K. S.

2018-02-01

Integrated farming system is a system that emphasized linkages and synergism of farming units waste utilization. The objective of the study was to analyze the impact of input and output prices on both Rice Livestock Integrated Farming System (RLIFS) and non RLIFS farmers. The study used econometric model in the form of a simultaneous equations system consisted of 36 equations (18 behavior and 18 identity equations). The impact of changes in some variables was obtained through simulation of input and output prices on simultaneous equations. The results showed that the price increasing of the seed, SP-36, urea, medication/vitamins, manure, bran, straw had negative impact on production of the rice, cow, manure, bran, straw and household income. The decrease in the rice and cow production, production input usage, allocation of family labor, rice and cow business income was greater in RLIFS than non RLIFS farmers. The impact of rising rice and cow cattle prices in the two groups of farmers was not too much different because (1) farming waste wasn’t used effectively (2) manure and straw had small proportion of production costs. The increase of input and output price didn’t have impact on production costs and household expenditures on RLIFS.

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...

76 FR 34985 - Farm Credit System Insurance Corporation Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-15

... FARM CREDIT SYSTEM INSURANCE CORPORATION Farm Credit System Insurance Corporation Board Meeting AGENCY: Farm Credit System Insurance Corporation. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the...

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.

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.

Is agritourism eco-friendly? A comparison between agritourisms and other farms in Italy using farm accountancy data network dataset.

PubMed

Mastronardi, Luigi; Giaccio, Vincenzo; Giannelli, Agostino; Scardera, Alfonso

2015-01-01

This paper presents the results of research regarding the environmental performances of Italian farms with agritourism compared with farms without agritourism. In Italy, agritourism is considered an agricultural activity and can only be performed by a farmer. Moreover, Italian national legislation forces the farmer to dedicate himself mainly to traditional farming, rather than to tourism activities. For this reason, environmental performances have been highlighted by analyzing only features and production systems of the farms. By utilizing the most frequent indicators used in studies regarding sustainability, the authors show how Italian agritourisms tend to develop more environmentally friendly agricultural methods, which have a positive impact on biodiversity, landscape and natural resources. The empirical analysis is based on the Italian FADN (Farm Accountancy Data Network) dataset. The European FADN was created to represent farms' technical and economic operation in the European Union and on which it drafts the agricultural and rural policies. The dichotomous structure of the dependent variable (presence or absence of agritourism at the farm) has a propensity for an assessment method based on Binary Response Model Regression.

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

Sanz Rodrigo, Javier; Chávez Arroyo, Roberto Aurelio; Moriarty, Patrick

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge ismore » how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, 'building the bridge' means developing models for the so-called 'terra incognita,' a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.« less

Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

NASA Astrophysics Data System (ADS)

Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

2003-08-01

For two decades now, the use of Remote Sensing/Precision Agriculture to improve farm yields while reducing the use of polluting chemicals and the limited water supply has been a major goal. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, farm efficiency must increase to meet future food requirements and to make farming a sustainable, profitable occupation. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The real goal is to increase farm profitability by identifying the additional treatments of chemicals and water that increase revenues more than they increase costs and do no exceed pollution standards (constrained optimization). Even though the economic and environmental benefits appear to be great, Remote Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now in place, but other needed factors have been missing. Commercial satellite systems can now image the Earth (multi-spectrally) with a resolution as fine as 2.5 m. Precision variable dispensing systems using GPS are now available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been developed. Personal computers and internet access are now in place in most farm homes and can provide a mechanism for periodically disseminating advice on what quantities of water and chemicals are needed in specific regions of each field. Several processes have been selected that fuse the disparate sources of information on the current and historic states of the crop and soil, and the remaining resource levels available, with the critical decisions that farmers are required to make. These are done in a way that is easy for the farmer to understand and profitable to implement. A "Constrained Optimization Algorithm" to further improve these processes will be presented. The objective function of the model will used to maximize the farmer's profit via increasing yields while decreasing environmental damage and decreasing applications of costly treatments. This model will incorporate information from Remote Sensing, from in-situ weather sources, from soil history, and from tacit farmer knowledge of the relative productivity of selected "Management Zones" of the farm, to provide incremental advice throughout the growing season on the optimum usage of water and chemical treatments.

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.

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.

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.

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.

77 FR 8179 - Disclosure to Investors in System-wide and Consolidated Bank Debt Obligations of the Farm Credit...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... FARM CREDIT ADMINISTRATION 12 CFR Part 630 RIN 3052-AC77 Disclosure to Investors in System-wide and Consolidated Bank Debt Obligations of the Farm Credit System AGENCY: Farm Credit Administration...) System Audit Committee (SAC) and the Farm Credit System (System) annual report to investors. The proposed...

Contribution of milk production to global greenhouse gas emissions. An estimation based on typical farms.

PubMed

Hagemann, Martin; Ndambi, Asaah; Hemme, Torsten; Latacz-Lohmann, Uwe

2012-02-01

Studies on the contribution of milk production to global greenhouse gas (GHG) emissions are rare (FAO 2010) and often based on crude data which do not appropriately reflect the heterogeneity of farming systems. This article estimates GHG emissions from milk production in different dairy regions of the world based on a harmonised farm data and assesses the contribution of milk production to global GHG emissions. The methodology comprises three elements: (1) the International Farm Comparison Network (IFCN) concept of typical farms and the related globally standardised dairy model farms representing 45 dairy regions in 38 countries; (2) a partial life cycle assessment model for estimating GHG emissions of the typical dairy farms; and (3) standard regression analysis to estimate GHG emissions from milk production in countries for which no typical farms are available in the IFCN database. Across the 117 typical farms in the 38 countries analysed, the average emission rate is 1.50 kg CO(2) equivalents (CO(2)-eq.)/kg milk. The contribution of milk production to the global anthropogenic emissions is estimated at 1.3 Gt CO(2)-eq./year, accounting for 2.65% of total global anthropogenic emissions (49 Gt; IPCC, Synthesis Report for Policy Maker, Valencia, Spain, 2007). We emphasise that our estimates of the contribution of milk production to global GHG emissions are subject to uncertainty. Part of the uncertainty stems from the choice of the appropriate methods for estimating emissions at the level of the individual animal.

12 CFR 615.5560 - Book-entry Procedure for Farm Credit System Financial Assistance Corporation Securities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OPERATIONS Farm Credit System Financial Assistance Corporation Securities § 615.5560 Book-entry Procedure for Farm Credit System Financial Assistance Corporation Securities. (a) The Farm Credit System Financial... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Book-entry Procedure for Farm Credit System...

Whole Farm Net Greenhouse Gas Abatement from Establishing Kikuyu-Based Perennial Pastures in South-Western Australia

PubMed Central

Thomas, Dean T.; Sanderman, Jonathan; Eady, Sandra J.; Masters, David G.; Sanford, Paul

2012-01-01

Simple Summary Greenhouse gas (GHG) emissions from ruminant livestock production (sheep, cattle and goats) have contributed to a common perception that a shift in the human diet from animal to plant-based products is environmentally responsible. In this study we found that the level of net emissions from livestock production systems is strongly influenced by the type of farming system that is used, and in fact GHG emission levels from some livestock production systems may be comparable with cropping systems. By introducing into farming systems ‘perennial’ pasture plants that are able to capture more atmospheric carbon, which is then stored in the soil, emission levels from livestock production can be substantially reduced. Abstract On-farm activities that reduce GHG emissions or sequester carbon from the atmosphere to compensate for anthropogenic emissions are currently being evaluated by the Australian Government as carbon offset opportunities. The aim of this study was to examine the implications of establishing and grazing Kikuyu pastures, integrated as part of a mixed Merino sheep and cropping system, as a carbon offset mechanism. For the assessment of changes in net greenhouse gas emissions, results from a combination of whole farm economic and livestock models were used (MIDAS and GrassGro). Net GHG emissions were determined by deducting increased emissions from introducing this practice change (increased methane and nitrous oxide emissions due to higher stocking rates) from the soil carbon sequestered from growing the Kikuyu pasture. Our results indicate that livestock systems using perennial pastures may have substantially lower net GHG emissions, and reduced GHG intensity of production, compared with annual plant-based production systems. Soil carbon accumulation by converting 45% of arable land within a farm enterprise to Kikuyu-based pasture was determined to be 0.80 t CO2-e farm ha−1 yr−1 and increased GHG emissions (leakage) was 0.19 t CO2-e farm ha−1 yr−1. The net benefit of this practice change was 0.61 t CO2-e farm ha−1 yr−1 while the rate of soil carbon accumulation remains constant. The use of perennial pastures improved the efficiency of animal production almost eight fold when expressed as carbon dioxide equivalent emissions per unit of animal product. The strategy of using perennial pasture to improve production levels and store additional carbon in the soil demonstrates how livestock should be considered in farming systems as both sources and sinks for GHG abatement. PMID:26487024

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

Characterization of Dutch dairy farms using sensor systems for cow management.

PubMed

Steeneveld, W; Hogeveen, H

2015-01-01

To improve cow management in large dairy herds, sensors have been developed that can measure physiological, behavioral, and production indicators on individual cows. Recently, the number of dairy farms using sensor systems has increased. It is not known, however, to what extent sensor systems are used on dairy farms, and the reasons why farmers invest or not in sensor systems are unclear. The first objective of this study was to give an overview of the sensor systems currently used in the Netherlands. The second objective was to investigate the reasons for investing or not investing in sensor systems. The third objective was to characterize farms with and without sensor systems. A survey was developed to investigate first, the reasons for investing or not in sensor systems and, then, how the sensor systems are used in daily cow management. The survey was sent to 1,672 Dutch dairy farmers. The final data set consisted of 512 dairy farms (response rate of 30.6%); 202 farms indicated that they had sensor systems and 310 farms indicated that they did not have sensor systems. A wide variety of sensor systems was used on Dutch dairy farms; those for mastitis detection and estrus detection were the most-used sensor systems. The use of sensor systems was different for farms using an automatic milking system (AMS) and a conventional milking system (CMS). Reasons for investing were different for different sensor systems. For sensor systems attached to the AMS, the farmers made no conscious decision to invest: they answered that the sensors were standard in the AMS or were bought for reduced cost with the AMS. The main reasons for investing in estrus detection sensor systems were improving detection rates, gaining insights into the fertility level of the herd, improving profitability of the farm, and reducing labor. Main reasons for not investing in sensor systems were economically related. It was very difficult to characterize farms with and without sensor systems. Farms with CMS and sensor systems had more cows than CMS farms without sensor systems. Furthermore, farms with sensor systems had fewer labor hours per cow compared with farms without sensor systems. Other farm characteristics (age of the farmer, availability of a successor, growth in herd size, milk production per cow, number of cows per hectare, and milk production per hectare) did not differ for farms with and without sensor systems. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

12 CFR 1400.1 - Farm Credit System Insurance Corporation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 9 2013-01-01 2013-01-01 false Farm Credit System Insurance Corporation. 1400.1 Section 1400.1 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION ORGANIZATION AND FUNCTIONS Organization and Functions § 1400.1 Farm Credit System Insurance Corporation. The Farm Credit...

12 CFR 1400.1 - Farm Credit System Insurance Corporation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 9 2012-01-01 2012-01-01 false Farm Credit System Insurance Corporation. 1400.1 Section 1400.1 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION ORGANIZATION AND FUNCTIONS Organization and Functions § 1400.1 Farm Credit System Insurance Corporation. The Farm Credit...

12 CFR 1400.1 - Farm Credit System Insurance Corporation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 7 2011-01-01 2011-01-01 false Farm Credit System Insurance Corporation. 1400.1 Section 1400.1 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION ORGANIZATION AND FUNCTIONS Organization and Functions § 1400.1 Farm Credit System Insurance Corporation. The Farm Credit...

12 CFR 1400.1 - Farm Credit System Insurance Corporation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 10 2014-01-01 2014-01-01 false Farm Credit System Insurance Corporation. 1400.1 Section 1400.1 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION ORGANIZATION AND FUNCTIONS Organization and Functions § 1400.1 Farm Credit System Insurance Corporation. The Farm Credit...

12 CFR 1400.1 - Farm Credit System Insurance Corporation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Farm Credit System Insurance Corporation. 1400.1 Section 1400.1 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION ORGANIZATION AND FUNCTIONS Organization and Functions § 1400.1 Farm Credit System Insurance Corporation. The Farm Credit...

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.

From cow to cheese: Novel phenotypes related to the sensory profile of model cheeses from individual cows.

PubMed

Cipolat-Gotet, C; Cecchinato, A; Drake, M A; Marangon, A; Martin, B; Bittante, G

2018-07-01

Milk samples were taken once from a total of 1,224 Brown Swiss cows from 83 herds, and 1,500 mL of raw full-fat milk from each cow was processed according to a laboratory-scale model-cheese-making procedure. A sensory panel was assembled and the members trained to evaluate the sensory profile of individual model cheeses. The protocol scorecard was composed of 7 main sensory descriptors related to smell intensity, flavor intensity, taste (salt and sour), and texture (elasticity, firmness, and moisture), and 40 sensory attributes describing smell and flavor profiles. Sensory data were analyzed using a mixed model that included random effects of herd, animal, and panelist, as well as fixed effects of dairy system, days in milk, parity, and order of cheese presentation, and covariates for cheese weight and fat:protein ratio. The sensory profile was not much affected by the dairy farming systems included in the trial, but it was affected by farm within dairy system: cheeses from traditional dairy farms had a greater wood/humus attribute of both smell and flavor than those from modern farm. Of the modern farms, cheeses from those using total mixed rations including silages had a more intense smell of sour milk and a firmer, less moist texture than those using total mixed rations without silages. Moreover, for all the sensory traits, we found less variance related to herd and animals than that related to the panelists and the residuals. Stage of lactation was found to be the most important, whereas parity was not relevant. In particular, cheese smell intensity (and some related attributes) exhibited a quadratic trend with lower values in mid-lactation, whereas flavor and salt descriptors were more intense in the last period of lactation. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Farming systems and sanitary problems in mountain cattle farms.

PubMed

Bernúes, A; Manrique, E; Maza, M T

1994-01-01

On the basis of concepts established by ecopathology and the systems theory, certain aspects of the 'Ecosanitary System', which forms part of the 'Farming System', were studied. Multivariant statistical methods were used to analyze and classify 69 mountain cattle farms into different types and to establish relationships between variables relating to pathological problems and others relating to aspects of production and farm structure. Stable mastitis characterized farms with a higher milk production, more intensive farming and greater hygiene measures. The pattern of diarrhoea in the calves was similar. Problems relating to reproduction and calving were more characteristic of traditional, small farms.

Comparing offshore wind farm wake observed from satellite SAR and wake model results

NASA Astrophysics Data System (ADS)

Bay Hasager, Charlotte

2014-05-01

Offshore winds can be observed from satellite synthetic aperture radar (SAR). In the FP7 EERA DTOC project, the European Energy Research Alliance project on Design Tools for Offshore Wind Farm Clusters, there is focus on mid- to far-field wind farm wakes. The more wind farms are constructed nearby other wind farms, the more is the potential loss in annual energy production in all neighboring wind farms due to wind farm cluster effects. It is of course dependent upon the prevailing wind directions and wind speed levels, the distance between the wind farms, the wind turbine sizes and spacing. Some knowledge is available within wind farm arrays and in the near-field from various investigations. There are 58 offshore wind farms in the Northern European seas grid connected and in operation. Several of those are spaced near each other. There are several twin wind farms in operation including Nysted-1 and Rødsand-2 in the Baltic Sea, and Horns Rev 1 and Horns Rev 2, Egmond aan Zee and Prinses Amalia, and Thompton 1 and Thompton 2 all in the North Sea. There are ambitious plans of constructing numerous wind farms - great clusters of offshore wind farms. Current investigation of offshore wind farms includes mapping from high-resolution satellite SAR of several of the offshore wind farms in operation in the North Sea. Around 20 images with wind farm wake cases have been retrieved and processed. The data are from the Canadian RADARSAT-1/-2 satellites. These observe in microwave C-band and have been used for ocean surface wind retrieval during several years. The satellite wind maps are valid at 10 m above sea level. The wakes are identified in the raw images as darker areas downwind of the wind farms. In the SAR-based wind maps the wake deficit is found as areas of lower winds downwind of the wind farms compared to parallel undisturbed flow in the flow direction. The wind direction is clearly visible from lee effects and wind streaks in the images. The wind farm wake cases are modeled by various types of wake models. In the EERA DTOC project the model suite consists of engineering models (Ainslie, DWM, GLC, PARK, WASP/NOJ), simplified CFD models (FUGA, FarmFlow), full CFD models (CRES-flowNS, RANS), mesoscale model (SKIRON, WRF) and coupled meso-scale and microscale models. The comparison analysis between the satellite wind wake and model results will be presented and discussed. It is first time a comprehensive analysis is performed on this subject. The topic gains increasing importance because there is a growing need to precisely model also mid- and far-field wind farms wakes for development and planning of offshore wind farm clusters.

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.

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.

12 CFR 615.5175 - Investments in Farm Credit System institution preferred stock.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Investments in Farm Credit System institution preferred stock. 615.5175 Section 615.5175 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM... Capital, and Other Investments § 615.5175 Investments in Farm Credit System institution preferred stock...

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.

[Application of CRISPR/Cas9 mediated genome editing in farm animals].

PubMed

Xing, Yu-yun; Yang, Qiang; Ren, Jun

2016-03-01

CRISPR (Clustered regularly interspaced short palindromic repeats)/Cas (CRISPR associated proteins) is an acquired immune system found in bacteria and archaea that fight against invasion of viruses or plasmids. CRISPR/Cas systems are currently classified into three main types: I, II and III, of which type II has relatively simple components. The CRISPR/Cas9 technology modified from type II CRISPR/Cas system has been developed as an efficient genome editing tool. Since the initial application of the CRISPR/Cas9 technology in mammals in 2013, the reports of this system for genomic editing has skyrocketed. Farm animals are not only economically important animals, but also ideal animal models for human diseases and biomedical studies. In this review, we summarize the applications of CRISPR/Cas9 in farm animals, briefly describe the off-target effects and the main solutions, and finally highlight the future perspectives of this technology.

Enhancing Ecoefficiency in Shrimp Farming through Interconnected Ponds

PubMed Central

Barraza-Guardado, Ramón Héctor; Arreola-Lizárraga, José Alfredo; Juárez-García, Manuel; Juvera-Hoyos, Antonio; Casillas-Hernández, Ramón

2015-01-01

The future development of shrimp farming needs to improve its ecoefficiency. The purpose of this study was to evaluate water quality, flows, and nitrogen balance and production parameters on a farm with interconnected pond design to improve the efficiency of the semi-intensive culture of Litopenaeus vannamei ponds. The study was conducted in 21 commercial culture ponds during 180 days at densities of 30–35 ind m−2 and daily water exchange <2%. Our study provides evidence that by interconnecting ponds nutrient recycling is favored by promoting the growth of primary producers of the pond as chlorophyll a. Based on the mass balance and flow of nutrients this culture system reduces the flow of solid, particulate organic matter, and nitrogen compounds to the environment and significantly increases the efficiency of water (5 to 6.5 m3 kg−1 cycle−1), when compared with traditional culture systems. With this culture system it is possible to recover up to 34% of the total nitrogen entering the system, with production in excess of 4,000 kg ha−1 shrimp. We believe that the production system with interconnected ponds is a technically feasible model to improve ecoefficiency production of shrimp farming. PMID:26525070

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.

Using models to establish the financially optimum strategy for Irish dairy farms.

PubMed

Ruelle, E; Delaby, L; Wallace, M; Shalloo, L

2018-01-01

Determining the effect of a change in management on farm with differing characteristics is a significant challenge in the evaluation of dairy systems due to the interacting components of complex biological systems. In Ireland, milk production is increasing substantially following the abolition of the European Union milk quota regime in 2015. There are 2 main ways to increase the milk production on farm (within a fixed land base): either increase the number of animals (thus increasing the stocking rate) or increase the milk production per animal through increased feeding or increased lactation length. In this study, the effect of increased concentrate feeding or an increase in grazing intensity was simulated to determine the effect on the farm system and its economic performance. Four stocking rates (2.3, 2.6, 2.9, and 3.2 cow/ha) and 5 different concentrate supplementation strategies (0, 180, 360, 600, and 900 kg of dry matter/lactation) resulting in 20 different scenarios were evaluated across different milk, concentrate, and silage purchase prices. Each simulation was run across 10 yr of meteorological data, which had been recorded over the period 2004 to 2013. Three models-the Moorepark and St Gilles grass growth model, the pasture-based herd dynamic milk model, and the Moorepark dairy systems model-were integrated and applied to simulate the different scenarios. Overall, this study has demonstrated that the most profitable scenario was a stocking rate of 2.6 cow/ha with a concentrate supplementation of 600 kg of dry matter/cow. The factor that had the greatest influence on profitability was variability of milk price. 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/).

Coevolution of farming and private property during the early Holocene.

PubMed

Bowles, Samuel; Choi, Jung-Kyoo

2013-05-28

The advent of farming around 12 millennia ago was a cultural as well as technological revolution, requiring a new system of property rights. Among mobile hunter-gatherers during the late Pleistocene, food was almost certainly widely shared as it was acquired. If a harvested crop or the meat of a domesticated animal were to have been distributed to other group members, a late Pleistocene would-be farmer would have had little incentive to engage in the required investments in clearing, cultivation, animal tending, and storage. However, the new property rights that farming required--secure individual claims to the products of one's labor--were infeasible because most of the mobile and dispersed resources of a forager economy could not cost-effectively be delimited and defended. The resulting chicken-and-egg puzzle might be resolved if farming had been much more productive than foraging, but initially it was not. Our model and simulations explain how, despite being an unlikely event, farming and a new system of farming-friendly property rights nonetheless jointly emerged when they did. This Holocene revolution was not sparked by a superior technology. It occurred because possession of the wealth of farmers--crops, dwellings, and animals--could be unambiguously demarcated and defended. This facilitated the spread of new property rights that were advantageous to the groups adopting them. Our results thus challenge unicausal models of historical dynamics driven by advances in technology, population pressure, or other exogenous changes. Our approach may be applied to other technological and institutional revolutions such as the 18th- and 19th-century industrial revolution and the information revolution today.

Coevolution of farming and private property during the early Holocene

PubMed Central

Bowles, Samuel; Choi, Jung-Kyoo

2013-01-01

The advent of farming around 12 millennia ago was a cultural as well as technological revolution, requiring a new system of property rights. Among mobile hunter–gatherers during the late Pleistocene, food was almost certainly widely shared as it was acquired. If a harvested crop or the meat of a domesticated animal were to have been distributed to other group members, a late Pleistocene would-be farmer would have had little incentive to engage in the required investments in clearing, cultivation, animal tending, and storage. However, the new property rights that farming required—secure individual claims to the products of one’s labor—were infeasible because most of the mobile and dispersed resources of a forager economy could not cost-effectively be delimited and defended. The resulting chicken-and-egg puzzle might be resolved if farming had been much more productive than foraging, but initially it was not. Our model and simulations explain how, despite being an unlikely event, farming and a new system of farming-friendly property rights nonetheless jointly emerged when they did. This Holocene revolution was not sparked by a superior technology. It occurred because possession of the wealth of farmers—crops, dwellings, and animals—could be unambiguously demarcated and defended. This facilitated the spread of new property rights that were advantageous to the groups adopting them. Our results thus challenge unicausal models of historical dynamics driven by advances in technology, population pressure, or other exogenous changes. Our approach may be applied to other technological and institutional revolutions such as the 18th- and 19th-century industrial revolution and the information revolution today. PMID:23671111

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…

7 CFR 4290.720 - Enterprises that may be ineligible for Financing.

Code of Federal Regulations, 2010 CFR

2010-01-01

... wells, wind farms, or power facilities (including solar, geothermal, hydroelectric, or biomass power... ineligible for Farm Credit System Assistance. If one or more Farm Credit System Institutions or their... that is not otherwise eligible to receive Financing from the Farm Credit System under the Farm Credit...

7 CFR 4290.720 - Enterprises that may be ineligible for Financing.

Code of Federal Regulations, 2011 CFR

2011-01-01

... wells, wind farms, or power facilities (including solar, geothermal, hydroelectric, or biomass power... ineligible for Farm Credit System Assistance. If one or more Farm Credit System Institutions or their... that is not otherwise eligible to receive Financing from the Farm Credit System under the Farm Credit...

A high resolution WRF model for wind energy forecasting

NASA Astrophysics Data System (ADS)

Vincent, Claire Louise; Liu, Yubao

2010-05-01

The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the diffusion constant caused damping of the unrealistic fluctuations, but did not completely solve the problem. Using two-way nesting also mitigated the unrealistic fluctuations significantly. It can be concluded that for real case LES modelling of wind farm circulations, care should be taken to ensure the consistency between the mesoscale weather forcing and LES models to avoid exciting spurious noise along the forcing boundary. The development of algorithms that adequately model the sub-grid-scale mixing that cannot be resolved by LES models is an important area for further research. References Liu, Y. Y._W. Liu, W. Y.Y. Cheng, W. Wu, T. T. Warner and K. Parks, 2009: Simulating intra-farm wind variations with the WRF-RTFDDA-LES modeling system. 10th WRF Users' Workshop, Boulder, C, USA. June 23 - 26, 2009. Skamarock, W., J. Dudhia, D.O. Gill, D.M. Barker, M.G.Duda, X-Y. Huang, W. Wang and J.G. Powers, A Description of the Advanced Research WRF version 3, NCAR Technical Note TN-475+STR, NCAR, Boulder, Colorado, 2008.

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.

Intensive Farming: Evolutionary Implications for Parasites and Pathogens

PubMed Central

Nilsen, Frank; Ebert, Dieter; Skorping, Arne

2010-01-01

An increasing number of scientists have recently raised concerns about the threat posed by human intervention on the evolution of parasites and disease agents. New parasites (including pathogens) keep emerging and parasites which previously were considered to be ‘under control’ are re-emerging, sometimes in highly virulent forms. This re-emergence may be parasite evolution, driven by human activity, including ecological changes related to modern agricultural practices. Intensive farming creates conditions for parasite growth and transmission drastically different from what parasites experience in wild host populations and may therefore alter selection on various traits, such as life-history traits and virulence. Although recent epidemic outbreaks highlight the risks associated with intensive farming practices, most work has focused on reducing the short-term economic losses imposed by parasites, such as application of chemotherapy. Most of the research on parasite evolution has been conducted using laboratory model systems, often unrelated to economically important systems. Here, we review the possible evolutionary consequences of intensive farming by relating current knowledge of the evolution of parasite life-history and virulence with specific conditions experienced by parasites on farms. We show that intensive farming practices are likely to select for fast-growing, early-transmitted, and hence probably more virulent parasites. As an illustration, we consider the case of the fish farming industry, a branch of intensive farming which has dramatically expanded recently and present evidence that supports the idea that intensive farming conditions increase parasite virulence. We suggest that more studies should focus on the impact of intensive farming on parasite evolution in order to build currently lacking, but necessary bridges between academia and decision-makers. PMID:21151485

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.

76 FR 76409 - Meeting of the Farm Credit System Insurance Corporation Board

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-07

... FARM CREDIT SYSTEM INSURANCE CORPORATION Meeting of the Farm Credit System Insurance Corporation... given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND... Coverage and the Audit Committee Charter Closed Sesson Confidential Report on System Performance Audit Plan...

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.

Development of livestock production in the tropics: farm and farmers' perspectives.

PubMed

Oosting, S J; Udo, H M J; Viets, T C

2014-08-01

Because of an increasing demand for animal-source foods, an increasing desire to reduce poverty and an increasing need to reduce the environmental impact of livestock production, tropical farming systems with livestock must increase their productivity. An important share of the global human and livestock populations are found within smallholder mixed-crop-livestock systems, which should, therefore, contribute significantly towards this increase in livestock production. The present paper argues that increased livestock production in smallholder mixed-crop-livestock systems faces many constraints at the level of the farm and the value chain. The present paper aims to describe and explain the impact of increased production from the farm and farmers' perspective, in order to understand the constraints for increased livestock production. A framework is presented that links farming systems to livestock value chains. It is concluded that farming systems that pass from subsistence to commercial livestock production will: (1) shift from rural to urban markets; (2) become part of a different value chain (with lower prices, higher demands for product quality and increased competition from peri-urban producers and imports); and (3) have to face changes in within-farm mechanisms and crop-livestock relationships. A model study showed that feed limitation, which is common in tropical farming systems with livestock, implies that maximum herd output is achieved with small herd sizes, leaving low-quality feeds unutilised. Maximal herd output is not achieved at maximal individual animal output. Having more animals than required for optimal production - which is often the case as a larger herd size supports non-production functions of livestock, such as manure production, draught, traction and capital storage - goes at the expense of animal-source food output. Improving low-quality feeds by treatment allows keeping more animals while maintaining the same level of production. Ruminant methane emission per kg of milk produced is mainly determined by the level of milk production per cow. Part of the methane emissions, however, should be attributed to the non-production functions of ruminants. It was concluded that understanding the farm and farmers' perceptions of increased production helps with the understanding of productivity increase constraints and adds information to that reported in the literature at the level of technology, markets and institutions.

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.

77 FR 45606 - Policy Statement Concerning Assistance to Troubled Farm Credit System Institutions

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-01

... FARM CREDIT SYSTEM INSURANCE CORPORATION Policy Statement Concerning Assistance to Troubled Farm...) published for comment a draft Policy Statement Concerning Assistance to Troubled Farm Credit System (System) Institutions to replace the Corporation's present Policy Statement Concerning Stand- Alone Assistance. The...

77 FR 37399 - Policy Statement Concerning Assistance to Troubled Farm Credit System Institutions

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-21

... FARM CREDIT SYSTEM INSURANCE CORPORATION Policy Statement Concerning Assistance to Troubled Farm... publishing for comment a draft Policy Statement Concerning Assistance to Troubled Farm Credit System (System) Institutions to replace the Corporation's present Policy Statement Concerning Stand- Alone Assistance. The...

77 FR 76356 - Disclosure to Investors in System-wide and Consolidated Bank Debt Obligations of the Farm Credit...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-28

... FARM CREDIT ADMINISTRATION 12 CFR Part 630 RIN 3052-AC77 Disclosure to Investors in System-wide and Consolidated Bank Debt Obligations of the Farm Credit System; System Audit Committee; Effective... Corporation System Audit Committee and the Farm Credit System annual report to investors. In accordance with...

Assessing the production and economic benefits from preventing cows grazing on wet soils in New Zealand.

PubMed

Laurenson, Seth; Houlbrooke, David J; Beukes, Pierre C

2016-10-01

Intensive grazing by cattle on wet pasture can have a negative effect on soil physical quality and future pasture production. On a North Otago dairy farm in New Zealand, experimental plots were monitored for four years to assess whether preventing cow grazing of wet pastures during the milking season would improve soil structure and pasture production compared with unrestricted access to pastures. The DairyNZ Whole Farm Model was used to scale up results to a farm system level and ascertain the cost benefit of deferred grazing management. Soils under deferred grazing management had significantly higher total porosity, yet no significant improvement in macroporosity (values ranging between 0.112 and 0.146 m(3)  m(-3) ). Annual pasture production did not differ between the control and deferred grazing treatments, averaging 17.0 ± 3.8 and 17.9 ± 4.1 t DM ha(-1) year(-1) respectively (P > 0.05). Furthermore, whole farm modelling indicated that farm operating profit was reduced by NZ$1683 ha(-1) year(-1) (four-year average) under deferred grazing management. Deferring dairy cow grazing from wet Pallic soils in North Otago was effective in improving soil structure (measured as total soil porosity), yet did not lead to a significant increase in pasture production. Whole farm modelling indicated no economic benefit of removing cows from wet soils during the milking season. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Herd-level risk factors for Neospora caninum seroprevalence in dairy farms in southern Brazil.

PubMed

Corbellini, Luis G; Smith, David R; Pescador, Caroline A; Schmitz, Milene; Correa, Andre; Steffen, David J; Driemeier, David

2006-05-17

A cross-sectional study was used to test the relationship between herd seroprevalence to Neospora caninum and various potential herd-level risk factors in 60 dairy farms located in two distinct regions in southern Brazil. Thirty farms were randomly selected from within each region. A questionnaire was designed to summarize each farm's production system as it might relate to N. caninum transmission. The questionnaire contained 105 closed questions relating to general characteristics of the farms, farm facilities, management, source of food and water, herd health, environment and biosecurity, which included questions relevant to N. caninum transmission, including presence and number of dogs and other animals, purchase of animals and contact with man. Serum samples were collected from 40% of animals in each farm and N. caninum antibodies were detected by immunofluorescent antibody test (IFAT). The association between potential risk factors and the probability of an animal being seropositive was modeled using a generalized estimation equations (GEE) logistic regression model. The model accounted for multilevel correlation of data from multiple animals within herds. The mean (+/-S.D.) number of animals in the 60 herds was 64.5 (+/-45.6), ranging from 20 to 280 females. Blood samples were collected from 1549 animals. The size of the farms varied from 4 to 100 ha (mean 30.1+/-25.9 ha). At least one dog was found in 57 of the 60 dairy farms (95%). The mean number of dogs was 3.1 (+/-1.9), ranging from 0 to 10. All females were raised on pasture. For all cattle sampled, N. caninum seroprevalence was 17.8%. Overall, 93.3% of herds (56/60) had at least one seropositive animal identified. Four variables were significantly associated with N. caninum sero-response in the 57 dairy farms, which were included in the final multivariable model: the number of dogs on the farm, farm area (hectares), feeding pooled sources of colostrum and region. The odds of a cow being seropositive increased 1.13 times for each additional dog present on the farm (P=0.021). Cattle from farms that fed calves colostrum pooled from multiple cows had 1.79 times greater odds for being seropositive for N. caninum (P<0.003). The probability of being seropositive was inverse to the area of the farms, such that cattle had 0.92 times the odds to be seropositive (P=0.014) for each additional 10 ha of farmland. Finally, cattle from farms in region one had 0.71 times the odds to be seropositive than cattle from region two (P=0.035). Results of this study suggest that several risk factors may explain why dairy cattle in Brazil may become exposed to N. caninum. However, further investigation of these factors is necessary because the purpose of this study was to refine and generate hypotheses on N. caninum transmission.

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.

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.

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

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

Energy Economics of Farm Biogas in Cold Climates

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

Pillay, Pragasen; Grimberg, Stefan; Powers, Susan E

Anaerobic digestion of farm and dairy waste has been shown to be capital intensive. One way to improve digester economics is to co-digest high-energy substrates together with the dairy manure. Cheese whey for example represents a high-energy substrate that is generated during cheese manufacture. There are currently no quantitative tools available that predict performance of co-digestion farm systems. The goal of this project was to develop a mathematical tool that would (1) predict the impact of co-digestion and (2) determine the best use of the generated biogas for a cheese manufacturing plant. Two models were developed that separately could bemore » used to meet both goals of the project. Given current pricing structures of the most economical use of the generated biogas at the cheese manufacturing plant was as a replacement of fuel oil to generate heat. The developed digester model accurately predicted the performance of 26 farm digesters operating in the North Eastern U.S.« less

Process-based Modeling of Ammonia Emission from Beef Cattle Feedyards with the Integrated Farm Systems Model.

PubMed

Waldrip, Heidi M; Rotz, C Alan; Hafner, Sasha D; Todd, Richard W; Cole, N Andy

2014-07-01

Ammonia (NH) volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N) and potentially leads to overfertilization and acidification of aquatic and terrestrial ecosystems. In addition, NH is involved in the formation of atmospheric fine particulate matter (PM), which can affect human health. Process-based models have been developed to estimate NH emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot beef cattle feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita NH emission rates were compared with emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations and were sensitive to variations in air temperature and dietary crude protein concentration. Predicted mean daily NH emission rates for the two feedyards had 71 to 81% agreement with observations. In addition, IFSM estimates of annual feedyard emissions were within 11 to 24% of observations, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can quantify average feedyard NH emissions, assist with emissions reporting, provide accurate information for legislators and policymakers, investigate methods to mitigate NH losses, and evaluate the effects of specific management practices on farm nutrient balances. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Security and Stability Analysis of Wind Farms Integration into Distribution Network

NASA Astrophysics Data System (ADS)

Guan-yang, Li; Hongzhao, Wang; Guanglei, Li; Yamei, Cheng; Hong-zheng, Liu; Yi, Sun

2017-05-01

With the increasing share of the wind power in the power system, wind power fluctuations will cause obvious negative impacts on weak local grid. This paper firstly establish electromechanical transient simulation model for doubly fed induction wind turbine, then use Matlab/Simulink to achieve power flow calculation and transient simulation of power system including wind farms, the local synchronous generator, load, etc, finally analyze wind power on the impact of the local power grid under typical circumstances. The actual calculated results indicate that wind mutation causes little effect on the power grid, but when the three-phase short circuit fault happens, active power of wind power decreases sharply and the voltage of location of wind power into the grid also drop sharply, finally wind farm split from power system. This situation is not conducive to security and stability of the local power grid. It is necessary to develop security and stability measures in the future.

Nitrates in drinking water: relation with intensive livestock production.

PubMed

Giammarino, M; Quatto, P

2015-01-01

An excess of nitrates causes environmental pollution in receiving water bodies and health risk for human, if contaminated water is source of drinking water. The directive 91/676/ CEE [1] aims to reduce the nitrogen pressure in Europe from agriculture sources and identifies the livestock population as one of the predominant sources of surplus of nutrients that could be released in water and air. Directive is concerned about cattle, sheep, pigs and poultry and their territorial loads, but it does not deal with fish farms. Fish farms effluents may contain pollutants affecting ecosystem water quality. On the basis of multivariate statistical analysis, this paper aims to establish what types of farming affect the presence of nitrates in drinking water in the province of Cuneo, Piedmont, Italy. In this regard, we have used data from official sources on nitrates in drinking water and data Arvet database, concerning the presence of intensive farming in the considered area. For model selection we have employed automatic variable selection algorithm. We have identified fish farms as a major source of nitrogen released into the environment, while pollution from sheep and poultry has appeared negligible. We would like to emphasize the need to include in the "Nitrate Vulnerable Zones" (as defined in Directive 91/676/CEE [1]), all areas where there are intensive farming of fish with open-system type of water use. Besides, aquaculture open-system should be equipped with adequate downstream system of filtering for removing nitrates in the wastewater.

PubMed Central

QUATTO, P.

2015-01-01

Summary Introduction. An excess of nitrates causes environmental pollution in receiving water bodies and health risk for human, if contaminated water is source of drinking water. The directive 91/676/ CEE [1] aims to reduce the nitrogen pressure in Europe from agriculture sources and identifies the livestock population as one of the predominant sources of surplus of nutrients that could be released in water and air. Directive is concerned about cattle, sheep, pigs and poultry and their territorial loads, but it does not deal with fish farms. Fish farms effluents may contain pollutants affecting ecosystem water quality. Methods. On the basis of multivariate statistical analysis, this paper aims to establish what types of farming affect the presence of nitrates in drinking water in the province of Cuneo, Piedmont, Italy. In this regard, we have used data from official sources on nitrates in drinking water and data Arvet database, concerning the presence of intensive farming in the considered area. For model selection we have employed automatic variable selection algorithm. Results and discussion. We have identified fish farms as a major source of nitrogen released into the environment, while pollution from sheep and poultry has appeared negligible. We would like to emphasize the need to include in the "Nitrate Vulnerable Zones" (as defined in Directive 91/676/CEE [1]), all areas where there are intensive farming of fish with open-system type of water use. Besides, aquaculture open-system should be equipped with adequate downstream system of filtering for removing nitrates in the wastewater. PMID:26900335

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

Organic Farming: Biodiversity Impacts Can Depend on Dispersal Characteristics and Landscape Context

PubMed Central

Feber, Ruth E.; Johnson, Paul J.; Bell, James R.; Chamberlain, Dan E.; Firbank, Leslie G.; Fuller, Robert J.; Manley, Will; Mathews, Fiona; Norton, Lisa R.; Townsend, Martin; Macdonald, David W.

2015-01-01

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower dispersal abilities generally. The evidence for interactions among landscape and farming system in their effects on spiders highlights the importance of developing strategies for managing farmland at the landscape-scale for most effective conservation of biodiversity. PMID:26309040

Organic Farming: Biodiversity Impacts Can Depend on Dispersal Characteristics and Landscape Context.

PubMed

Feber, Ruth E; Johnson, Paul J; Bell, James R; Chamberlain, Dan E; Firbank, Leslie G; Fuller, Robert J; Manley, Will; Mathews, Fiona; Norton, Lisa R; Townsend, Martin; Macdonald, David W

2015-01-01

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower dispersal abilities generally. The evidence for interactions among landscape and farming system in their effects on spiders highlights the importance of developing strategies for managing farmland at the landscape-scale for most effective conservation of biodiversity.

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 mobile, high-throughput semi-automated system for testing cognition in large non-primate animal models of Huntington disease.

PubMed

McBride, Sebastian D; Perentos, Nicholas; Morton, A Jennifer

2016-05-30

For reasons of cost and ethical concerns, models of neurodegenerative disorders such as Huntington disease (HD) are currently being developed in farm animals, as an alternative to non-human primates. Developing reliable methods of testing cognitive function is essential to determining the usefulness of such models. Nevertheless, cognitive testing of farm animal species presents a unique set of challenges. The primary aims of this study were to develop and validate a mobile operant system suitable for high throughput cognitive testing of sheep. We designed a semi-automated testing system with the capability of presenting stimuli (visual, auditory) and reward at six spatial locations. Fourteen normal sheep were used to validate the system using a two-choice visual discrimination task. Four stages of training devised to acclimatise animals to the system are also presented. All sheep progressed rapidly through the training stages, over eight sessions. All sheep learned the 2CVDT and performed at least one reversal stage. The mean number of trials the sheep took to reach criterion in the first acquisition learning was 13.9±1.5 and for the reversal learning was 19.1±1.8. This is the first mobile semi-automated operant system developed for testing cognitive function in sheep. We have designed and validated an automated operant behavioural testing system suitable for high throughput cognitive testing in sheep and other medium-sized quadrupeds, such as pigs and dogs. Sheep performance in the two-choice visual discrimination task was very similar to that reported for non-human primates and strongly supports the use of farm animals as pre-clinical models for the study of neurodegenerative diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Simulating the impact of no-till systems on field water fluxes and maize productivity under semi-arid conditions

NASA Astrophysics Data System (ADS)

Mupangwa, W.; Jewitt, G. P. W.

Crop output from the smallholder farming sector in sub-Saharan Africa is trailing population growth leading to widespread household food insecurity. It is therefore imperative that crop production in semi-arid areas be improved in order to meet the food demand of the ever increasing human population. No-till farming practices have the potential to increase crop productivity in smallholder production systems of sub-Saharan Africa, but rarely do because of the constraints experienced by these farmers. One of the most significant of these is the consumption of mulch by livestock. In the absence of long term on-farm assessment of the no-till system under smallholder conditions, simulation modelling is a tool that provides an insight into the potential benefits and can highlight shortcomings of the system under existing soil, climatic and socio-economic conditions. Thus, this study was designed to better understand the long term impact of no-till system without mulch cover on field water fluxes and maize productivity under a highly variable rainfall pattern typical of semi-arid South Africa. The simulated on-farm experiment consisted of two tillage treatments namely oxen-drawn conventional ploughing (CT) and ripping (NT). The APSIM model was applied for a 95 year period after first being calibrated and validated using measured runoff and maize yield data. The predicted results showed significantly higher surface runoff from the conventional system compared to the no-till system. Predicted deep drainage losses were higher from the NT system compared to the CT system regardless of the rainfall pattern. However, the APSIM model predicted 62% of the annual rainfall being lost through soil evaporation from both tillage systems. The predicted yields from the two systems were within 50 kg ha -1 difference in 74% of the years used in the simulation. In only 9% of the years, the model predicted higher grain yield in the NT system compared to the CT system. It is suggested that NT systems may have great potential for reducing surface runoff from smallholder fields and that the NT systems may have potential to recharge groundwater resources through increased deep drainage. However, it was also noted that the APSIM model has major shortcomings in simulating the water balance at this level of detail and that the findings need to be confirmed by further field based and modelling studies. Nevertheless, it is clear that without mulch or a cover crop, the continued high soil evaporation and correspondingly low crop yields suggest that there is little benefit to farmers adopting NT systems in semiarid environments, despite potential water resources benefits downstream. In such cases, the potential for payment for ecosystem services should be explored.

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

Investment appraisal of automatic milking and conventional milking technologies in a pasture-based dairy system.

PubMed

Shortall, J; Shalloo, L; Foley, C; Sleator, R D; O'Brien, B

2016-09-01

The successful integration of automatic milking (AM) systems and grazing has resulted in AM becoming a feasible alternative to conventional milking (CM) in pasture-based systems. The objective of this study was to identify the profitability of AM in a pasture-based system, relative to CM herringbone parlors with 2 different levels of automation, across 2 farm sizes, over a 10-yr period following initial investment. The scenarios which were evaluated were (1) a medium farm milking 70 cows twice daily, with 1 AM unit, a 12-unit CM medium-specification (MS) parlor and a 12-unit CM high-specification (HS) parlor, and (2) a large farm milking 140 cows twice daily with 2 AM units, a 20-unit CM MS parlor and a 20-unit CM HS parlor. A stochastic whole-farm budgetary simulation model combined capital investment costs and annual labor and maintenance costs for each investment scenario, with each scenario evaluated using multiple financial metrics, such as annual net profit, annual net cash flow, total discounted net profitability, total discounted net cash flow, and return on investment. The capital required for each investment was financed from borrowings at an interest rate of 5% and repaid over 10-yr, whereas milking equipment and building infrastructure were depreciated over 10 and 20 yr, respectively. A supporting labor audit (conducted on both AM and CM farms) showed a 36% reduction in labor demand associated with AM. However, despite this reduction in labor, MS CM technologies consistently achieved greater profitability, irrespective of farm size. The AM system achieved intermediate profitability at medium farm size; it was 0.5% less profitable than HS technology at the large farm size. The difference in profitability was greatest in the years after the initial investment. This study indicated that although milking with AM was less profitable than MS technologies, it was competitive when compared with a CM parlor of similar technology. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Near real time wind energy forecasting incorporating wind tunnel modeling

NASA Astrophysics Data System (ADS)

Lubitz, William David

A series of experiments and investigations were carried out to inform the development of a day-ahead wind power forecasting system. An experimental near-real time wind power forecasting system was designed and constructed that operates on a desktop PC and forecasts 12--48 hours in advance. The system uses model output of the Eta regional scale forecast (RSF) to forecast the power production of a wind farm in the Altamont Pass, California, USA from 12 to 48 hours in advance. It is of modular construction and designed to also allow diagnostic forecasting using archived RSF data, thereby allowing different methods of completing each forecasting step to be tested and compared using the same input data. Wind-tunnel investigations of the effect of wind direction and hill geometry on wind speed-up above a hill were conducted. Field data from an Altamont Pass, California site was used to evaluate several speed-up prediction algorithms, both with and without wind direction adjustment. These algorithms were found to be of limited usefulness for the complex terrain case evaluated. Wind-tunnel and numerical simulation-based methods were developed for determining a wind farm power curve (the relation between meteorological conditions at a point in the wind farm and the power production of the wind farm). Both methods, as well as two methods based on fits to historical data, ultimately showed similar levels of accuracy: mean absolute errors predicting power production of 5 to 7 percent of the wind farm power capacity. The downscaling of RSF forecast data to the wind farm was found to be complicated by the presence of complex terrain. Poor results using the geostrophic drag law and regression methods motivated the development of a database search method that is capable of forecasting not only wind speeds but also power production with accuracy better than persistence.

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.

Life cycle assessment of different sea cucumber ( Apostichopus japonicus Selenka) farming systems

NASA Astrophysics Data System (ADS)

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

2015-12-01

The life cycle assessment was employed to evaluate the environmental impacts of three farming systems (indoor intensive, semi-intensive and extensive systems) of sea cucumber living near Qingdao, China, which can effectively overcome the interference of inaccurate background parameters caused by the diversity of economic level and environment in different regions. Six indicators entailing global warming potential (1.86E + 04, 3.45E + 03, 2.36E + 02), eutrophication potential (6.65E + 01, -1.24E + 02, -1.65E + 02), acidification potential (1.93E + 02, 4.33E + 01, 1.30E + 00), photochemical oxidant formation potential (2.35E-01, 5.46E -02, 2.53E-03), human toxicity potential (2.47E + 00, 6.08E-01, 4.91E + 00) and energy use (3.36E + 05, 1.27E + 04, 1.48E + 03) were introduced in the current study. It was found that all environmental indicators in the indoor intensive farming system were much higher than those in semi-intensive and extensive farming systems because of the dominant role of energy input, while energy input also contributed as the leading cause factor for most of the indicators in the semi-intensive farming system. Yet in the extensive farming system, infrastructure materials played a major role. Through a comprehensive comparison of the three farming systems, it was concluded that income per unit area of indoor intensive farming system was much higher than those of semi-intensive and extensive farming systems. However, the extensive farming system was the most sustainable one. Moreover, adequate measures were proposed, respectively, to improve the environmental sustainability of each farming system in the present study.

Environment and farm factors associated with exposure to Theileria parva infection in cattle under traditional mixed farming system in Mbeere District, Kenya.

PubMed

Gachohi, John M; Kitala, Phillip M; Ngumi, Priscilla N; Skilton, Rob A

2011-01-01

The objective of this study was to investigate the relationship between seroprevalence to Theileria parva infection in cattle and potential environmental and farm-level effects in 80 farms under traditional crop-livestock system in Mbeere District, Kenya. A standardized questionnaire was used to collect the effects characteristics as related to T. parva infection epidemiology. Serum samples were collected from 440 cattle of all ages for detection of T. parva antibodies by the enzyme-linked immunosorbent assay technique. The association between the variables was assessed using a generalized estimation equation logistic regression model. The overall T. parva seroprevalence, accounting for correlation of responses, was 19.3% (95% confidence interval (CI) 14%, 25%). Two variables, "administrative division" and "presence of the vector tick on the farm", were significantly associated with the T. parva seroresponse. Respectively, cattle from farms in Gachoka, Evurore, and Mwea divisions were (and their 95% CI) 1.3 (0.36, 4.8), 4.4 (1.2, 15.9), and 15.2 (4.9, 47.1) times more likely to be seropositive relative to those from Siakago Division (P = 0.000). Cattle from farms in which the vector tick was present were 2.9 (1.2, 6.7) times more likely to be seropositive (P = 0.011). Results of this study suggested that both environmental and farm factors may be associated with T. parva infection epidemiology in Mbeere District. Under such circumstances, characterization of environmental suitability for the vector tick and corresponding environment-specific farm management practices in the district is required both for improved understanding of the disease and in planning disease control programs.

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

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...

Effect of rearing factors on the prevalence of floor eggs, cloacal cannibalism and feather pecking in commercial flocks of loose housed laying hens.

PubMed

Gunnarsson, S; Keeling, L J; Svedberg, J

1999-03-01

1. Effects of rearing conditions on behavioural problems were investigated in a cohort study of commercial flocks of laying hens housed in 2 different loose housing systems. The sample population was 120 385 laying hens from 59 flocks of various hybrids at 21 different farms. 2. Logistic regression modelling was used to test the effects of selected factors on floor eggs, cloacal cannibalism and feather pecking. In addition to early access to perches or litter, models included hybrid, stocking density, group size, housing system, age at delivery, identical housing system at the rearing farm and at the production farm and, in models for floor eggs and cloacal cannibalism, nest area per hen. Odds ratios were calculated from the results of the models to allow risk assessment. 3. No significant correlations were found between the prevalence of floor eggs, cloacal cannibalism and feather pecking. 4. Access to perches from not later than the 4th week of age decreased the prevalence of floor eggs during the period from start-of-lay until 35 weeks of age, odds ratio 0-30 (P<0-001). Furthermore, early access to perches decreased the prevalence of cloacal cannibalism during the production period, odds ratio 0-46 (P=0.03). 5. No other factor had a significant effect in these models. Although it was not significant, early access to litter had a non-significant tendency to reduce the prevalence of feather pecking.

Farming Systems Research: A Critical Appraisal. MSU Rural Development Paper No. 6.

ERIC Educational Resources Information Center

Gilbert, Elon H.; And Others

The objectives of the state-of-the-art paper, second in a series on farming systems research (FSR) in the Third World, are to: (1) review the literature on farming systems; (2) evaluate farming systems research in international institutes and in national agricultural research systems in the Third World; and (3) recommend what can be done to…

12 CFR 1402.13 - Request for records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION RELEASING INFORMATION Availability of Records of the Farm Credit System Insurance Corporation § 1402.13 Request for records. Requests for records... regular business day in the office of the Farm Credit System Insurance Corporation, 1501 Farm Credit Drive...

78 FR 4847 - Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-23

... FARM CREDIT SYSTEM INSURANCE CORPORATION Board Meeting AGENCY: Farm Credit System Insurance Corporation. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of the Farm...

[Agricultural policies and farming systems: A case study of landscape changes in Shizuitou Village in the recent four decades].

PubMed

Wang, Xiao-jun; Zhou, Yang; Yan, Yan-bin; Li, Lei

2015-01-01

Agricultural policy in China's rural heartland is driving profound changes to traditional farming systems. A case study covering four decades mapped and recorded farming patterns and processes in Shizuitou Village, a rural village in northwest Shanxi. An integrated geospatial methodology from geography and anthropology was employed in the case study to record the changing dynamics of farming systems in Shizuitou Village to discover the long-term impacts of China's agricultural policies on village farming systems. Positive and negative impacts of agricultural policies on village farming systems were mapped, inventoried and evaluated using Participatory Geographic Information Systems (PGIS). The results revealed traditional polycultures are being gradually replaced by industrialized monocultures. The driving forces behind these farming changes come from a series of government agricultural policies aiming at modernization of farming systems in China. The goal of these policies was to spur rapid development of industrial agriculture under the guise of modernization but is leading to the decay of traditional farming systems in the village that maintained local food security with healthy land for hundreds of years. The paper concluded with a recommendation that in future, agricultural policy makers should strike a more reasonable balance between short-term agricultural profits and long-term farming sustainability based on the principles of ecological sustainable development under the context of global changes.

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.

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.

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.

Nutritional and ecological evaluation of dairy farming systems based on concentrate feeding regimes in semi-arid environments of Jordan

PubMed Central

Alqaisi, Othman; Hemme, Torsten; Hagemann, Martin; Susenbeth, Andreas

2013-01-01

The objective of this study was to evaluate the nutritional and ecological aspects of feeding systems practiced under semi-arid environments in Jordan. Nine dairy farms representing the different dairy farming systems were selected for this study. Feed samples (n = 58), fecal samples (n = 108), and milk samples (n = 78) were collected from the farms and analysed for chemical composition. Feed samples were also analysed for metabolisable energy (ME) contents and in vitro organic matter digestibility according to Hohenheim-Feed-Test. Furthermore, fecal nitrogen concentration was determined to estimate in vivo organic matter digestibility. ME and nutrient intakes were calculated based on the farmer’s estimate of dry matter intake and the analysed composition of the feed ingredients. ME and nutrient intakes were compared to recommended standard values for adequate supply of ME, utilizable crude protein, rumen undegradable crude protein (RUCP), phosphorus (P), and calcium (Ca). Technology Impact Policy Impact Calculation model complemented with a partial life cycle assessment model was used to estimate greenhouse gas emissions of milk production at farm gate. The model predicts CH4, N2O and CO2 gases emitted either directly or indirectly. Average daily energy corrected milk yield (ECM) was 19 kg and ranged between 11 and 27 kg. The mean of ME intake of all farms was 184 MJ/d with a range between 115 and 225 MJ/d. Intake of RUCP was lower than the standard requirements in six farms ranging between 19 and 137 g/d, was higher (32 and 93 g/d) in two farms, and matched the requirements in one farm. P intake was higher than the requirements in all farms (mean oversupply = 19 g/d) and ranged between 3 and 30 g/d. Ca intake was significantly below the requirements in small scale farms. Milk nitrogen efficiency N-eff (milk N/intake N) varied between 19% and 28% and was mainly driven by the level of milk yield. Total CO2 equivalent (CO2 equ) emission ranged between 0.90 and 1.88 kg CO2/kg ECM milk, where the enteric and manure CH4 contributed to 52% of the total CO2 equ emissions, followed by the indirect emissions of N2O and the direct emissions of CO2 gases which comprises 17% and 15%, respectively, from total CO2 equ emissions. Emissions per kg of milk were significantly driven by the level of milk production (r2 = 0.93) and of eDMI (r2 = 0.88), while the total emissions were not influenced by diet composition. A difference of 16 kg ECM/d in milk yield, 9% in N-eff and of 0.9 kg CO2 equ/kg in ECM milk observed between low and high yielding animals. To improve the nutritional status of the animals, protein requirements have to be met. Furthermore, low price by-products with a low carbon credit should be included in the diets to replace the high proportion of imported concentrate feeds and consequently improve the economic situation of dairy farms and mitigate CO2 equ emissions. PMID:24596499

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.

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…

75 FR 53966 - Regular Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-02

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of the Farm...

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.

Evaluation of the sustainability of contrasted pig farming systems: breeding programmes.

PubMed

Rydhmer, L; Gourdine, J L; de Greef, K; Bonneau, M

2014-12-01

The sustainability of breeding activities in 15 pig farming systems in five European countries was evaluated. One conventional and two differentiated systems per country were studied. The Conventional systems were the standard systems in their countries. The differentiated systems were of three categories: Adapted Conventional with focus on animal welfare, meat quality or environment (five systems); Traditional with local breeds in small-scale production (three systems) and Organic (two systems). Data were collected with a questionnaire from nine breeding organisations providing animals and semen to the studied farming systems and from, on average, five farmers per farming system. The sustainability assessment of breeding activities was performed in four dimensions. The first dimension described whether the market for the product was well defined, and whether the breeding goal reflected the farming system and the farmers' demands. The second dimension described recording and selection procedures, together with genetic change in traits that were important in the system. The third dimension described genetic variation, both within and between pig breeds. The fourth dimension described the management of the breeding organisation, including communication, transparency, and technical and human resources. The results show substantial differences in the sustainability of breeding activities, both between farming systems within the same category and between different categories of farming systems. The breeding activities are assessed to be more sustainable for conventional systems than for differentiated systems in three of the four dimensions. In most differentiated farming systems, breeding goals are not related to the system, as these systems use the same genetic material as conventional systems. The breeds used in Traditional farming systems are important for genetic biodiversity, but the small scale of these systems renders them vulnerable. It is hoped that, by reflecting on different aspects of sustainability, this study will encourage sustainable developments in pig production.

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.

Monitoring of In-Field Variability for Site Specific Crop Management Through Open Geospatial Information

NASA Astrophysics Data System (ADS)

Řezník, T.; Lukas, V.; Charvát, K.; Charvát, K., Jr.; Horáková, Š.; Křivánek, Z.; Herman, L.

2016-06-01

The agricultural sector is in a unique position due to its strategic importance around the world. It is crucial for both citizens (consumers) and the economy (both regional and global), which, ideally, should ensure that the whole sector is a network of interacting organisations. It is important to develop new tools, management methods, and applications to improve the management and logistic operations of agricultural producers (farms) and agricultural service providers. From a geospatial perspective, this involves identifying cost optimization pathways, reducing transport, reducing environmental loads, and improving the energy balance, while maintaining production levels, etc. This paper describes the benefits of, and open issues arising from, the development of the Open Farm Management Information System. Emphasis is placed on descriptions of available remote sensing and other geospatial data, and their harmonization, processing, and presentation to users. At the same time, the FOODIE platform also offers a novel approach of yield potential estimations. Validation for one farm demonstrated 70% successful rate when comparing yield results at a farm counting 1'284 hectares on one hand and results of a theoretical model of yield potential on the other hand. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture and water pollution monitoring by means of remote sensing.

Water resource protection in Australia: Links between land use and river health with a focus on stubble farming systems

NASA Astrophysics Data System (ADS)

Bowmer, Kathleen H.

2011-06-01

SummaryStubble farming (conservation farming, minimum tillage, zero tillage) has increased in Australia over several decades with claims of improved productivity, landscape stability and environmental benefit including ecosystem services downstream, yet recent audits show a dramatic and general decline in river health. This review explores explanations for this apparent anomaly. Many confounding factors complicate interactions between land use and river condition and may disguise or over-ride the potential benefits of adoption of stubble systems or other improvements in agricultural land use practice. These factors include climate change and variability; land use changes including an increase in bushfires, growth of farm dams and afforestation; lag times between land use change and expression of benefits in river systems; use of inappropriate scale that disguises local benefit; variations in the extent of ecosystem resilience; impacts of river regulation; and impacts of introduced species. Additionally, the value of river condition and utility is complicated by different local or regional perceptions and by contrasting rural and urban outlooks. The use of indicators, risk frameworks and biophysical modelling may help elucidate the complex relationships between land use and downstream ecosystem impact. The strengthening of local, regional and catchment scale approaches is advocated. This includes the re-integration of land management and governance with water management and planning. It is encouraging that farmers are themselves developing systems to optimise trade-offs between on-farm activities and ecosystem service benefits. This approach needs to be supported and extended.

Challenges of agricultural monitoring: integration of the Open Farm Management Information System into GEOSS and Digital Earth

NASA Astrophysics Data System (ADS)

Řezník, T.; Kepka, M.; Charvát, K.; Charvát, K., Jr.; Horáková, S.; Lukas, V.

2016-04-01

From a global perspective, agriculture is the single largest user of freshwater resources, each country using an average of 70% of all its surface water supplies. An essential proportion of agricultural water is recycled back to surface water and/or groundwater. Agriculture and water pollution is therefore the subject of (inter)national legislation, such as the Clean Water Act in the United States of America, the European Water Framework Directive, and the Law of the People's Republic of China on the Prevention and Control of Water Pollution. Regular monitoring by means of sensor networks is needed in order to provide evidence of water pollution in agriculture. This paper describes the benefits of, and open issues stemming from, regular sensor monitoring provided by an Open Farm Management Information System. Emphasis is placed on descriptions of the processes and functionalities available to users, the underlying open data model, and definitions of open and lightweight application programming interfaces for the efficient management of collected (spatial) data. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture pollution monitoring. The final part of the paper deals with the integration of the Open Farm Management Information System into the Digital Earth framework.

Exposure to Inhalable Dust, Endotoxin, and Total Volatile Organic Carbons on Dairy Farms Using Manual and Automated Feeding Systems.

PubMed

Basinas, Ioannis; Cronin, Garvin; Hogan, Victoria; Sigsgaard, Torben; Hayes, James; Coggins, Ann Marie

2017-04-01

Agricultural workers tend to have high exposures to organic dusts which may induce or exacerbate respiratory disorders. Studies investigating the effect of work tasks and farm characteristics on organic dust exposures among farm workers suggest that handling of animal feed is an important exposure determinant; however, the effect of the animal feeding system has not been explored in any detail. To measure the exposure of Irish dairy farmers to inhalable dust, endotoxin, and total volatile organic compounds (TVOCs) during parlour work and to explore whether levels of exposure to these agents depend on the applied feeding system in the farms. Thirty-eight personal exposure measurements were collected from farmers across seven dairy farms. The farms used manual, loft, or semi-automated feeding systems. Information on worker tasks and farm characteristics was collected during the surveys. Associations between exposure concentrations and feeding systems, worker tasks, and other farm characteristics were explored in linear mixed-effect regression models with farmer identity treated as a random effect. Exposure concentrations were variable and had a geometric mean (GM; geometric standard deviation) of 1.5 mg m-3 (1.8) for inhalable dust and 128 EU m-3 (2.5) for endotoxin. More than 50% of the exposure measurements for endotoxin, and organic dust exceeded recommended health-based occupational exposure limits. Endotoxin levels were somewhat lower in farms using semi-automatic feeding systems when compared to those using manual feeding systems but in multivariate regression analysis associations were not statistically significant (β = -0.54, P = 0.4). Performance of activities related to handling and spreading of hay or straw was the strongest determinant for both inhalable dust and endotoxin exposure (β = 0.78, P ≤ 0.001; β = 0.72, P = 0.02, respectively). The level of dust exposure increased also as a consequence of a lower outdoor temperature, and higher ratio of distributed feed per cow (P = 0.01). Stationary measurements of TVOC and CO2 concentrations inside the dairy parlours had a GM of 180 ppb (1.9) and 589 ppb (1.3), respectively. The use of cow teat disinfectants and building ventilation were both strong predictors of TVOC concentrations within parlours. Dairy farm workers can be exposed to high and variable levels of inhalable dust and endotoxin and may be at risk of respiratory disease. Results from this study suggest that exposure control strategies for organic dusts and TVOCs exposures should consider building ventilation and work tasks such as spreading of bedding material, using spray disinfectants and animal feeding. Until effective permanent engineering controls are established farm workers should be encouraged to wear respiratory protective equipment during these tasks. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

7 CFR 1470.6 - Eligibility requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... producer must be the operator in the Farm Service Agency (FSA) farm records management system. Potential applicants that are not in the FSA farm records management system must establish records with FSA. Potential applicants whose records are not current in the FSA farm records management system must update those records...

7 CFR 1470.6 - Eligibility requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... producer must be the operator in the Farm Service Agency (FSA) farm records management system. Potential applicants that are not in the FSA farm records management system must establish records with FSA. Potential applicants whose records are not current in the FSA farm records management system must update those records...

7 CFR 1470.6 - Eligibility requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... producer must be the operator in the Farm Service Agency (FSA) farm records management system. Potential applicants that are not in the FSA farm records management system must establish records with FSA. Potential applicants whose records are not current in the FSA farm records management system must update those records...

7 CFR 1470.6 - Eligibility requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... producer must be the operator in the Farm Service Agency (FSA) farm records management system. Potential applicants that are not in the FSA farm records management system must establish records with FSA. Potential applicants whose records are not current in the FSA farm records management system must update those records...

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

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.

Integrated Water Resources Simulation Model for Rural Community

NASA Astrophysics Data System (ADS)

Li, Y.-H.; Liao, W.-T.; Tung, C.-P.

2012-04-01

The purpose of this study is to develop several water resources simulation models for residence houses, constructed wetlands and farms and then integrate these models for a rural community. Domestic and irrigation water uses are the major water demand in rural community. To build up a model estimating domestic water demand for residence houses, the average water use per person per day should be accounted first, including water uses of kitchen, bathroom, toilet and laundry. On the other hand, rice is the major crop in the study region, and its productive efficiency sometimes depends on the quantity of irrigation water. The water demand can be estimated by crop water use, field leakage and water distribution loss. Irrigation water comes from rainfall, water supply system and reclaimed water which treated by constructed wetland. In recent years, constructed wetlands play an important role in water resources recycle. They can purify domestic wastewater for water recycling and reuse. After treating from constructed wetlands, the reclaimed water can be reused in washing toilets, watering gardens and irrigating farms. Constructed wetland is one of highly economic benefits for treating wastewater through imitating the processing mechanism of natural wetlands. In general, the treatment efficiency of constructed wetlands is determined by evapotranspiration, inflow, and water temperature. This study uses system dynamics modeling to develop models for different water resource components in a rural community. Furthermore, these models are integrated into a whole system. The model not only is utilized to simulate how water moves through different components, including residence houses, constructed wetlands and farms, but also evaluates the efficiency of water use. By analyzing the flow of water, the water resource simulation model can optimizes water resource distribution under different scenarios, and the result can provide suggestions for designing water resource system of a rural community. Keywords: Water Resources, Simulation Model, Domestic Water, Irrigation, Constructed Wetland, Rural Community

12 CFR 620.4 - Preparing and providing the annual report.

Code of Federal Regulations, 2010 CFR

2010-01-01

....4 Section 620.4 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DISCLOSURE TO... institution of the Farm Credit System must: (1) Prepare and send to the Farm Credit Administration an... copy of its annual report on its Web site when it sends the report electronically to the Farm Credit...

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.

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.

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.

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

Biogas Technology Application in Western Kenya-A Field Investigation in Nandi and Bomet Counties

NASA Astrophysics Data System (ADS)

Venort, Taisha

The integration of biogas technology into Kenyan farming systems is becoming more common since the launch of the Kenya National Biogas Programme (KENDBIP). A comprehensive assessment of the status, operation of biogas plants constructed through KENDBIP, and their role within rural farming systems, is undertaken in two important dairy herds of Kenya (i.e., Nandi and Bomet counties), towards understanding factors affecting applications, for energy and agronomic use. Data on farming systems, operation and application were collected from 242 farm households in both counties. A Binary Linear Regression model was developed to pinpoint constraint factors most influential to plants operation. Descriptive statistics were used to compare users' experiences, and capture farm households' trends in energy and fertilizer use. Higher operational rate in Bomet (77%) than Nandi (59%), reveal that plants' viability are impacted by subsidies 'liability schemes of local supporting programs. Records of partial substitution to biogas and bio-slurry seem to contribute to the reinforcement of local agro-forestry traditions through an increase in the adoption of zero-grazing practices, wood/tree lots retention, and more efficient agricultural land attribution in the smallholder context. These changes are all having a positive impact on farm households' livelihoods and food security. Key recommendations to biogas programs stakeholders are that local subsidy schemes take better account of liability towards local technicians, Quality Control responsibilities are decentralized to local enterprises, and Research & Development strategies further investigate biogas technology application in agriculture, and its role in directly impacted value chains (i.e., Dairy, African Leafy vegetables, Feed & Fodder), for better experiences by farmers.

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.

Antibiotic use by farmers to control mastitis as influenced by health advice and dairy farming systems.

PubMed

Poizat, A; Bonnet-Beaugrand, F; Rault, A; Fourichon, C; Bareille, N

2017-10-01

Mastitis is a bacterial disease common in dairy farms. Although knowledge about mastitis and its optimal technical management and treatment is now available, some dairy farmers still use antibiotics in inappropriate ways. Antibiotic use by farmers can be influenced by personal restraints and motivations, but it can be assumed that external drivers are also influential. The main purpose of this article is thus to analyse the choices of antibiotic and alternative medicine use for mastitis treatment and investigate the possible influence of two unexplored external drivers in dairy farms: (i) the health advice offered to farmers by farm advisors and veterinarians, (ii) the dairy farming system, as defined by combining the market valuation chosen for the milk, the level of intensification, and the perceived pressure related to investments. Research was based on 51 individual semi-structured interviews with farmers and their corresponding veterinarians and farm advisors. Based on verbatim, the use of antibiotics and alternative medicine by farmers for mastitis treatment, the vet-farmers interactions, and the dairy farming systems are described. The advisory relationships between farmers and farm advisors and between farmers and veterinarians influenced the implementation of selective dry cow therapy, but had very little effect on the use of alternative medicines by farmers, who were more willing to experiment alternative medicines than their advisors. The dairy farming system had very little influence on antibiotic use: some misuse of antibiotics was found whatever the farming system. Systematic dry cow therapy was also a widespread habit in all dairy farming systems except organic. The use of alternative medicine was common in all farming systems. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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

12 CFR 614.4590 - Equitable treatment of OFIs and Farm Credit System associations.

Code of Federal Regulations, 2010 CFR

2010-01-01

... differences in credit risk and administrative costs to the Farm Credit Bank or agricultural credit bank. (c... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Equitable treatment of OFIs and Farm Credit System associations. 614.4590 Section 614.4590 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT...

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.

Ships as future floating farm systems?

PubMed

Moustafa, Khaled

2018-04-03

Environmental and agriculture challenges such as severe drought, desertification, sprawling cities and shrinking arable lands in large regions in the world compel us to think about alternative and sustainable farming systems. Ongoing projects to build floating cities in the sea suggest that building specific ships for farming purposes (as farming ships or farming boats) would also be attainable to introduce new farming surfaces and boost food production worldwide to cope with food insecurity issues.

Modelling Management Practices in Viticulture while Considering Resource Limitations: The Dhivine Model

PubMed Central

Martin-Clouaire, Roger; Rellier, Jean-Pierre; Paré, Nakié; Voltz, Marc; Biarnès, Anne

2016-01-01

Many farming-system studies have investigated the design and evaluation of crop-management practices with respect to economic performance and reduction in environmental impacts. In contrast, little research has been devoted to analysing these practices in terms of matching the recurrent context-dependent demand for resources (labour in particular) with those available on the farm. This paper presents Dhivine, a simulation model of operational management of grape production at the vineyard scale. Particular attention focuses on representing a flexible plan, which organises activities temporally, the resources available to the vineyard manager and the process of scheduling and executing the activities. The model relies on a generic production-system ontology used in several agricultural production domains. The types of investigations that the model supports are briefly illustrated. The enhanced realism of the production-management situations simulated makes it possible to examine and understand properties of resource-constrained work-organisation strategies and possibilities for improving them. PMID:26990089

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.

12 CFR 609.905 - Background.

Code of Federal Regulations, 2014 CFR

2014-01-01

... facilitates electronic commerce (E-commerce) and allows Farm Credit System (System) institutions and their customers to use new technologies. System institutions may use E-commerce but must establish good business... Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ELECTRONIC COMMERCE General Rules § 609.905...

12 CFR 609.905 - Background.

Code of Federal Regulations, 2012 CFR

2012-01-01

... facilitates electronic commerce (E-commerce) and allows Farm Credit System (System) institutions and their customers to use new technologies. System institutions may use E-commerce but must establish good business... Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ELECTRONIC COMMERCE General Rules § 609.905...

12 CFR 609.905 - Background.

Code of Federal Regulations, 2013 CFR

2013-01-01

... facilitates electronic commerce (E-commerce) and allows Farm Credit System (System) institutions and their customers to use new technologies. System institutions may use E-commerce but must establish good business... Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ELECTRONIC COMMERCE General Rules § 609.905...

12 CFR 609.905 - Background.

Code of Federal Regulations, 2010 CFR

2010-01-01

... facilitates electronic commerce (E-commerce) and allows Farm Credit System (System) institutions and their customers to use new technologies. System institutions may use E-commerce but must establish good business... Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ELECTRONIC COMMERCE General Rules § 609.905...

12 CFR 609.905 - Background.

Code of Federal Regulations, 2011 CFR

2011-01-01

... facilitates electronic commerce (E-commerce) and allows Farm Credit System (System) institutions and their customers to use new technologies. System institutions may use E-commerce but must establish good business... Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ELECTRONIC COMMERCE General Rules § 609.905...

The Development of a Model Design to Assess Instruction in Farm Management in Terms of Economic Returns and the Understanding of Economic Principles.

ERIC Educational Resources Information Center

Rolloff, John August

The records of 27 farm operators participating in farm business analysis programs in 5 Ohio schools were studied to develop and test a model for determining the influence of the farm business analysis phase of vocational agriculture instruction in farm management. Economic returns were measured as ratios between 1965 program inputs and outputs…

Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S.

USDA-ARS?s Scientific Manuscript database

Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...

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.

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.

A regional assessment of the cost and effectiveness of mitigation measures for reducing nutrient losses to water and greenhouse gas emissions to air from pastoral farms.

PubMed

Vibart, Ronaldo; Vogeler, Iris; Dennis, Samuel; Kaye-Blake, William; Monaghan, Ross; Burggraaf, Vicki; Beautrais, Josef; Mackay, Alec

2015-06-01

Using a novel approach that links geospatial land resource information with individual farm-scale simulation, we conducted a regional assessment of nitrogen (N) and phosphorous (P) losses to water and greenhouse gas (GHG) emissions to air from the predominant mix of pastoral industries in Southland, New Zealand. An evaluation of the cost-effectiveness of several nutrient loss mitigation strategies applied at the farm-scale, set primarily for reducing N and P losses and grouped by capital cost and potential ease of adoption, followed an initial baseline assessment. Grouped nutrient loss mitigation strategies were applied on an additive basis on the assumption of full adoption, and were broadly identified as 'improved nutrient management' (M1), 'improved animal productivity' (M2), and 'restricted grazing' (M3). Estimated annual nitrate-N leaching losses occurring under representative baseline sheep and beef (cattle) farms, and representative baseline dairy farms for the region were 10 ± 2 and 32 ± 6 kg N/ha (mean ± standard deviation), respectively. Both sheep and beef and dairy farms were responsive to N leaching loss mitigation strategies in M1, at a low cost per kg N-loss mitigated. Only dairy farms were responsive to N leaching loss abatement from adopting M2, at no additional cost per kg N-loss mitigated. Dairy farms were also responsive to N leaching loss abatement from adopting M3, but this reduction came at a greater cost per kg N-loss mitigated. Only dairy farms were responsive to P-loss mitigation strategies, in particular by adopting M1. Only dairy farms were responsive to GHG abatement; greater abatement was achieved by the most intensified dairy farm system simulated. Overall, M1 provided for high levels of regional scale N- and P-loss abatement at a low cost per farm without affecting overall farm production, M2 provided additional N-loss abatement but only marginal P-loss abatement, whereas M3 provided the greatest N-loss abatement, but delivered no additional P abatement, and came at a large financial cost to farmers, sheep and beef farmers in particular. The modelling approach provides a farm-scale framework that can be extended to other regions to accommodate different farm production systems and performances, capturing the interactions between farm types, land use capabilities and production levels, as these influence nutrient losses and GHG emissions, and the effectiveness of mitigation strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

PubMed

Amirpour Haredasht, Sara; Polson, Dale; Main, Rodger; Lee, Kyuyoung; Holtkamp, Derald; Martínez-López, Beatriz

2017-06-07

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight. The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124). The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

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.

Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms

NASA Astrophysics Data System (ADS)

Zhong, Shuya; Pantelous, Athanasios A.; Beer, Michael; Zhou, Jian

2018-05-01

Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.

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

Organic fields sustain weed metacommunity dynamics in farmland landscapes.

PubMed

Henckel, Laura; Börger, Luca; Meiss, Helmut; Gaba, Sabrina; Bretagnolle, Vincent

2015-06-07

Agro-ecosystems constitute essential habitat for many organisms. Agricultural intensification, however, has caused a strong decline of farmland biodiversity. Organic farming (OF) is often presented as a more biodiversity-friendly practice, but the generality of the beneficial effects of OF is debated as the effects appear often species- and context-dependent, and current research has highlighted the need to quantify the relative effects of local- and landscape-scale management on farmland biodiversity. Yet very few studies have investigated the landscape-level effects of OF; that is to say, how the biodiversity of a field is affected by the presence or density of organically farmed fields in the surrounding landscape. We addressed this issue using the metacommunity framework, with weed species richness in winter wheat within an intensively farmed landscape in France as model system. Controlling for the effects of local and landscape structure, we showed that OF leads to higher local weed diversity and that the presence of OF in the landscape is associated with higher local weed biodiversity also for conventionally farmed fields, and may reach a similar biodiversity level to organic fields in field margins. Based on these results, we derive indications for improving the sustainable management of farming systems. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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.

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

Short-Term Planning of Hybrid Power System

NASA Astrophysics Data System (ADS)

Knežević, Goran; Baus, Zoran; Nikolovski, Srete

2016-07-01

In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

Carbon footprint and ammonia emissions of California beef production systems

USDA-ARS?s Scientific Manuscript database

Beef production is a recognized source of greenhouse gas (GHG) and ammonia (NH3) emissions; however, little information exists on the net emissions from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH3 ...

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.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Yield and Economic Performance of Organic and Conventional Cotton-Based Farming Systems – Results from a Field Trial in India

PubMed Central

Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M.; Mäder, Paul

2013-01-01

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007–2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1st crop cycle (cycle 1: 2007–2008) for cotton (−29%) and wheat (−27%), whereas in the 2nd crop cycle (cycle 2: 2009–2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (−1% in cycle 1, −11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems. PMID:24324659

Yield and economic performance of organic and conventional cotton-based farming systems--results from a field trial in India.

PubMed

Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M; Mäder, Paul

2013-01-01

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007-2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1(st) crop cycle (cycle 1: 2007-2008) for cotton (-29%) and wheat (-27%), whereas in the 2(nd) crop cycle (cycle 2: 2009-2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (-1% in cycle 1, -11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems.

Is the profitability of Canadian freestall farms associated with their performance on an animal welfare assessment?

PubMed

Villettaz Robichaud, M; Rushen, J; de Passillé, A M; Vasseur, E; Haley, D; Orsel, K; Pellerin, D

2018-03-01

Improving animal welfare on farm can sometimes require substantial financial investments. The Canadian dairy industry recently updated their Code of Practice for the care of dairy animals and created a mandatory on-farm animal care assessment (proAction Animal Care). Motivating dairy farmers to follow the recommendations of the Code of Practice and successfully meet the targets of the on-farm assessment can be enhanced by financial gain associated with improved animal welfare. The aim of the current study was to evaluate the association between meeting or not meeting several criteria from an on-farm animal welfare assessment and the farms' productivity and profitability indicators. Data from 130 freestall farms (20 using automatic milking systems) were used to calculate the results of the animal care assessment. Productivity and profitability indicators, including milk production, somatic cell count, reproduction, and longevity, were retrieved from the regional dairy herd improvement association databases. Economic margins over replacement costs were also calculated. Univariable and multivariable linear regression models were used to evaluate the associations between welfare and productivity and profitability indicators. The proportion of automatic milking system farms that met the proAction criterion for hock lesions was higher compared with parlor farms and lower for the neck lesion criterion. The proAction criterion for lameness prevalence was significantly associated with average corrected milk production per year. Average days in milk (DIM) at first breeding acted as an effect modifier for this association, resulting in a steeper increase of milk production in farms that met the criterion with increasing average DIM at first breeding. The reproduction and longevity indicators studied were not significantly associated with meeting or not meeting the proAction criteria investigated in this study. Meeting the proAction lameness prevalence parameter was associated with an increased profitability margin per cow over replacement cost by $236 compared with farms that did not. These results suggest that associations are present between meeting the lameness prevalence benchmark of the Animal Care proAction Initiative and freestall farms' productivity and profitability. Overall, meeting the animal-based criteria evaluated in this study was not detrimental to freestall farms' productivity and profitability. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

Farm-level feasibility of bioenergy depends on variations across multiple sectors

NASA Astrophysics Data System (ADS)

Myhre, Mitchell; Barford, Carol

2013-03-01

The potential supply of bioenergy from farm-grown biomass is uncertain due to several poorly understood or volatile factors, including land availability, yield variability, and energy prices. Although biomass production for liquid fuel has received more attention, here we present a case study of biomass production for renewable heat and power in the state of Wisconsin (US), where heating constitutes at least 30% of total energy demand. Using three bioenergy systems (50 kW, 8.8 MW and 50 MW) and Wisconsin farm-level data, we determined the net farm income effect of producing switchgrass (Panicum virgatum) as a feedstock, either for on-farm use (50 kW system) or for sale to an off-farm energy system operator (8.8 and 50 MW systems). In southern counties, where switchgrass yields approach 10 Mg ha-1 yr-1, the main determinants of economic feasibility were the available land area per farm, the ability to utilize bioheat, and opportunity cost assumptions. Switchgrass yield temporal variability was less important. For the state median farm size and switchgrass yield, at least 25% (50 kW system) or 50% (8.8 MW system) bioheat utilization was required to economically offset propane or natural gas heat, respectively, and purchased electricity. Offsetting electricity only (50 MW system) did not generate enough revenue to meet switchgrass production expenses. Although the opportunity cost of small-scale (50 kW) on-farm bioenergy generation was higher, it also held greater opportunity for increasing farm net income, especially by replacing propane-based heat.

Evaluation of the use of an on-farm system for bacteriologic culture of milk from cows with low-grade mastitis.

PubMed

Neeser, Nicole L; Hueston, William D; Godden, Sandra M; Bey, Russell F

2006-01-15

To determine factors associated with implementation and use of an on-farm system for bacteriologic culture of milk from cows with lowgrade mastitis, including information on how producers used the on-farm bacteriologic culture system to guide antimicrobial selection practices and the resulting impact on patterns of antimicrobial use. Retrospective cohort study. Producers of 81 dairy farms. Farms that used an on-farm system for bacteriologic culture of milk from January 2001 to July 2003 were surveyed. Over half of those producers continuing to use the on-farm culture delayed antimicrobial treatment pending results of bacteriologic culture. Most other producers initiated empirical antimicrobial treatment while bacteriologic culture results were pending. Several barriers to the use of an on-farm system were identified. Significant reductions in rates of antimicrobial use were detected when comparing antimicrobial use rates before and during use of the on-farm system. Most producers chose to treat cows with mastitis caused by gram-positive pathogens with antimicrobials, whereas treatment choices for cows with mastitis caused by gram-negative bacteria and in cases in which no growth was detected varied. Readily available results permit antimicrobial selections to be made on the basis of the causative agent of mastitis. Adoption of an on-farm system for bacteriologic culture of milk may result in significant reductions in the percentage of cows treated with antimicrobials. Decreasing antimicrobial use may have several benefits including preventing unnecessary discarding of milk, decreasing the potential for drug residues in milk, and improving treatment outcomes as a result of targeted treatments.

7 CFR 4290.720 - Enterprises that may be ineligible for Financing.

Code of Federal Regulations, 2012 CFR

2012-01-01

... wells, wind farms, or power facilities (including solar, geothermal, hydroelectric, or biomass power... the majority of the activities of the Enterprise. Examples include motion pictures. (e) Farm land... ineligible for Farm Credit System Assistance. If one or more Farm Credit System Institutions or their...

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.

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.

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.

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/).

Comparing technical efficiency of farms with an automatic milking system and a conventional milking system.

PubMed

Steeneveld, W; Tauer, L W; Hogeveen, H; Oude Lansink, A G J M

2012-12-01

Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a new management approach and a corresponding change in labor tasks. Together with labor savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs and depreciation. Therefore, it is hypothesized that AMS farms differ from CMS farms in capital:labor ratio and possibly their technical efficiency, at least during a transition learning period. The current study used actual farm accounting data from dairy farms in the Netherlands with an AMS and a CMS to investigate the empirical substitution of capital for labor in the AMS farms and to determine if the technical efficiency of the AMS farms differed from the CMS farms. The technical efficiency estimates were obtained with data envelopment analysis. The 63 AMS farms and the 337 CMS farms in the data set did not differ in general farm characteristics such as the number of cows, number of hectares, and the amount of milk quota. Farms with AMS have significantly higher capital costs (€12.71 per 100 kg of milk) than CMS farms (€10.10 per 100 kg of milk). Total labor costs and net outputs were not significantly different between AMS and CMS farms. A clear substitution of capital for labor with the adoption of an AMS could not be observed. Although the AMS farms have a slightly lower technical efficiency (0.76) than the CMS farms (0.78), a significant difference in these estimates was not observed. This indicates that the farms were not different in their ability to use inputs (capital, labor, cows, and land) to produce outputs (total farm revenues). The technical efficiency of farms invested in an AMS in 2008 or earlier was not different from the farms invested in 2009 or 2010, indicating that a learning effect during the transition period was not observed. The results indicate that the economic performance of AMS and CMS farms are similar. What these results show is that other than higher capital costs, the use of AMS rather than a CMS does not affect farm efficiency and that the learning costs to use an AMS are not present as measured by any fall in technical efficiency. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Quantifying Uncertainty of Wind Power Production Through an Analog Ensemble

NASA Astrophysics Data System (ADS)

Shahriari, M.; Cervone, G.

2016-12-01

The Analog Ensemble (AnEn) method is used to generate probabilistic weather forecasts that quantify the uncertainty in power estimates at hypothetical wind farm locations. The data are from the NREL Eastern Wind Dataset that includes more than 1,300 modeled wind farms. The AnEn model uses a two-dimensional grid to estimate the probability distribution of wind speed (the predictand) given the values of predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind. The meteorological data is taken from the NCEP GFS which is available on a 0.25 degree grid resolution. The methodology first divides the data into two classes: training period and verification period. The AnEn selects a point in the verification period and searches for the best matching estimates (analogs) in the training period. The predictand value at those analogs are the ensemble prediction for the point in the verification period. The model provides a grid of wind speed values and the uncertainty (probability index) associated with each estimate. Each wind farm is associated with a probability index which quantifies the degree of difficulty to estimate wind power. Further, the uncertainty in estimation is related to other factors such as topography, land cover and wind resources. This is achieved by using a GIS system to compute the correlation between the probability index and geographical characteristics. This study has significant applications for investors in renewable energy sector especially wind farm developers. Lower level of uncertainty facilitates the process of submitting bids into day ahead and real time electricity markets. Thus, building wind farms in regions with lower levels of uncertainty will reduce the real-time operational risks and create a hedge against volatile real-time prices. Further, the links between wind estimate uncertainty and factors such as topography and wind resources, provide wind farm developers with valuable information regarding wind farm siting.

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.

Impact of Offshore Wind Power Integrated by VSC-HVDC on Power Angle Stability of Power Systems

NASA Astrophysics Data System (ADS)

Lu, Haiyang; Tang, Xisheng

2017-05-01

Offshore wind farm connected to grid by VSC-HVDC loses frequency support for power system, so adding frequency control in wind farm and VSC-HVDC system is an effective measure, but it will change wind farm VSC-HVDC’s transient stability on power system. Through theoretical analysis, concluding the relationship between equivalent mechanical power and electromagnetic power of two-machine system with the active power of wind farm VSC-HVDC, then analyzing the impact of wind farm VSC-HVDC with or without frequency control and different frequency control parameters on angle stability of synchronous machine by EEAC. The validity of theoretical analysis has been demonstrated through simulation in PSCAD/EMTDC.

Optimal supplementary frequency controller design using the wind farm frequency model and controller parameters stability region.

PubMed

Toulabi, Mohammadreza; Bahrami, Shahab; Ranjbar, Ali Mohammad

2018-03-01

In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is first characterized. The proposed controller is then designed based on the obtained open loop system. The stability region associated with the controller parameters is analytically determined by decomposing the closed-loop system's characteristic polynomial into the odd and even parts. The performance of the proposed controller is evaluated through extensive simulations in MATLAB/Simulink environment in a power system comprising a high penetration of VSWTs equipped with the proposed controller. Finally, based on the obtained feasible area and appropriate objective function, the optimal values associated with the controller parameters are determined using the genetic algorithm (GA). Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions

USDA-ARS?s Scientific Manuscript database

A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...

Stability Augmentation of Wind Farm using Variable Speed Permanent Magnet Synchronous Generator

NASA Astrophysics Data System (ADS)

Rosyadi, Marwan; Muyeen, S. M.; Takahashi, Rion; Tamura, Junji

This paper presents a new control strategy of variable speed permanent magnet wind generator for stability augmentation of wind farm including fixed speed wind turbine with Induction Generator (IG). A new control scheme is developed for two levels back-to-back converters of Permanent Magnet Synchronous Generator (PMSG), by which both active and reactive powers delivered to the grid can be controlled easily. To avoid the converter damage, the DC link protection controller is also proposed in order to protect the dc link circuit during fault condition. To evaluate the control capability of the proposed controllers, simulations are performed on two model systems composed of wind farms connected to an infinite bus. From transient and steady state analyses by using PSCAD/EMTDC, it is concluded that the proposed control scheme is very effective to improve the stability of wind farm for severe network disturbance and randomly fluctuating wind speed.

Modelling potential production of macroalgae farms in UK and Dutch coastal waters

NASA Astrophysics Data System (ADS)

van der Molen, Johan; Ruardij, Piet; Mooney, Karen; Kerrison, Philip; O'Connor, Nessa E.; Gorman, Emma; Timmermans, Klaas; Wright, Serena; Kelly, Maeve; Hughes, Adam D.; Capuzzo, Elisa

2018-02-01

There is increasing interest in macroalgae farming in European waters for a range of applications, including food, chemical extraction for biofuel production. This study uses a 3-D numerical model of hydrodynamics and biogeochemistry to investigate potential production and environmental effects of macroalgae farming in UK and Dutch coastal waters. The model included four experimental farms in different coastal settings in Strangford Lough (Northern Ireland), in Sound of Kerrera and Lynn of Lorne (north-west Scotland) and in the Rhine plume (the Netherlands), as well as a hypothetical large-scale farm off the UK north Norfolk coast. The model could not detect significant changes in biogeochemistry and plankton dynamics at any of the farm sites averaged over the farming season. The results showed a range of macroalgae growth behaviours in response to simulated environmental conditions. These were then compared with in situ observations where available, showing good correspondence for some farms and less good correspondence for others. At the most basic level, macroalgae production depended on prevailing nutrient concentrations and light conditions, with higher levels of both resulting in higher macroalgae production. It is shown that under non-elevated and interannually varying winter nutrient conditions, farming success was modulated by the timings of the onset of increasing nutrient concentrations in autumn and nutrient drawdown in spring. Macroalgae carbohydrate content also depended on nutrient concentrations, with higher nutrient concentrations leading to lower carbohydrate content at harvest. This will reduce the energy density of the crop and thus affect its suitability for conversion into biofuel. For the hypothetical large-scale macroalgae farm off the UK north Norfolk coast, the model suggested high, stable farm yields of macroalgae from year to year with substantial carbohydrate content and limited environmental effects.

Multi-agent modeling and simulation of farmland use change in the farming-pastoral zone: A case study of Qianjingou Town in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Yan, H.

2015-12-01

Farmland is the most basic material conditions for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both of the sustainable rural livelihoods and sustainable farmland use into account has vital significance of theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems together, and natural factors and social factors that are related to its changing process need to be considered when modeling farmland changing process. This paper takes Qianjingou Town in Inner Mongolia farming-pastoral zone as study area. From the perspective of the relationship between households' livelihoods and farmland use, this study builds the process mechanism of farmland use change based on questionnaires data, and constructs multi-agent simulation model of farmland use change with the help of Eclipse and Repast toolbox. Through simulating the relationship between natural factors (with geographical location) and households' behaviors, this paper systematically simulates households' renting and abandoning farmland behaviors, and truly describes dynamic interactions between households' livelihoods and factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (households' family structures, economic development and government policies). In the end, this study scientifically predicts farmland use change trend in the future 30 years. The simulation results show that, the number of abandoned and sublet farmland plots has a gradually increasing trend, the number of non-farm households and pure-outwork households has a remarkable increasing trend, and the number of part-farm households and pure-farm households shows a decreasing trend. Households' livelihoods sustainability in the study area is confronted with increasing pressure, and households' nonfarm employment has an increasing trend, while regional appropriate-scale agricultural management can be maintained. The research results establish the theory foundation and basic method for developing sustainable farmland use managements that can both meet households' willing and guarantee grain and ecology security.

12 CFR 619.9140 - Farm Credit bank(s).

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Farm Credit bank(s). 619.9140 Section 619.9140 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DEFINITIONS § 619.9140 Farm Credit bank(s). Except as otherwise defined, the term Farm Credit bank(s) includes Farm Credit Banks...

12 CFR 619.9140 - Farm Credit bank(s).

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Farm Credit bank(s). 619.9140 Section 619.9140 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DEFINITIONS § 619.9140 Farm Credit bank(s). Except as otherwise defined, the term Farm Credit bank(s) includes Farm Credit Banks...

76 FR 20668 - Farm Credit System Insurance Corporation Board; Regular Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-13

... Plan. C. New Business Presentation of 2010 Audits Results. Closed Sesson FCSIC Report on System... Meeting AGENCY: Farm Credit System Insurance Corporation. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the...

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.

Assessing biodiversity on the farm scale as basis for ecosystem service payments.

PubMed

von Haaren, Christina; Kempa, Daniela; Vogel, Katrin; Rüter, Stefan

2012-12-30

Ecosystem services payments must be based on a standardised transparent assessment of the goods and services provided. This is especially relevant in the context of EU agri-environmental programs, but also for organic-food companies that foster environmental services on their contractor farms. Addressing the farm scale is important because land users/owners are major recipients of payments and they could be more involved in data generation and conservation management. A standardised system for measuring on-farm biodiversity does not yet exist that concentrates on performance indicators and includes farmers in generating information. A method is required that produces ordinal or metric scaled assessment results as well as management measures. Another requirement is the ease of application, which includes the ease of gathering input data and understandability. In order to respond to this need, we developed a method which is designed for automated application in an open source farm assessment system named MANUELA. The method produces an ordinal scale assessment of biodiversity that includes biotopes, species, biotope connectivity and the influence of land use. In addition, specific measures for biotope types are proposed. The open source geographical information system OpenJump is used for the implementation of MANUELA. The results of the trial applications and robustness tests show that the assessment can be implemented, for the most part, using existing information as well as data available from farmers or advisors. The results are more sensitive for showing on-farm achievements and changes than existing biotope-type classifications. Such a differentiated classification is needed as a basis for ecosystem service payments and for designing effective measures. The robustness of the results with respect to biotope connectivity is comparable to that of complex models, but it should be further improved. Interviews with the test farmers substantiate that the assessment methods can be implemented on farms and they are understood by farmers. Copyright © 2012 Elsevier Ltd. All rights reserved.

Groundwater economics: An object-oriented foundation for integrated studies of irrigated agricultural systems

USDA-ARS?s Scientific Manuscript database

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...

Seasonality of parasitic helminths of Leporinus macrocephalus and their parasitism rates in farming systems in the Amazon.

PubMed

Martins, Williane Maria de Oliveira; Justo, Márcia Cristina Nascimento; Cárdenas, Melissa Querido; Cohen, Simone Chinicz

2017-01-01

The objective of the present study was to analyze the seasonality of parasitic helminths of Leporinus macrocephalus from fish farms in the municipality of Cruzeiro do Sul, Acre, Brazil, and their parasitism rates. Between June 2014 and March 2015, 200 specimens were sampled from two fish farms: one with a semi-intensive system and the other with an extensive system (100 fish from each farm: 50 during the dry season and 50 during the rainy season). Fifteen species of parasites were found, with seasonal variations of some according to the farming system. In the semi-intensive fish farm, there was greater prevalence of infection during the dry season. Also, Urocleidoides paradoxus, Procamallanus (Spirocamallanus) inopinatus, Goezia leporini and Rhabdochona (Rhabdochona) acuminata presented differences in their parasitism rates between the seasons. In the extensive fish farm, no variation in the prevalence of infection was observed between the seasons and two species Tereancistrum parvus and G. leporini demonstrated differences only regarding the mean intensity of infection. The data presented here may help fish farmers to understand the parasite dynamics of L. macrocephalus in farming systems during the dry and rainy seasons in the state of Acre.

Fact sheets and slides summarizing Soil and Water Assessment Tool (SWAT) and Integrated Farm Systems Model (IFSM)

USDA-ARS?s Scientific Manuscript database

Water quality models address nonpoint source pollution from agricultural land at a range of scales and complexities and involve a variety of input parameters. It is often difficult for conservationists and stakeholders to understand and reconcile water quality results from different models. However,...

Dermal Exposure Assessment to Pesticides in Farming Systems in Developing Countries: Comparison of Models

PubMed Central

Lesmes Fabian, Camilo; Binder, Claudia R.

2015-01-01

In the field of occupational hygiene, researchers have been working on developing appropriate methods to estimate human exposure to pesticides in order to assess the risk and therefore to take the due decisions to improve the pesticide management process and reduce the health risks. This paper evaluates dermal exposure models to find the most appropriate. Eight models (i.e., COSHH, DERM, DREAM, EASE, PHED, RISKOFDERM, STOFFENMANAGER and PFAM) were evaluated according to a multi-criteria analysis and from these results five models (i.e., DERM, DREAM, PHED, RISKOFDERM and PFAM) were selected for the assessment of dermal exposure in the case study of the potato farming system in the Andean highlands of Vereda La Hoya, Colombia. The results show that the models provide different dermal exposure estimations which are not comparable. However, because of the simplicity of the algorithm and the specificity of the determinants, the DERM, DREAM and PFAM models were found to be the most appropriate although their estimations might be more accurate if specific determinants are included for the case studies in developing countries. PMID:25938911

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.

Potential of plant polyphenols to combat oxidative stress and inflammatory processes in farm animals.

PubMed

Gessner, D K; Ringseis, R; Eder, K

2017-08-01

Polyphenols are secondary plant metabolites which have been shown to exert antioxidative and antiinflamma tory effects in cell culture, rodent and human studies. Based on the fact that conditions of oxidative stress and inflammation are highly relevant in farm animals, polyphenols are considered as promising feed additives in the nutrition of farm animals. However, in contrast to many studies existing with model animals and humans, potential antioxidative and antiinflammatory effects of polyphenols have been less investigated in farm animals so far. This review aims to give an overview about potential antioxidative and antiinflammatory effects in farm animals. The first part of the review highlights the occurrence and the consequences of oxidative stress and inflammation on animal health and performance. The second part of the review deals with bioavailability and metabolism of polyphenols in farm animals. The third and main part of the review presents an overview of the findings from studies which investigated the effects of polyphenols of various plant sources in pigs, poultry and cattle, with particular consideration of effects on the antioxidant system and inflammation. Journal of Animal Physiology and Animal Nutrition © 2016 Blackwell Verlag GmbH.

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.

77 FR 55837 - Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-11

... FARM CREDIT SYSTEM INSURANCE CORPORATION Board Meeting AGENCY: Farm Credit System Insurance Corporation. ACTION: Regular meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the Board will be held...

Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

NASA Astrophysics Data System (ADS)

Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

2017-12-01

In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

Farm Women, Farming Systems, and Agricultural Structure: Suggestions for Scholarship.

ERIC Educational Resources Information Center

Flora, Cornelia Butler

1981-01-01

Suggests research agenda to analyze the class struggle occurring with farm women. Views the household as the unit of analysis, both internally from a farming-systems perspective and externally as responding to shifts in policy and technology. Available from: Rural Sociological Society, 325 Morgan Hall, University of Tennessee, Knoxville, TN 37916.…

"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

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.

Development of a decision support system for small reservoir irrigation systems in rainfed and drought prone areas.

PubMed

Balderama, Orlando F

2010-01-01

An integrated computer program called Cropping System and Water Management Model (CSWM) with a three-step feature (expert system-simulation-optimization) was developed to address a range of decision support for rainfed farming, i.e. crop selection, scheduling and optimisation. The system was used for agricultural planning with emphasis on sustainable agriculture in the rainfed areas through the use of small farm reservoirs for increased production and resource conservation and management. The application of the model was carried out using crop, soil, and climate and water resource data from the Philippines. Primarily, four sets of data representing the different rainfall classification of the country were collected, analysed, and used as input in the model. Simulations were also done on date of planting, probabilities of wet and dry period and with various capacities of the water reservoir used for supplemental irrigation. Through the analysis, useful information was obtained to determine suitable crops in the region, cropping schedule and pattern appropriate to the specific climate conditions. In addition, optimisation of the use of the land and water resources can be achieved in areas partly irrigated by small reservoirs.

7 CFR 1470.6 - Eligibility requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... operator in the Farm Service Agency (FSA) farm records management system for the agricultural operation... management system must establish records with FSA prior to application. Potential applicants whose records are not current in the FSA farm records management system must update those records with FSA prior to...

77 FR 2541 - Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-18

... FARM CREDIT SYSTEM INSURANCE CORPORATION Board Meeting AGENCY: Farm Credit System Insurance Corporation Board; Regular Meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the...

75 FR 1780 - Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-13

... FARM CREDIT SYSTEM INSURANCE CORPORATION Meetings AGENCY: Farm Credit System Insurance Corporation Board; Regular Meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of...

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.

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.

Ecologically sound management: aspects of modern sustainable deer farming systems.

PubMed

Pearse, A J; Drew, K R

1998-01-01

Modern deer farming systems have become increasingly intensive allowing strategic feeding for production and genetic improvement programmes. Meeting feeding standards that account for changing nutritional demands related to seasonality and reproductive state is critical. As the industry matures there is a growing awareness of the balance between retaining natural behaviour in producing breeding stock on larger extensive holdings and intensification systems for performance in young stock. Stocking rates are critical determinants of success as land use and capability needs are matched with an increasing stratification of stock type and purpose. Food product safety and welfare considerations of farmed deer are being driven by consumer demands. Farm quality assurance and codes of practice are developing to ensure that deer farming meets and exceeds international expectations of land use and deer welfare in modern deer farming systems.

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.

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.

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/).

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.

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.

Developing an Integrated Model Framework for the Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

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

David Muth, Jr.; Jared Abodeely; Richard Nelson

Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues can have negative impacts on soil health. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist capable of simultaneously addressing all environmental factors that can limit availability of residue. The VE-Suite model integration framework has been used to couple a set of environmental process models to support agricultural residue removal decisions. The RUSLE2, WEPS, and Soil Conditioning Index models have been integrated. A disparate set of databases providing the soils, climate, and management practice datamore » required to run these models have also been integrated. The integrated system has been demonstrated for two example cases. First, an assessment using high spatial fidelity crop yield data has been run for a single farm. This analysis shows the significant variance in sustainably accessible residue across a single farm and crop year. A second example is an aggregate assessment of agricultural residues available in the state of Iowa. This implementation of the integrated systems model demonstrates the capability to run a vast range of scenarios required to represent a large geographic region.« less

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…

Evaluation of ecofriendly management practices of french beanrust (Uromyces appendiculatus) in organic farming system

NASA Astrophysics Data System (ADS)

Chhetry, G. K. N.; Mangang, H. C.

2012-09-01

Organic farming system emphasises on sustainable development of agriculture. The traditional agriculture system was much akin to the organic system but modernization of agriculture made a shift to this trend. The north east region of India is potential organic farming sites. Most of the farming systems are traditional and are organic by default; however crops in organic farming are prone to many fungal diseases. Hence for validation of the impact of organic practices on the disease development of plants, a study has been conducted for three years under natural environmental conditions on bean rust (Uromyces appendiculatus). Study includes ecofriendly practices like: plant extract treatment, intercropping of beans with maize, organic manure application, influence of cropping season and Trichoderma treatment. Rust is a major prevalent disease in the cultivation of beans as in other parts of the world. Detailed study of the disease in the organic environment and the impact of various treatments and agricultural agronomic practices would help in validation of the practices for the management of the disease in the organic farming system. In our study for three consecutive years it has been revealed that the practices of the traditional farmers likeplant extract application, intercropping, and manure application were found to have significant positive effects in reducing rust development in the bean fields. The treatment of farm yard manure resulted in development of lesser area under disease progress curve. The plant extract of Artemisia vulgaris has marked positive impact on reducing rust disease parameters. Foliar application of Trichoderma reduces the disease parameters of rust. This study would enhance information in understanding the impact of organic farming system on bean rust and would help in validitation of sustainable agricultural practices for use in organic farming system.

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.

Transition to farming more likely for small, conservative groups with property rights, but increased productivity is not essential

PubMed Central

Gallagher, Elizabeth M.; Shennan, Stephen J.; Thomas, Mark G.

2015-01-01

Theories for the origins of agriculture are still debated, with a range of different explanations offered. Computational models can be used to test these theories and explore new hypotheses; Bowles and Choi [Bowles S, Choi J-K (2013) Proc Natl Acad Sci USA 110(22):8830–8835] have developed one such model. Their model shows the coevolution of farming and farming-friendly property rights, and by including climate variability, replicates the timings for the emergence of these events seen in the archaeological record. Because the processes modeled occurred a long time ago, it can be difficult to justify exact parameter values; hence, we propose a fitting to idealized outcomes (FIO) method to explore the model’s parameter space in more detail. We have replicated the model of Bowles and Choi, and used the FIO method to identify complexities and interactions of the model previously unidentified. Our results indicate that the key parameters for the emergence of farming are group structuring, group size, conservatism, and farming-friendly property rights (lending further support to Bowles and Choi’s original proposal). We also find that although advantageous, it is not essential that farming productivity be greater than foraging productivity for farming to emerge. In addition, we highlight how model behaviors can be missed when gauging parameter sensitivity via a fix-all-but-one variation approach. PMID:26578766

Serological survey of Neospora caninum infection in cattle herds from Western Romania.

PubMed

Imre, Kálmán; Morariu, Sorin; Ilie, Marius S; Imre, Mirela; Ferrari, Nicola; Genchi, Claudio; Dărăbuş, Gheorghe

2012-06-01

Serum samples from 376 randomly selected adult cattle, from 25 farms located in 3 counties (Arad, Bihor, and Timiş) from western Romania, were sampled for Neospora caninum antibodies using a commercial ELISA-kit. Seroprevalence values and risk factors for neosporosis (cow age, breed, herd size, farming system, previous abortion, and number of farm dogs) were examined using a generalized linear mixed model with a binomial distribution. Overall, the seroprevalence of N. caninum was 27.7% (104/376) with a prevalence of 27.9% (24/86) in Arad, 26.9% (25/93) in Bihor, and 27.9% (55/197) in Timiş. Of 25 cattle herds, 23 were seropositive with a prevalence ranging from 10.0 to 52.2%. No correlation was found between N. caninum seropositivity and age, breed, herd size, breeding system, and previous abortion. The number of farm dogs was the only factor (P(Wald)  =  0.03) positively associated with seroprevalence in cows and can be considered the risk factor in the acquiring of infection. The present work is the first regarding serological evidence of N. caninum infection in cattle from western Romania.

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.

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.

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.

Grazing in an uncertain environment: Modeling the trade-off between production and robustness

USDA-ARS?s Scientific Manuscript database

Concern with the environmental, economic, and social impacts of the post-WWII model of agricultural intensification has led to renewed interest in grazing as a feeding strategy for temperate livestock farming systems. Putting the culture and utilization of grass at the core of livestock feeding not ...

Three Proposed Data Collection Models for Annual Inventories

Treesearch

Bill Bechtold; Ron McRoberts; Frank Spirek; Chuck Liff

2005-01-01

Three competing data collection models for the U.S. Department of Agriculture Forest Service Forest Inventory and Analysis (FIA) program?s annual inventories are presented. We show that in the presence of panel creep, the model now in place does not meet requirements of an annual inventory system mandated by the 1998 Farm Bill. Two data-collection models that use...

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

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

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.

12 CFR 619.9145 - Farm Credit Bank.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Farm Credit Bank. 619.9145 Section 619.9145 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DEFINITIONS § 619.9145 Farm Credit Bank. The term Farm Credit Bank refers to a bank resulting from the mandatory merger of the Federal land...

12 CFR 619.9145 - Farm Credit Bank.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Farm Credit Bank. 619.9145 Section 619.9145 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DEFINITIONS § 619.9145 Farm Credit Bank. The term Farm Credit Bank refers to a bank resulting from the mandatory merger of the Federal land...

Creating a model to detect dairy cattle farms with poor welfare using a national database.

PubMed

Krug, C; Haskell, M J; Nunes, T; Stilwell, G

2015-12-01

The objective of this study was to determine whether dairy farms with poor cow welfare could be identified using a national database for bovine identification and registration that monitors cattle deaths and movements. The welfare of dairy cattle was assessed using the Welfare Quality(®) protocol (WQ) on 24 Portuguese dairy farms and on 1930 animals. Five farms were classified as having poor welfare and the other 19 were classified as having good welfare. Fourteen million records from the national cattle database were analysed to identify potential welfare indicators for dairy farms. Fifteen potential national welfare indicators were calculated based on that database, and the link between the results on the WQ evaluation and the national cattle database was made using the identification code of each farm. Within the potential national welfare indicators, only two were significantly different between farms with good welfare and poor welfare, 'proportion of on-farm deaths' (p<0.01) and 'female/male birth ratio' (p<0.05). To determine whether the database welfare indicators could be used to distinguish farms with good welfare from farms with poor welfare, we created a model using the classifier J48 of Waikato Environment for Knowledge Analysis. The model was a decision tree based on two variables, 'proportion of on-farm deaths' and 'calving-to-calving interval', and it was able to correctly identify 70% and 79% of the farms classified as having poor and good welfare, respectively. The national cattle database analysis could be useful in helping official veterinary services in detecting farms that have poor welfare and also in determining which welfare indicators are poor on each particular farm. Copyright © 2015 Elsevier B.V. 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.

Wind farm optimization using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Ituarte-Villarreal, Carlos M.

In recent years, the wind power industry has focused its efforts on solving the Wind Farm Layout Optimization (WFLO) problem. Wind resource assessment is a pivotal step in optimizing the wind-farm design and siting and, in determining whether a project is economically feasible or not. In the present work, three (3) different optimization methods are proposed for the solution of the WFLO: (i) A modified Viral System Algorithm applied to the optimization of the proper location of the components in a wind-farm to maximize the energy output given a stated wind environment of the site. The optimization problem is formulated as the minimization of energy cost per unit produced and applies a penalization for the lack of system reliability. The viral system algorithm utilized in this research solves three (3) well-known problems in the wind-energy literature; (ii) a new multiple objective evolutionary algorithm to obtain optimal placement of wind turbines while considering the power output, cost, and reliability of the system. The algorithm presented is based on evolutionary computation and the objective functions considered are the maximization of power output, the minimization of wind farm cost and the maximization of system reliability. The final solution to this multiple objective problem is presented as a set of Pareto solutions and, (iii) A hybrid viral-based optimization algorithm adapted to find the proper component configuration for a wind farm with the introduction of the universal generating function (UGF) analytical approach to discretize the different operating or mechanical levels of the wind turbines in addition to the various wind speed states. The proposed methodology considers the specific probability functions of the wind resource to describe their proper behaviors to account for the stochastic comportment of the renewable energy components, aiming to increase their power output and the reliability of these systems. The developed heuristic considers a variable number of system components and wind turbines with different operating characteristics and sizes, to have a more heterogeneous model that can deal with changes in the layout and in the power generation requirements over the time. Moreover, the approach evaluates the impact of the wind-wake effect of the wind turbines upon one another to describe and evaluate the power production capacity reduction of the system depending on the layout distribution of the wind turbines.

77 FR 21099 - Farm Credit Administration Board; Sunshine Act; Regular Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-09

... Report on Farm Credit System Condition Farm Credit System Building Association Auditor's Report on 2011 Financial Audit Executive Session Meeting with Auditors \\1\\ \\1\\ Session Closed--Exempt pursuant to 5 U.S.C...

Effect of feed supplements on dry season milk yield and profitability of crossbred cows in Honduras.

PubMed

Reiber, Christoph; Peters, Michael; Möhring, Jens; Schultze-Kraft, Rainer

2013-06-01

The contribution of dry season silage feeding on daily milk yield (MY) and dairying profitability in terms of income over feed cost (IOFC) was evaluated in dual-purpose cattle production systems in Honduras. MY records of 34 farms from two milk collection centres were collected over a 2-year period. Farms were surveyed to obtain information on the type, quantity and cost of supplemented feed, breed type and number of lactating cows in each month. Farms were classified in silage farms (SF, with a short silage supplementation period), non-silage farms (NSF) and prototype farms (PF, with an extended silage supplementation period). Data were analysed using descriptive statistics and a linear mixed model approach. PF had significantly higher MY than SF and NSF but, due to higher expenses for both concentrate and silage, similar IOFC compared to NSF. SF had similar MY but lower IOFC compared to NSF, due to higher feed expenses. The effect of silage feeding, particularly maize silage, on MY was significant and superior to that of other forage supplements. Silage supplementation contributed to the highest MY and IOFC on farms with crossbred cows of >62.5 % Bos taurus and to the second highest profitability on farms with >87.5 % Bos indicus share. It is concluded that silage can play an important role in drought-constrained areas of the tropics and can contribute to profitable dairying, irrespective of breed.

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.

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.

CFD Study of the Performance of an Operational Wind Farm and its Impact on the Local Climate: CFD sensitivity to forestry modelling

NASA Astrophysics Data System (ADS)

Wylie, Scott; Watson, Simon

2013-04-01

Any past, current or projected future wind farm developments are highly dependent on localised climatic conditions. For example the mean wind speed, one of the main factors in assessing the economic feasibility of a wind farm, can vary significantly over length scales no greater than the size of a typical wind farm. Any additional heterogeneity at a potential site, such as forestry, can affect the wind resource further not accounting for the additional difficulty of installation. If a wind farm is sited in an environmentally sensitive area then the ability to predict the wind farm performance and possible impacts on the important localised climatic conditions are of increased importance. Siting of wind farms in environmentally sensitive areas is not uncommon, such as areas of peat-land as in this example. Areas of peat-land are important sinks for carbon in the atmosphere but their ability to sequester carbon is highly dependent on the local climatic conditions. An operational wind farm's impact on such an area was investigated using CFD. Validation of the model outputs were carried out using field measurements from three automatic weather stations (AWS) located throughout the site. The study focuses on validation of both wind speed and turbulence measurement, whilst also assessing the models ability to predict wind farm performance. The use of CFD to model the variation in wind speed over heterogeneous terrain, including wind turbines effects, is increasing in popularity. Encouraging results have increased confidence in the ability of CFD performance in complex terrain with features such as steep slopes and forests, which are not well modelled by the widely used linear models such as WAsP and MS-Micro. Using concurrent measurements from three stationary AWS across the wind farm will allow detailed validation of the model predicted flow characteristics, whilst aggregated power output information will allow an assessment of how accurate the model setup can predict wind farm performance. Given the dependence of the local climatic conditions influence on the peat-land's ability to sequester carbon, accurate predictions of the local wind and turbulence features will allow us to quantify any possible wind farm influences. This work was carried out using the commercially available Reynolds Averaged Navier-Stokes (RANS) CFD package ANSYS CFX. Utilising the Windmodeller add-on in CFX, a series of simulations were carried out to assess wind flow interactions through and around the wind farm, incorporating features such as terrain, forestry and rotor wake interactions. Particular attention was paid to forestry effects, as the AWS are located close to the vicinity of forestry. Different Leaf Area Densities (LAD) were tested to assess how sensitive the models output was to this change.

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.

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

Pathways to sustainable intensification through crop water management

NASA Astrophysics Data System (ADS)

MacDonald, Graham K.; D'Odorico, Paolo; Seekell, David A.

2016-09-01

How much could farm water management interventions increase global crop production? This is the central question posed in a global modelling study by Jägermeyr et al (2016 Environ. Res. Lett. 11 025002). They define the biophysical realm of possibility for future gains in crop production related to agricultural water practices—enhancing water availability to crops and expanding irrigation by reducing non-productive water consumption. The findings of Jägermeyr et al offer crucial insight on the potential for crop water management to sustainably intensify agriculture, but they also provide a benchmark to consider the broader role of sustainable intensification targets in the global food system. Here, we reflect on how the global crop water management simulations of Jägermeyr et al could interact with: (1) farm size at more local scales, (2) downstream water users at the river basin scale, as well as (3) food trade and (4) demand-side food system strategies at the global scale. Incorporating such cross-scale linkages in future research could highlight the diverse pathways needed to harness the potential of farm-level crop water management for a more productive and sustainable global food system.

Evaluation of new farming technologies in Ethiopia using the Integrated Decision Support System (IDSS).

PubMed

Clarke, Neville; Bizimana, Jean-Claude; Dile, Yihun; Worqlul, Abeyou; Osorio, Javier; Herbst, Brian; Richardson, James W; Srinivasan, Raghavan; Gerik, Thomas J; Williams, Jimmy; Jones, Charles A; Jeong, Jaehak

2017-01-31

This study investigates multi-dimensional impacts of adopting new technology in agriculture at the farm/village and watershed scale in sub-Saharan Africa using the Integrated Decision Support System (IDSS). Application of IDSS as an integrated modeling tool helps solve complex issues in agricultural systems by simultaneously assessing production, environmental, economic, and nutritional consequences of adopting agricultural technologies for sustainable increases in food production and use of scarce natural resources. The IDSS approach was applied to the Amhara region of Ethiopia, where the scarcity of resources and agro-environmental consequences are critical to agricultural productivity of small farm, to analyze the impacts of alternative agricultural technology interventions. Results show significant improvements in family income and nutrition, achieved through the adoption of irrigation technologies, proper use of fertilizer, and improved seed varieties while preserving environmental indicators in terms of soil erosion and sediment loadings. These pilot studies demonstrate the usefulness of the IDSS approach as a tool that can be used to predict and evaluate the economic and environmental consequences of adopting new agricultural technologies that aim to improve the livelihoods of subsistence farmers.

Initiative for Future Agricultural Food Systems (IFAFS) From Farm to School: Improving Small Farm Viability and School Meals

ERIC Educational Resources Information Center

Kish, Stacy

2008-01-01

Improving the nutritional value of school meals is a growing priority among school systems across the United States. To assist in this effort, the USDA's Cooperative State Research, Education, and Extension Service (CSREES) funded a coalition, which developed a new program called "From Farm to School: Improving Small Farm Viability and School…

Modeling Parasite Dynamics on Farmed Salmon for Precautionary Conservation Management of Wild Salmon

PubMed Central

Rogers, Luke A.; Peacock, Stephanie J.; McKenzie, Peter; DeDominicis, Sharon; Jones, Simon R. M.; Chandler, Peter; Foreman, Michael G. G.; Revie, Crawford W.; Krkošek, Martin

2013-01-01

Conservation management of wild fish may include fish health management in sympatric populations of domesticated fish in aquaculture. We developed a mathematical model for the population dynamics of parasitic sea lice (Lepeophtheirus salmonis) on domesticated populations of Atlantic salmon (Salmo salar) in the Broughton Archipelago region of British Columbia. The model was fit to a seven-year dataset of monthly sea louse counts on farms in the area to estimate population growth rates in relation to abiotic factors (temperature and salinity), local host density (measured as cohort surface area), and the use of a parasiticide, emamectin benzoate, on farms. We then used the model to evaluate management scenarios in relation to policy guidelines that seek to keep motile louse abundance below an average three per farmed salmon during the March–June juvenile wild Pacific salmon (Oncorhynchus spp.) migration. Abiotic factors mediated the duration of effectiveness of parasiticide treatments, and results suggest treatment of farmed salmon conducted in January or early February minimized average louse abundance per farmed salmon during the juvenile wild salmon migration. Adapting the management of parasites on farmed salmon according to migrations of wild salmon may therefore provide a precautionary approach to conserving wild salmon populations in salmon farming regions. PMID:23577082

Simulation of between-farm transmission of porcine reproductive and respiratory syndrome virus in Ontario, Canada using the North American Animal Disease Spread Model.

PubMed

Thakur, Krishna K; Revie, Crawford W; Hurnik, Daniel; Poljak, Zvonimir; Sanchez, Javier

2015-03-01

Porcine reproductive and respiratory syndrome (PRRS), a viral disease of swine, has major economic impacts on the swine industry. The North American Animal Disease Spread Model (NAADSM) is a spatial, stochastic, farm level state-transition modeling framework originally developed to simulate highly contagious and foreign livestock diseases. The objectives of this study were to develop a model to simulate between-farm spread of a homologous strain of PRRS virus in Ontario swine farms via direct (animal movement) and indirect (sharing of trucks between farms) contacts using the NAADSM and to compare the patterns and extent of outbreak under different simulated conditions. A total of 2552 swine farms in Ontario province were allocated to each census division of Ontario and geo-locations of the farms were randomly generated within the agriculture land of each Census Division. Contact rates among different production types were obtained using pig movement information from four regions in Canada. A total of 24 scenarios were developed involving various direct (movement of infected animals) and indirect (pig transportation trucks) contact parameters in combination with alternating the production type of the farm in which the infection was seeded. Outbreaks were simulated for one year with 1000 replications. The median number of farms infected, proportion of farms with multiple outbreaks and time to reach the peak epidemic were used to compare the size, progression and extent of outbreaks. Scenarios involving spread only by direct contact between farms resulted in outbreaks where the median percentage of infected farms ranged from 31.5 to 37% of all farms. In scenarios with both direct and indirect contact, the median percentage of infected farms increased to a range from 41.6 to 48.6%. Furthermore, scenarios with both direct and indirect contact resulted in a 44% increase in median epidemic size when compared to the direct contact scenarios. Incorporation of both animal movements and the sharing of trucks within the model indicated that the effect of direct and indirect contact may be nonlinear on outbreak progression. The increase of 44% in epidemic size when indirect contact, via sharing of trucks, was incorporated into the model highlights the importance of proper biosecurity measures in preventing transmission of the PRRS virus. Simulation of between-farm spread of the PRRS virus in swine farms has highlighted the relative importance of direct and indirect contact and provides important insights regarding the possible patterns and extent of spread of the PRRS virus in a completely susceptible population with herd demographics similar to those found in Ontario, Canada. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatiotemporal distribution of nitrogen dioxide within and around a large-scale wind farm - a numerical case study

NASA Astrophysics Data System (ADS)

Mo, Jingyue; Huang, Tao; Zhang, Xiaodong; Zhao, Yuan; Liu, Xiao; Li, Jixiang; Gao, Hong; Ma, Jianmin

2017-12-01

As a renewable and clean energy source, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around the world's largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an edge effect, which featured higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that both parameterization schemes yield higher concentration in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be the result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration level.

Performance Assessment Program for the Savannah River Site Liquid Waste Facilities - 13610

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

Rosenberger, Kent H.

2013-07-01

The Liquid Waste facilities at the U.S. Department of Energy's (DOE) Savannah River Site (SRS) are operated by Liquid Waste Operations contractor Savannah River Remediation LLC (SRR). A separate Performance Assessment (PA) is prepared to support disposal operations at the Saltstone Disposal Facility and closure evaluations for the two liquid waste tank farm facilities at SRS, F-Tank Farm and H-Tank Farm. A PA provides the technical basis and results to be used in subsequent documents to demonstrate compliance with the pertinent requirements identified in operations and closure regulatory guidance. The Saltstone Disposal Facility is subject to a State of Southmore » Carolina industrial solid waste landfill permit and the tank farms are subject to a state industrial waste water permit. The three Liquid Waste facilities are also subject to a Federal Facility Agreement approved by the State, DOE and the Environmental Protection Agency (EPA). Due to the regulatory structure, a PA is a key technical document reviewed by the DOE, the State of South Carolina and the EPA. As the waste material disposed of in the Saltstone Disposal Facility and the residual material in the closed tank farms 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, the U.S. Nuclear Regulatory Commission (NRC) is also a reviewing agency for the PAs. Pursuant to the Act, the NRC also has a continuing role to monitor disposal actions to assess compliance with stated performance objectives. The Liquid Waste PA program at SRS represents a continual process over the life of the disposal and closure operations. When the need for a PA or PA revision is identified, the first step is to develop a conceptual model to best represent the facility conditions. The conceptual model will include physical dimensions of the closed system, both the engineered and natural system, and modeling input parameters associated with the modeled features, both initial values (at the time of facility closure) and degradation rates/values. During the development of the PA, evaluations are conducted to reflect not only the results associated with the best available information at the time but also to evaluate potential uncertainties and sensitivities associated with the modeled system. While the PA will reflect the modeled system results from the best available information, it will also identify areas for future work to reduce overall PA uncertainties moving forward. DOE requires a PA Maintenance Program such that work continues to reduce model uncertainties, thus bolstering confidence in PA results that support regulatory decisions. This maintenance work may include new Research and Development activities or modeling as informed by previous PA results and other new information that becomes available. As new information becomes available, it is evaluated against previous PAs and appropriate actions are taken to ensure continued confidence in the regulatory decisions. Therefore, the PA program is a continual process that is not just the development of a PA but seeks to incorporate new information to reduce overall model uncertainty and provide continuing confidence in regulatory decisions. (author)« less

A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms.

PubMed

O'Brien, D; Capper, J L; Garnsworthy, P C; Grainger, C; Shalloo, L

2014-03-01

Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Reanalysis of the start of the UK 1967 to 1968 foot-and-mouth disease epidemic to calculate airborne transmission probabilities.

PubMed

Sanson, R L; Gloster, J; Burgin, L

2011-09-24

The aims of this study were to statistically reassess the likelihood that windborne spread of foot-and-mouth disease (FMD) virus (FMDV) occurred at the start of the UK 1967 to 1968 FMD epidemic at Oswestry, Shropshire, and to derive dose-response probability of infection curves for farms exposed to airborne FMDV. To enable this, data on all farms present in 1967 in the parishes near Oswestry were assembled. Cases were infected premises whose date of appearance of first clinical signs was within 14 days of the depopulation of the index farm. Logistic regression was used to evaluate the association between infection status and distance and direction from the index farm. The UK Met Office's NAME atmospheric dispersion model (ADM) was used to generate plumes for each day that FMDV was excreted from the index farm based on actual historical weather records from October 1967. Daily airborne FMDV exposure rates for all farms in the study area were calculated using a geographical information system. Probit analyses were used to calculate dose-response probability of infection curves to FMDV, using relative exposure rates on case and control farms. Both the logistic regression and probit analyses gave strong statistical support to the hypothesis that airborne spread occurred. There was some evidence that incubation period was inversely proportional to the exposure rate.

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

[Automated mapping of urban forests' disturbance and recovery in Nanjing, China].

PubMed

Lyu, Ying-ying; Zhuang, Yi-lin; Ren, Xin-yu; Li, Ming-shi; Xu, Wang-gu; Wang, Zhi

2016-02-01

Using Landsat TM/ETM dense time series observations spanning from 1987 to 2011, taking Laoshan forest farm and Purple Mountain as the research objects, the landsat ecosystem disturbance adaptive processing system (Ledaps) algorithm was used to generate surface reflectance datasets, which were fed to the vegetation change tracker model (VCT) model to derive urban forest disturbance and recovery products over Nanjing, followed by an intensive validation of the products. The results showed that there was a relatively high spatial agreement for forest disturbance products mapped by VCT, ranging from 65.4% to 95.0%. There was an apparent fluctuating forest disturbance and recovery rate over time, and the change trend of forest disturbance occurring at the two sites was roughly similar, but forest recovery was obviously different. Forest coverage in Purple Mountain was less than that in Laoshan forest farm, but the forest disturbance and recovery rates in Laoshan forest farm were larger than those in Purple Mountain.

Groundwater economics: An object-oriented foundation for integrated studies of irrigated agricultural systems

NASA Astrophysics Data System (ADS)

Steward, David R.; Peterson, Jeffrey M.; Yang, Xiaoying; Bulatewicz, Tom; Herrera-Rodriguez, Mauricio; Mao, Dazhi; Hendricks, Nathan

2009-05-01

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater wells and agricultural parcels is employed to couple these models using geographic information science technology and open modeling interface protocols. This approach is used to study the collective action problem of the common pool. Three different policies (existing, regulation, and incentive based) are studied in the semiarid grasslands overlying the Ogallala Aquifer in the central United States. Results show that while regulation using the prior appropriation doctrine and incentives using a water buy-back program may each achieve the same level of water savings across the study region, each policy has a different impact on spatial patterns of groundwater declines and farm level economic activity. This represents the first time that groundwater and econometric models of irrigated agriculture have been integrated at the well-parcel level and provides methods for scientific investigation of this coupled natural-human system. Results are useful for science to inform decision making and public policy debate.

Simulated Impact of Climate Change on Fremont Native American Maize Farming in Utah at the MCA-LIA Transition, ca. 12-14th c. CE

NASA Astrophysics Data System (ADS)

Thomson, M. J.; MacDonald, G. M.

2016-12-01

We present the results of a computational crop modeling experiment for ancient Fremont Native American Zea mays farming in the Uinta Basin, Utah, at the Medieval Climate Anomaly to Little Ice Age (MCA-LIA) transition, ca. 850-1450 CE. This period coincides with the rapid disappearance of complex Native American cultures from the American Southwest. The crop model (the Environment Policy Impact Calculator, EPIC) was driven by statistically downscaled precipitation, temperature and shortwave radiative flux from the Community Earth System Model Last Millennium Ensemble (CESM LME). We found that maize yield responded to changes in the model-reconstructed temperature and precipitation; and periods of reduced maize yields corresponded to the abandonment of higher elevation Fremont 14C-dated archaeological sites. EPIC produces good agreement between modeled and historically reported maize yields for the 19th century.

12 CFR 630.40 - Contents of the quarterly report to investors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... the System Audit Committee. (1) An interim balance sheet as of the end of the most recent fiscal.... 630.40 Section 630.40 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DISCLOSURE TO INVESTORS IN SYSTEMWIDE AND CONSOLIDATED BANK DEBT OBLIGATIONS OF THE FARM CREDIT SYSTEM Quarterly Reports...

Farm-Level Effects of Soil Conservation and Commodity Policy Alternatives: Model and Data Documentation.

ERIC Educational Resources Information Center

Sutton, John D.

This report documents a profit-maximizing linear programming (LP) model of a farm typical of a major corn-soybean producing area in the Southern Michigan-Northern Indiana Drift Plain. Following an introduction, a complete description of the farm is provided. The next section presents the LP model, which is structured to help analyze after-tax…

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

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

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

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

How best to geo-reference farms? A case study from Cornwall, England.

PubMed

Durr, P A; Froggatt, A E A

2002-11-29

The commonest way of geo-referencing farms as single points is using the location of the farmhouse as either read off a map or approximated by its postcode. While these two methods may be adequate for small farms, they are unlikely to be satisfactory for large ones, or alternatively when they are comprised of several discrete units or holdings. In order to investigate the best representation of the total farm polygon(s) by a single point, we undertook a study using nearly 500 actual farm boundaries in the county of Cornwall, England. For each farm, the farm boundaries were digitised, and its area and centroid determined using ArcView 3.2. A variety of point geo-referencing systems were tested to find the best single point location for a farm, as judged by the proportion of farm area captured. Whilst the centroid was found to capture the largest area, the main farm building was judged to be the best geo-referencing method for practical purposes. In contrast, the various systems of geo-coding using the farm postal address performed relatively poorly. Where there are separate parcels of land managed together in a single parish, they may be identified as a single unit, but if there are separate parcels in different parishes they should be identified as separate units.The implications of these results for Great Britain's national animal health information system (VETNET) are discussed.

Study of the ubiquitous hog farm system using wireless sensor networks for environmental monitoring and facilities control.

PubMed

Hwang, Jeonghwan; Yoe, Hyun

2010-01-01

Many hog farmers are now suffering from high pig mortality rates due to various wasting diseases and increased breeding costs, etc. It is therefore necessary for hog farms to implement systematic and scientific pig production technology to increase productivity and produce high quality pork in order to solve these problems. In this study, we describe such a technology by suggesting a ubiquitous hog farm system which applies WSN (Wireless Sensor Network) technology to the pig industry. We suggest that a WSN and CCTV (Closed-circuit television) should be installed on hog farms to collect environmental and image information which shall then help producers not only in monitoring the hog farm via the Web from outside the farm, but also facilitate the control of hog farm facilities in remote locations. In addition, facilities can be automatically controlled based on breeding environment parameters which are already set up and a SMS notice service to notify of deviations shall provide users with convenience. Hog farmers may increase production and improve pork quality through this ubiquitous hog farm system and prepare a database with information collected from environmental factors and the hog farm control devices, which is expected to provide information needed to design and implement suitable control strategies for hog farm operation.

Study of the Ubiquitous Hog Farm System Using Wireless Sensor Networks for Environmental Monitoring and Facilities Control

PubMed Central

Hwang, Jeonghwan; Yoe, Hyun

2010-01-01

Many hog farmers are now suffering from high pig mortality rates due to various wasting diseases and increased breeding costs, etc. It is therefore necessary for hog farms to implement systematic and scientific pig production technology to increase productivity and produce high quality pork in order to solve these problems. In this study, we describe such a technology by suggesting a ubiquitous hog farm system which applies WSN (Wireless Sensor Network) technology to the pig industry. We suggest that a WSN and CCTV (Closed-circuit television) should be installed on hog farms to collect environmental and image information which shall then help producers not only in monitoring the hog farm via the Web from outside the farm, but also facilitate the control of hog farm facilities in remote locations. In addition, facilities can be automatically controlled based on breeding environment parameters which are already set up and a SMS notice service to notify of deviations shall provide users with convenience. Hog farmers may increase production and improve pork quality through this ubiquitous hog farm system and prepare a database with information collected from environmental factors and the hog farm control devices, which is expected to provide information needed to design and implement suitable control strategies for hog farm operation. PMID:22163497

Communal breeding promotes a matrilineal social system where husband and wife live apart.

PubMed

Wu, Jia-Jia; He, Qiao-Qiao; Deng, Ling-Ling; Wang, Shi-Chang; Mace, Ruth; Ji, Ting; Tao, Yi

2013-05-07

The matrilineal Mosuo of southwest China live in large communal houses where brothers and sisters of three generations live together, and adult males walk to visit their wives only at night; hence males do not reside with their own offspring. This duolocal residence with 'walking' or 'visiting' marriage is described in only a handful of matrilineal peasant societies. Benefits to women of living with matrilineal kin, who cooperate with child-care, are clear. But why any kinship system can evolve where males invest more in their sister's offspring than their own is a puzzle for evolutionary anthropologists. Here, we present a new hypothesis for a matrilineal bias in male investment. We argue that, when household resources are communal, relatedness to the whole household matters more than relatedness to individual offspring. We use an inclusive fitness model to show that the more sisters (and other closely related females) co-reside, the more effort males should spend working on their sister's farm and less on their wife's farm. The model shows that paternity uncertainty may be a cause of lower overall work rates in males, but it is not likely to be the cause of a matrilineal bias. The bias in work effort towards working on their natal farm, and thus the duolocal residence and 'visiting marriage' system, can be understood as maximizing inclusive fitness in circumstances where female kin breed communally.

Push-pull farming systems.

PubMed

Pickett, John A; Woodcock, Christine M; Midega, Charles A O; Khan, Zeyaur R

2014-04-01

Farming systems for pest control, based on the stimulo-deterrent diversionary strategy or push-pull system, have become an important target for sustainable intensification of food production. A prominent example is push-pull developed in sub-Saharan Africa using a combination of companion plants delivering semiochemicals, as plant secondary metabolites, for smallholder farming cereal production, initially against lepidopterous stem borers. Opportunities are being developed for other regions and farming ecosystems. New semiochemical tools and delivery systems, including GM, are being incorporated to exploit further opportunities for mainstream arable farming systems. By delivering the push and pull effects as secondary metabolites, for example, (E)-4,8-dimethyl-1,3,7-nonatriene repelling pests and attracting beneficial insects, problems of high volatility and instability are overcome and compounds are produced when and where required. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

12 CFR 614.4000 - Farm Credit Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... institutions. (3) Farm Credit Banks, in their capacity as certified agricultural mortgage marketing facilities... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Farm Credit Banks. 614.4000 Section 614.4000 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS Lending...

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.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada.

PubMed

Foreman, Michael G G; Guo, Ming; Garver, Kyle A; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada

PubMed Central

Foreman, Michael G. G.; Guo, Ming; Garver, Kyle A.; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed. PMID:26114643

Sustainable, alternative farming practices as a means to simultaneously secure food production and reduce air pollution in East Asia

NASA Astrophysics Data System (ADS)

Tai, A. P. K.; Fung, K. M.; Yong, T.; Liu, X.

2015-12-01

Proper agricultural land management is essential for securing food supply and minimizing damage to the environment. Among available farming practices, relay strip intercropping and fertilizer application are commonly used, but to study their wider environmental implications and possible feedbacks we require an Earth system modeling framework. In this study, the effectiveness of a maize-soybean relay strip intercropping system and fertilizer reduction is investigated using a multi-model method. The DNDC (DeNitrification-DeComposition) model is used to simulate agricultural activities and their impacts on the environment through nitrogen emissions and changes in soil chemical composition. Crop yield, soil nutrient content and nitrogen emissions to the atmosphere in major agricultural regions of China are predicted under various cultivation scenarios. The GEOS-Chem global chemical transport model is then used to estimate the effects on downwind particle and ozone air pollution. We show that relay strip intercropping and optimal fertilization not only improve crop productivity, but also retain soil nutrients, reduce ammonia emission and mitigate downwind air pollution. By cutting 25% fertilization inputs but cultivating maize and soybean together in a relay strip intercropping system used with field studies, total crop production was improved slightly by 4.4% compared to monoculture with conventional amount of fertilizers. NH3 volatilization decreases by 29%, equivalent to saving the pollution-induced health damage costs by about US$2.5 billion per year. The possible feedback effects from atmospheric nitrogen deposition onto the croplands are also investigated. We show that careful management and better quantitative understanding of alternative farming practices hold huge potential in simultaneously addressing different global change issues including the food crisis, air pollution and climate change, and calls for greater collaboration between scientists, farmers and policy makers concerning these issues.

Development of an Upper Limb Power Assist System Using Pneumatic Actuators for Farming Lift-up Motion

NASA Astrophysics Data System (ADS)

Yagi, Eiichi; Harada, Daisuke; Kobayashi, Masaaki

A power assist system has lately attracted considerable attention to lifting-up an object without low back pain. We have been developing power assist systems with pneumatic actuators for the elbow and shoulder to farming support of lifting-up a bag of rice weighing 30kg. This paper describes the mechanism and control method of this power assist system. The pneumatic rotary actuator supports shoulder motion, and the air cylinder supports elbow motion. In this control method, the surface electromyogram(EMG) signals are used as input information of the controller. The joint support torques of human are calculated based on the antigravity term of necessary joint torques, which are estimated on the dynamics of a human approximated link model. The experimental results show the effectiveness of the proposed mechanism and control method of the power assist system.

12 CFR 614.4000 - Farm Credit Banks.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Farm Credit Banks. 614.4000 Section 614.4000 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS Lending Authorities § 614.4000 Farm Credit Banks. (a) Long-term real estate lending. Except to the extent such...

Requirements Verification Report AN Farm to 200 E Waste Transfer System for Project W-314 Tank Farm Restoration & Safe Operations

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

MCGREW, D.L.

2001-10-31

This Requirements Verification Report provides the traceability of how Project W-314 fulfilled the Project Development Specification requirements for the AN Farm to 200E Waste Transfer System Upgrade package.

No Evidence of Trade-Off between Farm Efficiency and Resilience: Dependence of Resource-Use Efficiency on Land-Use Diversity

PubMed Central

Kahiluoto, Helena; Kaseva, Janne

2016-01-01

Efficiency in the use of resources stream-lined for expected conditions could lead to reduced system diversity and consequently endanger resilience. We tested the hypothesis of a trade-off between farm resource-use efficiency and land-use diversity. We applied stochastic frontier production models to assess the dependence of resource-use-efficiency on land-use diversity as illustrated by the Shannon-Weaver index. Total revenue in relation to use of capital, land and labour on the farms in Southern Finland with a size exceeding 30 ha was studied. The data were extracted from the Finnish Profitability Bookkeeping data. Our results indicate that there is either no trade-off or a negligible trade-off of no economic importance. The small dependence of resource-use efficiency on land-use diversity can be positive as well as negative. We conclude that diversification as a strategy to enhance farm resilience does not necessarily constrain resource-use efficiency. PMID:27662475

77 FR 7558 - Withdrawal of Proposed Rule on Approval of Farm Credit System Lending Institutions in Federal...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-13

...-AI91 Withdrawal of Proposed Rule on Approval of Farm Credit System Lending Institutions in Federal... withdraws HUD's August 2011 rule that proposed to amend HUD's regulations to enable the direct lending... the direct lending institutions of the Farm Credit System to seek approval to participate in the FHA...

Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems.

PubMed

Mackenzie, S G; Leinonen, I; Ferguson, N; Kyriazakis, I

2015-06-01

The objective of the study was to develop a life cycle assessment (LCA) for pig farming systems that would account for uncertainty and variability in input data and allow systematic environmental impact comparisons between production systems. The environmental impacts of commercial pig production for 2 regions in Canada (Eastern and Western) were compared using a cradle-to-farm gate LCA. These systems had important contrasting characteristics such as typical feed ingredients used, herd performance, and expected emission factors from manure management. The study used detailed production data supplied by the industry and incorporated uncertainty/variation in all major aspects of the system including life cycle inventory data for feed ingredients, animal performance, energy inputs, and emission factors. The impacts were defined using 5 metrics-global warming potential, acidification potential, eutrophication potential (EP), abiotic resource use, and nonrenewable energy use-and were expressed per kilogram carcass weight at farm gate. Eutrophication potential was further separated into marine EP (MEP) and freshwater EP (FEP). Uncertainties in the model inputs were separated into 2 types: uncertainty in the data used to describe the system (α uncertainties) and uncertainty in impact calculations or background data that affects all systems equally (β uncertainties). The impacts of pig production in the 2 regions were systematically compared based on the differences in the systems (α uncertainties). The method of ascribing uncertainty influenced the outcomes. In eastern systems, EP, MEP, and FEP were lower (P < 0.05) when assuming that all uncertainty in the emission factors for leaching from manure application was β. This was mainly due to increased EP resulting from field emissions for typical ingredients in western diets. When uncertainty in these emission factors was assumed to be α, only FEP was lower in eastern systems (P < 0.05). The environmental impacts for the other impact categories were not significantly different between the 2 systems, despite their aforementioned differences. In conclusion, a probabilistic approach was used to develop an LCA that systematically dealt with uncertainty in the data when comparing multiple environmental impacts measures in pig farming systems for the first time. The method was used to identify differences between Canadian pig production systems but can also be applied for comparisons between other agricultural systems that include inherent variation.

A Novel Wind Speed Forecasting Model for Wind Farms of Northwest China

NASA Astrophysics Data System (ADS)

Wang, Jian-Zhou; Wang, Yun

2017-01-01

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon's Signed-Rank test, and Morgan-Granger-Newbold test tell us that the proposed model is different from the compared models.

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

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.

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.

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms

PubMed Central

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

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5–95%, 0.0058–0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10−5; 5–95%, 1.47 × 10−6–0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available. PMID:29686993

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms.

PubMed

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

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5-95%, 0.0058-0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10 -5 ; 5-95%, 1.47 × 10 -6 -0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available.

12 CFR 614.4240 - Collateral definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

....4240 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS... income and/or other collateral, absent the real estate, and the decision to extend credit was, in fact... staff evaluator from another Farm Credit System institution only if the employing institution is not...

12 CFR 614.4240 - Collateral definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

....4240 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS... income and/or other collateral, absent the real estate, and the decision to extend credit was, in fact... staff evaluator from another Farm Credit System institution only if the employing institution is not...

12 CFR 614.4240 - Collateral definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

....4240 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS... income and/or other collateral, absent the real estate, and the decision to extend credit was, in fact... staff evaluator from another Farm Credit System institution only if the employing institution is not...

12 CFR 614.4350 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS Lending and... indirectly. Excluded are a Farm Credit System association or other financing institution that comply with the... commitment to make a lease. (b) Commitment means a legally binding obligation to extend credit, enter into...

12 CFR 615.5045 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM FUNDING AND FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Collateral § 615.5045 Definitions. (a) Cost means the actual... accrued interest owed. (d) Secured interbank loan means a loan from one Farm Credit System bank to another...

12 CFR 614.4240 - Collateral definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

....4240 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS... income and/or other collateral, absent the real estate, and the decision to extend credit was, in fact... staff evaluator from another Farm Credit System institution only if the employing institution is not...

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

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes.

PubMed

Toma, Luiza; Mathijs, Erik

2007-04-01

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.

Wake Dynamics in the Atmospheric Boundary Layer Over Complex Terrain

NASA Astrophysics Data System (ADS)

Markfort, Corey D.

The goal of this research is to advance our understanding of atmospheric boundary layer processes over heterogeneous landscapes and complex terrain. The atmospheric boundary layer (ABL) is a relatively thin (˜ 1 km) turbulent layer of air near the earth's surface, in which most human activities and engineered systems are concentrated. Its dynamics are crucially important for biosphere-atmosphere couplings and for global atmospheric dynamics, with significant implications on our ability to predict and mitigate adverse impacts of land use and climate change. In models of the ABL, land surface heterogeneity is typically represented, in the context of Monin-Obukhov similarity theory, as changes in aerodynamic roughness length and surface heat and moisture fluxes. However, many real landscapes are more complex, often leading to massive boundary layer separation and wake turbulence, for which standard models fail. Trees, building clusters, and steep topography produce extensive wake regions currently not accounted for in models of the ABL. Wind turbines and wind farms also generate wakes that combine in complex ways to modify the ABL. Wind farms are covering an increasingly significant area of the globe and the effects of large wind farms must be included in regional and global scale models. Research presented in this thesis demonstrates that wakes caused by landscape heterogeneity must be included in flux parameterizations for momentum, heat, and mass (water vapor and trace gases, e.g. CO2 and CH4) in ABL simulation and prediction models in order to accurately represent land-atmosphere interactions. Accurate representation of these processes is crucial for the predictions of weather, air quality, lake processes, and ecosystems response to climate change. Objectives of the research reported in this thesis are: 1) to investigate turbulent boundary layer adjustment, turbulent transport and scalar flux in wind farms of varying configurations and develop an improved modeling framework for wind farm - atmosphere interaction, 2) to determine how heterogeneous patches of forest affect the structure of the ABL and its interactions with clearings and water bodies, 3) to investigate how landscape heterogeneity, including wakes, may be parameterized in regional-scale weather and climate models to improve the representation of surface fluxes, e.g. from lakes/wetlands and forest clearings. To achieve these objectives, this research employs an interdisciplinary strategy, utilizing concepts and methods from fluid mechanics, micrometeorology, ecosystem ecology and environmental sciences, and combines laboratory and field experiments. In particular, a) wind tunnel experiments of flow through and over model wind farms and model forest canopies were used to improve our fundamental understanding of how wakes affect land-atmosphere coupling, including surface fluxes, after wind farm installation and for heterogeneous landscapes of canopies and clearings or lakes, and b) extensive field studies over lakes and wetlands were undertaken to study the effects of wakes downwind of forest canopies and the effect of wind sheltering on lake stratification dynamics and gas fluxes. These experiments were also used to improve and validate numerical simulation techniques for the atmospheric boundary layer, specifically the large eddy simulation technique, which is used to simulate flow in wind farms and flow over heterogeneous terrain.

Effect of sensor systems for cow management on milk production, somatic cell count, and reproduction.

PubMed

Steeneveld, W; Vernooij, J C M; Hogeveen, H

2015-06-01

To improve management on dairy herds, sensor systems have been developed that can measure physiological, behavioral, and production indicators on individual cows. It is not known whether using sensor systems also improves measures of health and production in dairy herds. The objective of this study was to investigate the effect of using sensor systems on measures of health and production in dairy herds. Data of 414 Dutch dairy farms with (n=152) and without (n=262) sensor systems were available. For these herds, information on milk production per cow, days to first service, first calving age, and somatic cell count (SCC) was provided for the years 2003 to 2013. Moreover, year of investment in sensor systems was available. For every farm year, we determined whether that year was before or after the year of investment in sensor systems on farms with an automatic milking system (AMS) or a conventional milking system (CMS), or whether it was a year on a farm that never invested in sensor systems. Separate statistical analyses were performed to determine the effect of sensor systems for mastitis detection (color, SCC, electrical conductivity, and lactate dehydrogenase sensors), estrus detection for dairy cows, estrus detection for young stock, and other sensor systems (weighing platform, rumination time sensor, fat and protein sensor, temperature sensor, milk temperature sensor, urea sensor, β-hydroxybutyrate sensor, and other sensor systems). The AMS farms had a higher average SCC (by 12,000 cells/mL) after sensor investment, and CMS farms with a mastitis detection system had a lower average SCC (by 10,000 cells/mL) in the years after sensor investment. Having sensor systems was associated with a higher average production per cow on AMS farms, and with a lower average production per cow on CMS farms in the years after investment. The most likely reason for this lower milk production after investment was that on 96% of CMS farms, the sensor system investment occurred together with another major change at the farm, such as a new barn or a new milking system. Most likely, these other changes had led to a decrease in milk production that could not be compensated for by the use of sensor systems. Having estrus detection sensor systems did not improve reproduction performance. Labor reduction was an important reason for investing in sensor systems. Therefore, economic benefits from investments in sensor systems can be expected more from the reduction in labor costs than from improvements in measures of health and production in dairy herds. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

uFarm: a smart farm management system based on RFID

NASA Astrophysics Data System (ADS)

Kim, Hyoungsuk; Lee, Moonsup; Jung, Jonghyuk; Lee, Hyunwook; Kim, Taehyoun

2007-12-01

Recently, the livestock industry in Korea has been threatened by many challenges such as low productivity due to labor intensiveness, global competition compelled by the Free Trade Agreement (FTA), and emerging animal disease issues such as BSE or foot-and-mouth. In this paper, we propose a smart farm management system, called uFarm, which would come up with such challenges by automating farm management. First, we automate labor-intensive jobs using equipments based on sensors and actuators. The automation subsystem can be controlled by remote user through wireless network. Second, we provide real-time traceability of information on farm animals using the radio-frequency identification (RFID) method and embedded data server with network connectivity.

Prevalence and potential risk factors for the occurrence of cefotaxime resistant Escherichia coli in German fattening pig farms--a cross-sectional study.

PubMed

Hering, Johanna; Hille, Katja; Frömke, Cornelia; von Münchhausen, Christiane; Hartmann, Maria; Schneider, Bettina; Friese, Anika; Roesler, Uwe; Merle, Roswitha; Kreienbrock, Lothar

2014-09-01

A cross-sectional study concerning farm prevalence and risk factors for the count of cefotaxime resistant Escherichia coli (E. coli) (CREC) positive samples per sampling group on German fattening pig farms was performed in 2011 and 2012. Altogether 48 farms in four agricultural regions in the whole of Germany were investigated. Faecal samples, boot swabs and dust samples from two sampling groups per farm were taken and supplemental data were collected using a questionnaire. On 85% of the farms, at least one sample contained cefotaxime resistant E. coli colonies. Positive samples were more frequent in faeces (61%) and boot swabs (54%) than in dust samples (11%). Relevant variables from the questionnaire were analysed in a univariable mixed effect Poisson regression model. Variables that were related to the number (risk) of positive samples per sampling group with a p-value <0.2 were entered in a multivariable model. This model was reduced to statistically significant variables via backward selection. Factors that increased the risk for positive samples involved farm management and hygienic aspects. Farms that had a separate pen for diseased pigs had a 2.8 higher mean count of positive samples (95%-CI [1.71; 4.58], p=0.001) than farms without an extra pen. The mean count was increased on farms with under-floor exhaust ventilation compared to farms with over floor ventilation (2.22 [1.43; 3.46], p=0.001) and more positive samples were observed on farms that controlled flies with toxin compared to farms that did not (1.86 [1.24; 2.78], p=0.003). It can be concluded, that CREC are wide spread on German fattening pig farms. In addition the explorative approach of the present study suggests an influence of management strategies on the occurrence of cefotaxime resistant E. coli. Copyright © 2014 Elsevier B.V. All rights reserved.

12 CFR 614.4352 - Farm Credit Banks and agricultural credit banks.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Farm Credit Banks and agricultural credit banks. 614.4352 Section 614.4352 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS Lending and Leasing Limits § 614.4352 Farm Credit Banks and agricultural credit...

12 CFR 614.4352 - Farm Credit Banks and agricultural credit banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Farm Credit Banks and agricultural credit banks. 614.4352 Section 614.4352 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LOAN POLICIES AND OPERATIONS Lending and Leasing Limits § 614.4352 Farm Credit Banks and agricultural credit...

Understanding the Strategic Decisions Women Make in Farming Families

ERIC Educational Resources Information Center

Farmar-Bowers, Quentin

2010-01-01

Decision-systems theory (DST) was developed from in-depth interviews with farming families and provides an interpretation of the processes farming families use in making strategic decisions in regard to the family members, the farm and the businesses the farming family run. Understanding the nature and justifications used for different decisions…

Antimicrobials usage assessments in commercial poultry and local birds in North-central Nigeria: Associated pathways and factors for resistance emergence and spread.

PubMed

Alhaji, N B; Haruna, A E; Muhammad, B; Lawan, M K; Isola, T O

2018-06-01

The World Health Organization's Global Action Plan on antimicrobial resistance (AMR) recommended monitoring of antimicrobial use (AMU) through surveillance and research to help mitigate AMR. This survey was aimed at assessing poultry owners' knowledge/awareness and practices regarding AMU, identified pathways for AMR emergence and spread in small-scale commercial poultry farms and free-range local bird flocks in North-central Nigeria. An interview questionnaire-based cross-sectional study was conducted on commercial poultry farmers and local bird flock keepers in 2017. Also, a Traffic Light system model was used assess risk status of AMU in farms and flocks. All the 384 recruited poultry farmers/keepers participated in the survey. Female respondents were the majority (67.2%). Low proportion of poultry farmers (46.4%, 89/192) and very low proportion of bird keepers (6.8%, 13/192) knew antimicrobials misuse to be when administered under dose. About 48% (93/192) of farmers and 93% (179/192) of keepers arbitrary determined antimicrobial dosage before administration. Respondents used antimicrobials for therapeutic, prophylactic, and growth promotion in birds. Also, participants significantly identified contaminated poultry products, infected poultry or contaminated formites, and discharged contaminated faeces into environment as pathways for transmission of antimicrobial resistant pathogens to humans. Traffic Light system model revealed 88.5% of small-scale commercial poultry farms to frequently used antimicrobials without veterinarians' consultations thereby attaining Class 1 (Red risk) status. The model showed that 92.1% of free-range local bird flocks rarely used antimicrobials thereby attaining Class 3 (Green risk) status. Improper antimicrobial dosage in poultry (OR: 7.23; 95% CI: 2.74, 19.21), non-enforcement of AMU regulating laws in poultry (OR: 4.12; 95% CI: 2.39, 7.10), weak financial status of poultry owners (OR: 3.00; 95% CI: 2.39, 7.10), and management system (OR: 8.94; 95% CI: 5.62, 14.24) were more likely to satisfactorily influenced antimicrobials misuse in poultry farms and local bird flocks. The survey revealed low knowledge level regarding AMU in the poultry. Antimicrobials were rarely used in local bird flocks, making them likely organic and safe from AMR. It is imperative to educate farmers on judicious AMU, enforce existing veterinary legislation on antimicrobials, establish antimicrobials surveillance system, and sensitize farmers on adequate biosecurity measures and routine vaccination of farms, so as to assure food safety, food security, and public health. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Exploring economically and environmentally viable northeastern US dairy farm strategies for coping with rising corn grain prices.

PubMed

Ghebremichael, L T; Veith, T L; Cerosaletti, P E; Dewing, D E; Rotz, C A

2009-08-01

In 2008, corn grain prices rose $115/t of DM above the 2005 average. Such an increase creates tight marginal profits for small (<100) and medium-sized (100 to 199) dairy farms in the northeastern United States importing corn grain as animal feed supplement. Particularly in New York State, dairy farmers are attempting to avoid or minimize profit losses by growing more corn silage and reducing corn grain purchases. This study applies the Integrated Farm Systems Model to 1 small and 1 medium-sized New York State dairy farm to predict 1) sediment and P loss impacts from expanding corn fields, 2) benefits of no-till or cover cropping on corn fields, and 3) alternatives to the economic challenge of the current farming system as the price ratio of milk to corn grain continues to decline. Based on the simulation results, expanding corn silage production by 3% of the cultivated farm area increased sediment and sediment-bound P losses by 41 and 18%, respectively. Implementing no-till controlled about 84% of the erosion and about 75% of the sediment-bound P that would have occurred from the conventionally tilled, expanded corn production scenario. Implementing a conventionally tilled cover crop with the conventionally tilled, expanded corn production scenario controlled both erosion and sediment-bound P, but to a lesser extent than no-till corn with no cover crop. However, annual farm net return using cover crops was slightly less than when using no-till. Increasing on-farm grass productivity while feeding cows a high-quality, high-forage diet and precise dietary P levels offered dual benefits: 1) improved farm profitability from reduced purchases of dietary protein and P supplements, and 2) decreased runoff P losses from reduced P-levels in applied manure. Moreover, alternatives such as growing additional small grains on marginal lands and increasing milk production levels demonstrated great potential in increasing farm profitability. Overall, it is crucial that conservation measures such as no-till and cover cropping be implemented on new or existing corn lands as these areas often pose the highest threat for P losses through runoff. Although alternatives that would likely provide the largest net profit were evaluated one at a time to better quantify their individual impacts, combinations of these strategies, such as no-till corn plus a minimum-till cover crop, are recommended whenever feasible.

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

Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

NASA Astrophysics Data System (ADS)

PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

2018-03-01

In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

Gender differences in use of hearing protection devices among farm operators.

PubMed

McCullagh, Marjorie C; Banerjee, Tanima; Yang, James J; Bernick, Janice; Duffy, Sonia; Redman, Richard

2016-01-01

Although farm operators have frequent exposure to hazardous noise and high rates of noise-induced hearing loss, they have low use of hearing protection devices (HPDs). Women represent about one-third of farm operators, and their numbers are climbing. However, among published studies examining use of HPDs in this worker group, none have examined gender-related differences. The purpose of this study was to examine gender-related differences in use of hearing protection and related predictors among farm operators. Data previously collected at farm shows and by telephone were analyzed using t-tests and generalized linear model with zero inflated negative binomial (ZINB) distribution. The difference in rate of hearing protector use between men and women farm operators was not significant. There was no difference between men and women in most hearing protector-related attitudes and beliefs. Although men and women farm operators had similar rates of use of hearing protectors when working in high-noise environments, attitudes about HPD use differed. Specifically, interpersonal role modeling was a predictor of HPD use among women, but not for men. This difference suggests that while farm operators of both genders may benefit from interventions designed to reduce barriers to HPD use (e.g., difficulty communicating with co-workers and hearing warning sounds), farm women have unique needs in relation to cognitive-perceptual factors that predict HPD use. Women farm operators may lack role models for use of HPDs (e.g., in peers and advertising), contributing to their less frequent use of protection.

12 CFR 616.6700 - Stock purchase requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Stock purchase requirements. 616.6700 Section 616.6700 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM LEASING § 616.6700 Stock purchase requirements. (a) Each System institution, except the Farm Credit Leasing Services Corporation...

12 CFR 610.101 - Authority, purpose, and scope.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 610.101 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM REGISTRATION OF MORTGAGE LOAN ORIGINATORS § 610.101 Authority, purpose, and scope. (a) Authority. This part is issued pursuant to the Secure.... This part applies to any Farm Credit System lending institution that actually originates residential...

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

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.

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

Using biological-physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland.

PubMed

Salama, N K G; Dale, A C; Ivanov, V V; Cook, P F; Pert, C C; Collins, C M; Rabe, B

2018-06-01

Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle-tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011-2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2-week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy. © 2017 John Wiley & Sons Ltd.

Vertical farming monitoring system using the internet of things (IoT)

NASA Astrophysics Data System (ADS)

Chin, Yap Shien; Audah, Lukman

2017-09-01

Vertical farming had become a hot topic among peak development countries. However, vertical farming is hard to practice because minor changes on the surrounding would leave big impact to the productivity and quality of farming activity. Thus, the aim of this project is to provide a vertical farming monitoring system to help keeping track on the physical conditions of crops. In this system, varieties of sensors will be used to detect current physical conditions, and send the data to BeagleBone Black (BBB) microcontroller either in analog or digital input. Then, the data will be processed by BBB and upload to the Thingspeak Cloud. Furthermore, the system will record the position of equipment in used, which make it easier for maintenance when there is equipment broken down. The system also provide basic remote function where users could turn on/off the watering system, and the LED light via web-based application. The web-based application will also be designed to analyze and display data gathered in the form of graphs, charts or figures, for better understanding. With the improvement implemented on the vertical farming culture, it is expected that the productivity and quality of crops would increase significantly.

Transforming Agricultural Water Management in Support of Ecosystem Restoration

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

Hanlon, Edward; Capece, John

Threats to ecosystems are not local; they have to be handled with the global view in mind. Eliminating Florida farms, in order to meet its environmental goals, would simply move the needed agricultural production overseas, where environmentally less sensitive approaches are often used, thus yielding no net ecological benefit. South Florida is uniquely positioned to lead in the creation of sustainable agricultural systems, given its population, technology, and environmental restoration imperative. Florida should therefore aggressively focus on developing sustainable systems that deliver both agricultural production and environmental services. This presentation introduces a new farming concept of dealing with Florida’s agriculturalmore » land issues. The state purchases large land areas in order to manage the land easily and with ecosystem services in mind. 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 trying 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 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. Since the proposed approach is still being developed, there exist various unknown variables and considerations. However, working towards a long-term sustainable scenario needs to be the way ahead, as the threats are global and balancing the environment and agriculture is a serious global challenge.« less

Current situation and future prospects for beef production in Europe.

PubMed

Hocquette, Jean-Francois; Ellies-Oury, Marie-Pierre; Lherm, Michel; Pineau, Christele; Deblitz, Claus; Farmer, Linda

2018-05-24

The European Union (EU) is the world's third largest producer of beef. This contributes to the economy, rural development, social life, culture and gastronomy of Europe. The diversity of breeds, animal types (cows, bulls, steers, heifers) and farming systems (intensive, extensive on permanent or temporary pastures, mixed, breeders, feeders, etc) is a strength, and a weakness as the industry is often fragmented and poorly connected. There are also societal concerns regarding animal welfare and environmental issues, despite some positive environmental impacts of farming systems. The EU is amongst the most efficient for beef production as demonstrated by a relative low production of greenhouse gases. Due to regional differences in terms of climate, pasture availability, livestock practices and farms characteristics, productivity and incomes of beef producers vary widely across regions, being among the lowest of the agricultural systems. The beef industry is facing unprecedented challenges related to animal welfare, environmental impact, origin, authenticity, nutritional benefits and eating quality of beef. These may affect the whole industry, especially its farmers. It is therefore essential to bring the beef industry together to spread best practice and better exploit research in order to maintain and develop an economically viable and sustainable beef industry. Meeting consumers' expectations may be achieved by a better prediction of beef palatability using a modelling approach, such as in Australia. There is a need for accurate information and dissemination on the benefits and issues of beef for human health and for environmental impact. A better objective description of goods and services derived from livestock farming is also required. Putting into practice "agroecology" and organic farming principles are other potential avenues for the future. Different future scenarios can be written depending on the major driving forces, notably meat consumption, climate change, environmental policies and future organization of the supply chain.

Mapping Farming Practices in Belgian Intensive Cropping Systems from Sentinel-1 SAR Time Series

NASA Astrophysics Data System (ADS)

Chome, G.; Baret, P. V.; Defourny, P.

2016-08-01

The environmental impact of the so-called conventional farming system calls for new farming practices reducing negative externalities. Emerging farming practices such as no-till and new inter-cropping management are promising tracks. The development of methods to characterize crop management across an entire region and to understand their spatial dimension offers opportunities to accompany the transition towards a more sustainable agriculture.This research takes advantage of the unmatched polarimetric and temporal resolutions of Sentinel-1 SAR C- band to develop a method to identify farming practices at the parcel level. To this end, the detection of changes in backscattering due to surface roughness modification (tillage, inter-crop cover destruction ...) is used to detect the farming management. The final results are compared to a reference dataset collected through an intensive field campaign. Finally, the performances are discussed in the perspective of practices monitoring of cropping systems through remote sensing.

Vineyard management in virtual reality: autonomous control of a transformable drone

NASA Astrophysics Data System (ADS)

Griffiths, H.; Shen, H.; Li, N.; Rojas, S.; Perkins, N.; Liu, M.

2017-05-01

Grape vines are susceptible to many diseases. Routine scouting is critically important to keep vineyards in healthy condition. Currently, scouting relies on experienced farm workers to inspect acres of land while arduously filling out reports to document crop health conditions. This process is both labor and time consuming. Using drones to assist farm workers in scouting has great potential to improve the efficiency of vineyard management. Due to the complexity in grape farm disease detection, the drones are normally used to detect suspicious areas to help farm workers to prioritize scouting activities. Operations still rely heavily on humans for further inspection to be certain about the health conditions of the vines. This paper introduces an autonomous transition flight control method for a transformable drone, which is suitable for the future virtual presence of humans in further inspecting suspicious areas. The transformable drone adopts a tilt-rotor mechanism to automatically switch between hover and horizontal flight modes, following commands from virtual reality devices held in the ground control station. The conceptual design and transformation dynamics of the drone will be first discussed, followed by a model predictive control system developed to automatically control the transition flight. Simulation is also provided to show the effectiveness of the proposed control system.

Use of Chemical Pesticides in Ethiopia: A Cross-Sectional Comparative Study on Knowledge, Attitude and Practice of Farmers and Farm Workers in Three Farming Systems.

PubMed

Negatu, Beyene; Kromhout, Hans; Mekonnen, Yalemtshay; Vermeulen, Roel

2016-06-01

Chemical pesticides, regardless of their inherent hazard, are used intensively in the fast changing agricultural sector of Ethiopia. We conducted a cross-sectional pesticide Knowledge, Attitude and Practice (KAP) survey among 601 farmers and farm workers (applicators and re-entry workers) in three farming systems [large-scale closed greenhouses (LSGH), large-scale open farms (LSOF), and small-scale irrigated farms (SSIF)]. Main observations were that 85% of workers did not attain any pesticide-related training, 81% were not aware of modern alternatives for chemical pesticides, 10% used a full set of personal protective equipment, and 62% did not usually bath or shower after work. Among applicators pesticide training attendance was highest in LSGH (35%) and was lowest in SSIF (4%). None of the female re-entry farm workers had received pesticide-related training. Personal protective equipment use was twice as high among pesticide applicators as among re-entry workers (13 versus 7%), while none of the small-scale farm workers used personal protection equipment. Stockpiling and burial of empty pesticide containers and discarding empty pesticide containers in farming fields were reported in both LSOF and by 75% of the farm workers in SSIF. Considerable increment in chemical pesticide usage intensity, illegitimate usages of DDT and Endosulfan on food crops and direct import of pesticides without the formal Ethiopian registration process were also indicated. These results point out a general lack of training and knowledge regarding the safe use of pesticides in all farming systems but especially among small-scale farmers. This in combination with the increase in chemical pesticide usage in the past decade likely results in occupational and environmental health risks. Improved KAP that account for institutional difference among various farming systems and enforcement of regulatory measures including the available occupational and environmental proclamations in Ethiopia are urgently needed. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

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

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.

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.

12 CFR Appendix A to Part 630 - Supplemental Information Disclosure Guidelines

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Supplemental Information Disclosure Guidelines A Appendix A to Part 630 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DISCLOSURE TO INVESTORS IN SYSTEMWIDE AND CONSOLIDATED BANK DEBT OBLIGATIONS OF THE FARM CREDIT SYSTEM Pt. 630...

12 CFR 615.5220 - Capitalization bylaws.

Code of Federal Regulations, 2010 CFR

2010-01-01

....5220 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM FUNDING AND FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Issuance of Equities § 615.5220 Capitalization bylaws. (a) The board of directors of each System bank and association shall, pursuant to section 4.3A of the Farm...

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.

Water temperature, body mass and fasting heat production of pacu (Piaractus mesopotamicus).

PubMed

Aguilar, Fredy A A; Cruz, Thaline M P DA; Mourão, Gerson B; Cyrino, José Eurico P

2017-01-01

Knowledge on fasting heat production (HEf) of fish is key to develop bioenergetics models thus improving feeding management of farmed species. The core of knowledge on HEf of farmed, neotropical fish is scarce. This study assessed the effect of body mass and water temperature on standard metabolism and fasting heat production of pacu, Piaractus mesopotamicus, an omnivore, Neotropical fresh water characin important for farming and fisheries industries all through South American continent. An automated, intermittent flow respirometry system was used to measure standard metabolic rate (SMR) of pacu (17 - 1,050 g) at five water temperatures: 19, 23, 26, 29 and 33 °C. Mass specific SMR increased with increasing water temperature but decreased as function of body mass. The allometric exponent for scaling HEf was 0.788, and lied in the range recorded for all studied warm-water fish. The recorded van't Hoff factor (Q10) for pacu (2.06) shows the species low response to temperature increases. The model HEf = 0.04643×W0.7882×T1.837 allows to predict HEf (kJ d-1) from body mass (W, kg) and water temperature (T, °C), and can be used in bioenergetical models for the species.

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.

Seropositivity and risk factors for Brucella in dairy cows in urban and peri-urban small-scale farming in Tajikistan.

PubMed

Lindahl, Elisabeth; Sattorov, Nosirjon; Boqvist, Sofia; Sattori, Izzatullo; Magnusson, Ulf

2014-03-01

In this cross-sectional study, we assessed and mapped the seroprevalence of brucellosis in small-scale dairy farming in an urban and peri-urban area of Tajikistan and investigated factors associated with seropositivity. As urban and peri-urban farming is both an opportunity to improve the livelihood for small-scale farmers and a potential public health hazard, studies are warranted to reveal possible peculiarities in the epidemiology of brucellosis in this type of dairy farming. In total, 904 cows of breeding age belonging to 443 herds in 32 villages were serologically tested with indirect enzyme-linked immunosorbent assay (ELISA) and positive samples confirmed with competitive ELISA. Two logistic regression models were used to investigate an association between seropositivity and risk factors at herd and individual level. The herd and individual seroprevalences were 4.1 and 2.0 %, respectively. Herds with a history of abortions were found to be associated with seropositivity [odds ratio (OR) = 5.3; 95 % confidence interval (CI), 1.3-21.3]. Large herds with more than eight cattle were more likely to be seropositive compared to smaller herds with one to two cattle (OR = 13.9; 95 % CI, 1.6-119). The number of calves produced per cow (indicating age) was found to be associated with seropositivity. Younger cows with one to two produced calves were less likely to be seropositive compared to older cows with more than six produced calves (OR = 0.24; 95 % CI, 0.06-1.0). Neither introduction of new cattle to the herd nor communal grazing was associated with seropositivity. This study shows that infection with Brucella (1) is present in small-scale urban and peri-urban dairy farming in Tajikistan and (2) has significant negative effects on reproductive performance in this farming system and (3) that some previously known risk factors for seropositivity in rural farming system were absent here.

Development of a subgrade drainage model for unpaved roads.

DOT National Transportation Integrated Search

2015-10-01

With over 68 thousand miles of gravel roads in Iowa and the importance of these roads within the farm-to-market : transportation system, proper water management becomes critical for maintaining the integrity of the roadway : materials. However, the b...

Impact of youth injuries on the uninsured farm family's economic viability.

PubMed

Zaloshnja, Eduard; Miller, Ted R

2012-01-01

The objective of this study is to estimate the impact of youth injuries on the uninsured farm family's economic viability. Using farm prototypes, we compared farm profits with costs of farm youth injuries. We built profit models for two types of farms, dairy and soybean farms. Then we estimated the cost impact of farm youth injuries of different levels of severity on a farm family with no health insurance. A severe child injury that requires at least 10 days of hospitalisation would cost almost equal to the operating profit of the average dairy farm with no health insurance and would turn the operating profit of the average soybean farm into a severe loss of $99,499. Prevention of child agricultural injuries would significantly improve the financial situation for farm families that lack health insurance.

Lessons from sea louse and salmon epidemiology.

PubMed

Groner, Maya L; Rogers, Luke A; Bateman, Andrew W; Connors, Brendan M; Frazer, L Neil; Godwin, Sean C; Krkošek, Martin; Lewis, Mark A; Peacock, Stephanie J; Rees, Erin E; Revie, Crawford W; Schlägel, Ulrike E

2016-03-05

Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host-parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources. © 2016 The Author(s).

Lessons from sea louse and salmon epidemiology

PubMed Central

Rogers, Luke A.; Bateman, Andrew W.; Connors, Brendan M.; Frazer, L. Neil; Godwin, Sean C.; Krkošek, Martin; Lewis, Mark A.; Peacock, Stephanie J.; Rees, Erin E.; Revie, Crawford W.; Schlägel, Ulrike E.

2016-01-01

Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host–parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources. PMID:26880836

Security, protection, and control of power systems with large-scale wind power penetration

NASA Astrophysics Data System (ADS)

Acharya, Naresh

As the number of wind generation facilities in the utility system is fast increasing, many issues associated with their integration into the power system are beginning to emerge. Of the various issues, this dissertation deals with the development of new concepts and computational methods to handle the transmission issues and voltage issues caused by large-scale integration of wind turbines. This dissertation also formulates a probabilistic framework for the steady-state security assessment of wind power incorporating the forecast uncertainty and correlation. Transmission issues are mainly related to the overloading of transmission lines, when all the wind power generated cannot be delivered in full due to prior outage conditions. To deal with this problem, a method to curtail the wind turbine outputs through Energy Management System facilities in the on-line operational environment is proposed. The proposed method, which is based on linear optimization, sends the calculated control signals via the Supervisory Control and Data Acquisition system to wind farm controllers. The necessary ramping of the wind farm outputs is implemented either by the appropriate blade pitch angle control at the turbine level or by switching a certain number of turbines. The curtailment strategy is tested with an equivalent system model of MidAmerican Energy Company. The results show that the line overload in high wind areas can be alleviated by controlling the outputs of the wind farms step-by-step over an allowable period of time. A low voltage event during a system fault can cause a large number of wind turbines to trip, depending on voltages at the wind turbine terminals during the fault and the under-voltage protection setting of wind turbines. As a result, an N-1 contingency may evolve into an N-(K+1) contingency, where K is the number of wind farms tripped due to low voltage conditions. Losing a large amount of wind power following a line contingency might lead to system instabilities. It is important for the system operator to be aware of such limiting events during system operation and be prepared to take proper control actions. This can be achieved by incorporating the wind farm tripping status for each contingency as part of the static security assessment. A methodology to calculate voltages at the wind farm buses during a worst case line fault is proposed, which, along with the protection settings of wind turbines, can be used to determine the tripping of wind farms. The proposed algorithm is implemented in MATLAB and tested with MidAmerican Energy reduced network. The result shows that a large amount of wind capacity can be tripped due to a fault in the lines. Therefore, the technique will find its application in the static security assessment where each line fault can be associated with the tripping of wind farms as determined from the proposed method. A probabilistic framework to handle the uncertainty in day-ahead forecast error in order to correctly assess the steady-state security of the power system is presented. Stochastic simulations are conducted by means of Latin hypercube sampling along with the consideration of correlations. The correlation is calculated from the historical distribution of wind power forecast errors. The results from the deterministic simulation based on point forecast and the stochastic simulation show that security assessment based solely on deterministic simulations can lead to incorrect assessment of system security. With stochastic simulations, each outcome can be assigned a probability and the decision regarding control actions can be made based on the associated probability.

12 CFR 615.5450 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM FUNDING AND FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Book-Entry Procedures for Farm Credit Securities § 615.5450... as agent for the Farm Credit banks and the Funding Corporation. (j) Federal Reserve Bank Operating...

"Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidrectional Ammonia Flux in CMAQ"

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidirectional Ammonia Flux in CMAQ

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

Transforming Farm Health and Safety: The Case for Business Coaching.

PubMed

Blackman, Anna; Franklin, Richard C; Rossetto, Allison; Gray, David E

2015-01-01

In the U.S. and Australia, agriculture is consistently ranked as one of the most hazardous industries. The cost of injuries and deaths on Australian farms is significant, estimated to be between AU$0.5 billion and AU$1.2 billion per year. Death and injury in agriculture also place a significant financial and social burden on the family and friends of the injured, the community, and the health system. This article proposes that if farmers were to employ coaching in their businesses, they would benefit from advances in safety practices, resulting in associated improvements in overall farm productivity and a reduction in injury costs to the wider community. A coaching model is presented to demonstrate what an effective coaching process would need to include. An agenda for future research areas is also provided.

The effect of organic farming systems on species diversity

NASA Astrophysics Data System (ADS)

Leksono, Amin Setyo

2017-11-01

Organic farming systems have been well known to support the diversity of a wide range of taxa, including microorganisms, arable flora, invertebrates, birds, and mammals, which benefit from organic management leading to increases in abundance and/or species richness. The objective of this paper is to review the effect of organic farming on species diversity reported in several articles and compare this with the current study in Gondanglegi, Malang. A review of several studies showed that organic farming systems have been reported to increase species diversity, including that of mammals, birds, arthropods, vascular plants and arbuscular mycorrhizal fungi. The researchers about arthropod groups consisted of carabid beetles, butterflies, wasps, predators, and bees. Agricultural landscape, habitat type, farming system, landscape composition and connectivity all contribute to explaining species biodiversity and richness. Moreover, based on current and relevant studies, the results showed that the application of refugia blocks has increased arthropod diversity and composition.

The Risk-Informed Materials Management (RIMM) Tool System for Determining Safe-Levels of Contaminated Materials Managed on the Land

EPA Science Inventory

EPA’s Risk-Informed Materials Management (RIMM) tool system is a modeling approach that helps risk assessors evaluate the safety of managing raw, reused, or waste material streams via a variety of common scenarios (e.g., application to farms, use as a component in road cons...

Farm Management in Organic and Conventional Dairy Production Systems Based on Pasture in Southern Brazil and Its Consequences on Production and Milk Quality

PubMed Central

Kuhnen, Shirley; Stibuski, Rudinei Butka; Honorato, Luciana Aparecida; Pinheiro Machado Filho, Luiz Carlos

2015-01-01

Simple Summary This study provides the characteristics of the conventional high input (C-HI), conventional low input (C-LI), and organic low input (O-LI) pasture-based production systems used in Southern Brazil, and its consequences on production and milk quality. C-HI farms had larger farms and herds, annual pasture with higher inputs and milk yield, whereas O-LI had smaller farms and herds, perennial pastures with lowest input and milk yields; C-LI was in between. O-LI farms may contribute to eco-system services, but low milk yield is a major concern. Hygienic and microbiological milk quality was poor for all farms and needs to be improved. Abstract Pasture-based dairy production is used widely on family dairy farms in Southern Brazil. This study investigates conventional high input (C-HI), conventional low input (C-LI), and organic low input (O-LI) pasture-based systems and their effects on quantity and quality of the milk produced. We conducted technical site visits and interviews monthly over one year on 24 family farms (n = 8 per type). C-HI farms had the greatest total area (28.9 ha), greatest percentage of area with annual pasture (38.7%), largest number of lactating animals (26.2) and greatest milk yield per cow (22.8 kg·day−1). O-LI farms had the largest perennial pasture area (52.3%), with the greatest botanical richness during all seasons. Area of perennial pasture was positively correlated with number of species consumed by the animals (R2 = 0.74). Milk from O-LI farms had higher levels of fat and total solids only during the winter. Hygienic and microbiological quality of the milk was poor for all farms and need to be improved. C-HI farms had high milk yield related to high input, C-LI had intermediate characteristics and O-LI utilized a year round perennial pasture as a strategy to diminish the use of supplements in animal diets, which is an important aspect in ensuring production sustainability. PMID:26479369

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.

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.

12 CFR 621.3 - Application of generally accepted accounting principles.

Code of Federal Regulations, 2010 CFR

2010-01-01

... principles. 621.3 Section 621.3 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM ACCOUNTING... reports to the Farm Credit Administration, in accordance with generally accepted accounting principles... management and the Farm Credit Administration, in accordance with generally accepted accounting principles...

Cost of post-weaning multi-systemic wasting syndrome and porcine circovirus type-2 subclinical infection in England - an economic disease model.

PubMed

Alarcon, Pablo; Rushton, Jonathan; Wieland, Barbara

2013-06-01

Post-weaning multi-systemic wasting syndrome (PMWS) is a multi-factorial disease with major economic implications for the pig industry worldwide. The present study aimed to assess the economic impact of PMWS and porcine circovirus type 2 (PCV2) subclinical infections (PCV2SI) for farrow-to-finish farms and to estimate the resulting cost to the English pig industry. A disease model was built to simulate the varying proportions of pigs in a batch that get infected with PCV2 and develop either PMWS, subclinical disease (reduce growth without evident clinical signs) or remain healthy (normal growth and no clinical signs), depending on the farm level PMWS severity. This PMWS severity measure accounted for the level of post-weaning mortality, PMWS morbidity and proportion of PCV2 infected pigs observed on farms. The model generated six outcomes: infected pigs with PMWS that die (PMWS-D); infected pigs with PMWS that recover (PMWS-R); subclinical pigs that die (Sub-D); subclinical pigs that reach slaughter age (Sub-S); healthy pigs sold (H-S); and pigs, infected or non-infected by PCV2, that die due to non-PCV2 related causes (nonPCV2-D). Enterprise and partial budget analyses were used to assess the deficit/profits and the extra costs/extra benefits of a change in disease status, respectively. Results from the economic analysis at pig level were combined with the disease model's estimates of the proportion of different pigs produced at different severity scores to assess the cost of PMWS and subclinical disease at farm level, and these were then extrapolated to estimate costs at national level. The net profit for a H-S pig was £19.2. The mean loss for a PMWS-D pig was £84.1 (90% CI: 79.6-89.1), £24.5 (90% CI: 15.1-35.4) for a PMWS-R pig, £82.3 (90% CI: 78.1-87.5) for a Sub-D pig, and £8.1 (90% CI: 2.18-15.1) for a Sub-S pig. At farm level, the greatest proportion of negative economic impact was attributed to PCV2 subclinical pigs. The economic impact for the English pig industry for the year 2008, prior to the introduction of PCV2 vaccines, was estimated at £52.6 million per year (90% CI: 34.7-72.0), and approximately £88 million per year during the epidemic period. This was the first study to use empirical data to model the cost of PMWS/PCV2SI at different farm severity levels. Results from this model will be used to assess the efficiency of different control measures and to provide a decision support tool to farmers and policy makers. Copyright © 2013 Elsevier B.V. All rights reserved.

Soil Microbiome Is More Heterogeneous in Organic Than in Conventional Farming System

PubMed Central

Lupatini, Manoeli; Korthals, Gerard W.; de Hollander, Mattias; Janssens, Thierry K. S.; Kuramae, Eiko E.

2017-01-01

Organic farming system and sustainable management of soil pathogens aim at reducing the use of agricultural chemicals in order to improve ecosystem health. Despite the essential role of microbial communities in agro-ecosystems, we still have limited understanding of the complex response of microbial diversity and composition to organic and conventional farming systems and to alternative methods for controlling plant pathogens. In this study we assessed the microbial community structure, diversity and richness using 16S rRNA gene next generation sequences and report that conventional and organic farming systems had major influence on soil microbial diversity and community composition while the effects of the soil health treatments (sustainable alternatives for chemical control) in both farming systems were of smaller magnitude. Organically managed system increased taxonomic and phylogenetic richness, diversity and heterogeneity of the soil microbiota when compared with conventional farming system. The composition of microbial communities, but not the diversity nor heterogeneity, were altered by soil health treatments. Soil health treatments exhibited an overrepresentation of specific microbial taxa which are known to be involved in soil suppressiveness to pathogens (plant-parasitic nematodes and soil-borne fungi). Our results provide a comprehensive survey on the response of microbial communities to different agricultural systems and to soil treatments for controlling plant pathogens and give novel insights to improve the sustainability of agro-ecosystems by means of beneficial microorganisms. PMID:28101080

Neither "Family" nor "Corporate" Farming: Australian Tomato Growers as Farm Family Entrepreneurs

ERIC Educational Resources Information Center

Pritchard, Bill; Burch, David; Lawrence, Geoffrey

2007-01-01

For the past two decades there has been much debate about the future of family farming. The basic question on which this debate has turned is whether current pressures on family farm systems should be understood as symptomatic of a terminal condition, in which farmers are replaced progressively by corporate ownership; or whether family farms will…

76 FR 75542 - Rail Splitter Wind Farm, LLC v. Ameren Services Company Midwest Independent Transmission, System...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-02

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL12-11-000] Rail Splitter Wind Farm, LLC v. Ameren Services Company Midwest Independent Transmission, System Operator, Inc...) Rules of Practice and Procedures, 18 CFR 385.206, Rail Splitter Wind Farm, LLC (Rail Splitter or...

75 FR 68533 - Funding and Fiscal Affairs, Loan Policies and Operations, and Funding Operations; Capital...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-08

... banking regulators and with risks taken by Farm Credit System (FCS or System) institutions, taking into... FARM CREDIT ADMINISTRATION 12 CFR Part 615 RIN 3052-AC25 Funding and Fiscal Affairs, Loan Policies... Tier 2 AGENCY: Farm Credit Administration. ACTION: Advance notice of proposed rulemaking (ANPRM...

12 CFR 614.4125 - Funding and discount relationships between Farm Credit Banks or agricultural credit banks and...

Code of Federal Regulations, 2010 CFR

2010-01-01

..., Risk Management, Farm Credit System Insurance Corporation. (f) A direct lender association shall... Administration office that the Chief Examiner designates, and the Director, Risk Management, Farm Credit System... Credit Banks or agricultural credit banks and direct lender associations. 614.4125 Section 614.4125 Banks...

Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs

PubMed Central

Gilbert, Marius; Conchedda, Giulia; Van Boeckel, Thomas P.; Cinardi, Giuseppina; Linard, Catherine; Nicolas, Gaëlle; Thanapongtharm, Weerapong; D'Aietti, Laura; Wint, William; Newman, Scott H.; Robinson, Timothy P.

2015-01-01

The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification. PMID:26230336

Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs.

PubMed

Gilbert, Marius; Conchedda, Giulia; Van Boeckel, Thomas P; Cinardi, Giuseppina; Linard, Catherine; Nicolas, Gaëlle; Thanapongtharm, Weerapong; D'Aietti, Laura; Wint, William; Newman, Scott H; Robinson, Timothy P

2015-01-01

The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification.

Quantifying Human Appropriated Net Primary Productivity (HANPP) in a Ghanaian Cocoa System

NASA Astrophysics Data System (ADS)

Morel, A.; Adu-Bredu, S.; Adu Sasu, M.; Ashley Asare, R.; Boyd, E.; Hirons, M. A.; Malhi, Y.; Mason, J.; Norris, K.; Robinson, E. J. Z.; McDermott, C. L.

2015-12-01

Ghana is the second largest producer of cocoa (Theobroma cacoa), exporting approximately 18 percent of global volumes. These cocoa farms are predominantly small-scale, ranging in size from 2-4 hectares (ha). Traditionally, the model of cocoa expansion in Ghana relied on clearing new areas of forest and establishing a farm under remnant forest trees. This is increasingly less practical due to few unprotected forest areas remaining and management practices favoring close to full sun cocoa to maximize short-term yields. This study is part of a larger project, ECOLMITS, which is an interdisciplinary, ESPA-funded[1] initiative exploring the ecological limits of ecosystem system services (ESS) for alleviating poverty in small-scale agroforestry systems. The ecological study plots are situated within and around the Kakum National Forest, a well-protected, moist-evergreen forest of the Lower Guinea Forest region. Net primary productivity (NPP) is a measure of the rate at which carbon dioxide (CO2) is incorporated into plant tissues (e.g. canopy, stem and root). For this study, NPP was monitored in situ using methods developed by the Global Environmental Monitoring Network (GEM, http://gem.tropicalforests.ox.ac.uk/). By comparing NPP measured in intact forest and farms, the human appropriated NPP (HANPP) of this system can be estimated. The forest measures provide the "potential" NPP of the region, and then the reduction in NPP for farm plots is calculated for both land-cover change (HANPPLUC) and cocoa harvesting (HANPPHARV). The results presented are of the first year of NPP measurements across the cocoa landscape, including measurements from intact forest, logged forest and cocoa farms across a shade gradient and located at varying distances from the forest edge (e.g. 100 m, 500 m, 1 km and 5 km). These measures will have implications for carbon sequestration potential over the region and long-term sustainability of the Ghanaian cocoa sector. [1] Ecosystem Services for Poverty Alleviation grant program, http://www.espa.ac.uk/

Sea louse infection of juvenile sockeye salmon in relation to marine salmon farms on Canada's west coast.

PubMed

Price, Michael H H; Proboszcz, Stan L; Routledge, Rick D; Gottesfeld, Allen S; Orr, Craig; Reynolds, John D

2011-02-09

Pathogens are growing threats to wildlife. The rapid growth of marine salmon farms over the past two decades has increased host abundance for pathogenic sea lice in coastal waters, and wild juvenile salmon swimming past farms are frequently infected with lice. Here we report the first investigation of the potential role of salmon farms in transmitting sea lice to juvenile sockeye salmon (Oncorhynchus nerka). We used genetic analyses to determine the origin of sockeye from Canada's two most important salmon rivers, the Fraser and Skeena; Fraser sockeye migrate through a region with salmon farms, and Skeena sockeye do not. We compared lice levels between Fraser and Skeena juvenile sockeye, and within the salmon farm region we compared lice levels on wild fish either before or after migration past farms. We matched the latter data on wild juveniles with sea lice data concurrently gathered on farms. Fraser River sockeye migrating through a region with salmon farms hosted an order of magnitude more sea lice than Skeena River populations, where there are no farms. Lice abundances on juvenile sockeye in the salmon farm region were substantially higher downstream of farms than upstream of farms for the two common species of lice: Caligus clemensi and Lepeophtheirus salmonis, and changes in their proportions between two years matched changes on the fish farms. Mixed-effects models show that position relative to salmon farms best explained C. clemensi abundance on sockeye, while migration year combined with position relative to salmon farms and temperature was one of two top models to explain L. salmonis abundance. This is the first study to demonstrate a potential role of salmon farms in sea lice transmission to juvenile sockeye salmon during their critical early marine migration. Moreover, it demonstrates a major migration corridor past farms for sockeye that originated in the Fraser River, a complex of populations that are the subject of conservation concern.

Sea Louse Infection of Juvenile Sockeye Salmon in Relation to Marine Salmon Farms on Canada's West Coast

PubMed Central

Price, Michael H. H.; Proboszcz, Stan L.; Routledge, Rick D.; Gottesfeld, Allen S.; Orr, Craig; Reynolds, John D.

2011-01-01

Background Pathogens are growing threats to wildlife. The rapid growth of marine salmon farms over the past two decades has increased host abundance for pathogenic sea lice in coastal waters, and wild juvenile salmon swimming past farms are frequently infected with lice. Here we report the first investigation of the potential role of salmon farms in transmitting sea lice to juvenile sockeye salmon (Oncorhynchus nerka). Methodology/Principal Findings We used genetic analyses to determine the origin of sockeye from Canada's two most important salmon rivers, the Fraser and Skeena; Fraser sockeye migrate through a region with salmon farms, and Skeena sockeye do not. We compared lice levels between Fraser and Skeena juvenile sockeye, and within the salmon farm region we compared lice levels on wild fish either before or after migration past farms. We matched the latter data on wild juveniles with sea lice data concurrently gathered on farms. Fraser River sockeye migrating through a region with salmon farms hosted an order of magnitude more sea lice than Skeena River populations, where there are no farms. Lice abundances on juvenile sockeye in the salmon farm region were substantially higher downstream of farms than upstream of farms for the two common species of lice: Caligus clemensi and Lepeophtheirus salmonis, and changes in their proportions between two years matched changes on the fish farms. Mixed-effects models show that position relative to salmon farms best explained C. clemensi abundance on sockeye, while migration year combined with position relative to salmon farms and temperature was one of two top models to explain L. salmonis abundance. Conclusions/Significance This is the first study to demonstrate a potential role of salmon farms in sea lice transmission to juvenile sockeye salmon during their critical early marine migration. Moreover, it demonstrates a major migration corridor past farms for sockeye that originated in the Fraser River, a complex of populations that are the subject of conservation concern. PMID:21347456

Stackelberg Game Model of Wind Farm and Electric Vehicle Battery Switch Station

NASA Astrophysics Data System (ADS)

Jiang, Zhe; Li, Zhimin; Li, Wenbo; Wang, Mingqiang; Wang, Mengxia

2017-05-01

In this paper, a cooperation method between wind farm and Electric vehicle battery switch station (EVBSS) was proposed. In the pursuit of maximizing their own benefits, the cooperation between wind farm and EVBSS was formulated as a Stackelberg game model by treating them as decision makers in different status. As the leader, wind farm will determine the charging/discharging price to induce the charging and discharging behavior of EVBSS reasonably. Through peak load shifting, wind farm could increase its profits by selling more wind power to the power grid during time interval with a higher purchase price. As the follower, EVBSS will charge or discharge according to the price determined by wind farm. Through optimizing the charging /discharging strategy, EVBSS will try to charge with a lower price and discharge with a higher price in order to increase its profits. Since the possible charging /discharging strategy of EVBSS is known, the wind farm will take the strategy into consideration while deciding the charging /discharging price, and will adjust the price accordingly to increase its profits. The case study proved that the proposed cooperation method and model were feasible and effective.

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.

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.

Farm Management, Environment, and Weather Factors Jointly Affect the Probability of Spinach Contamination by Generic Escherichia coli at the Preharvest Stage

PubMed Central

Navratil, Sarah; Gregory, Ashley; Bauer, Arin; Srinath, Indumathi; Szonyi, Barbara; Nightingale, Kendra; Anciso, Juan; Jun, Mikyoung; Han, Daikwon; Lawhon, Sara; Ivanek, Renata

2014-01-01

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination. PMID:24509926

Fungal Diversity in Tomato Rhizosphere Soil under Conventional and Desert Farming Systems

PubMed Central

Kazerooni, Elham A.; Maharachchikumbura, Sajeewa S. N.; Rethinasamy, Velazhahan; Al-Mahrouqi, Hamed; Al-Sadi, Abdullah M.

2017-01-01

This study examined fungal diversity and composition in conventional (CM) and desert farming (DE) systems in Oman. Fungal diversity in the rhizosphere of tomato was assessed using 454-pyrosequencing and culture-based techniques. Both techniques produced variable results in terms of fungal diversity, with 25% of the fungal classes shared between the two techniques. In addition, pyrosequencing recovered more taxa compared to direct plating. These findings could be attributed to the ability of pyrosequencing to recover taxa that cannot grow or are slow growing on culture media. Both techniques showed that fungal diversity in the conventional farm was comparable to that in the desert farm. However, the composition of fungal classes and taxa in the two farming systems were different. Pyrosequencing revealed that Microsporidetes and Dothideomycetes are the two most common fungal classes in CM and DE, respectively. However, the culture-based technique revealed that Eurotiomycetes was the most abundant class in both farming systems and some classes, such as Microsporidetes, were not detected by the culture-based technique. Although some plant pathogens (e.g., Pythium or Fusarium) were detected in the rhizosphere of tomato, the majority of fungal species in the rhizosphere of tomato were saprophytes. Our study shows that the cultivation system may have an impact on fungal diversity. The factors which affected fungal diversity in both farms are discussed. PMID:28824590

A Dynamic Spatio-Temporal Model to Investigate the Effect of Cattle Movements on the Spread of Bluetongue BTV-8 in Belgium

PubMed Central

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases. PMID:24244324

A dynamic spatio-temporal model to investigate the effect of cattle movements on the spread of bluetongue BTV-8 in Belgium.

PubMed

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases.

The New BaBar Data Reconstruction Control System

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

Ceseracciu, Antonio

2003-06-02

The BaBar experiment is characterized by extremely high luminosity, a complex detector, and a huge data volume, with increasing requirements each year. To fulfill these requirements a new control system has been designed and developed for the offline data reconstruction system. The new control system described in this paper provides the performance and flexibility needed to manage a large number of small computing farms, and takes full benefit of OO design. The infrastructure is well isolated from the processing layer, it is generic and flexible, based on a light framework providing message passing and cooperative multitasking. The system is activelymore » distributed, enforces the separation between different processing tiers by using different naming domains, and glues them together by dedicated brokers. It provides a powerful Finite State Machine framework to describe custom processing models in a simple regular language. This paper describes this new control system, currently in use at SLAC and Padova on {approx}450 CPUs organized in 12 farms.« less

Simulated environmental transport distances of Lepeophtheirus salmonis in Loch Linnhe, Scotland, for informing aquaculture area management structures.

PubMed

Salama, N K G; Murray, A G; Rabe, B

2016-04-01

In the majority of salmon farming countries, production occurs in zones where practices are coordinated to manage disease agents such as Lepeophtheirus salmonis. To inform the structure of zones in specific systems, models have been developed accounting for parasite biology and system hydrodynamics. These models provide individual system farm relationships, and as such, it may be beneficial to produce more generalized principles for informing structures. Here, we use six different forcing scenarios to provide simulations from a previously described model of the Loch Linnhe system, Scotland, to assess the maximum dispersal distance of lice particles released from 12 sites transported over 19 day. Results indicate that the median distance travelled is 6.1 km from release site with <2.5% transported beyond 15 km, which occurs from particles originating from half of the release sites, with an absolute simulated distance of 36 km observed. This provides information suggesting that the disease management areas developed for infectious salmon anaemia control may also have properties appropriate for salmon lice management in Scottish coastal waters. Additionally, general numerical descriptors of the simulated relative lice abundance reduction with increased distance from release location are proposed. © 2015 Crown copyright. © 2015 John Wiley & Sons Ltd.

Implementation of Wireless Sensor Networks Based Pig Farm Integrated Management System in Ubiquitous Agricultural Environments

NASA Astrophysics Data System (ADS)

Hwang, Jeonghwan; Lee, Jiwoong; Lee, Hochul; Yoe, Hyun

The wireless sensor networks (WSN) technology based on low power consumption is one of the important technologies in the realization of ubiquitous society. When the technology would be applied to the agricultural field, it can give big change in the existing agricultural environment such as livestock growth environment, cultivation and harvest of agricultural crops. This research paper proposes the 'Pig Farm Integrated Management System' based on WSN technology, which will establish the ubiquitous agricultural environment and improve the productivity of pig-raising farmers. The proposed system has WSN environmental sensors and CCTV at inside/outside of pig farm. These devices collect the growth-environment related information of pigs, such as luminosity, temperature, humidity and CO2 status. The system collects and monitors the environmental information and video information of pig farm. In addition to the remote-control and monitoring of the pig farm facilities, this system realizes the most optimum pig-raising environment based on the growth environmental data accumulated for a long time.

Organic agriculture in the twenty-first century.

PubMed

Reganold, John P; Wachter, Jonathan M

2016-02-03

Organic agriculture has a history of being contentious and is considered by some as an inefficient approach to food production. Yet organic foods and beverages are a rapidly growing market segment in the global food industry. Here, we examine the performance of organic farming in light of four key sustainability metrics: productivity, environmental impact, economic viability and social wellbeing. Organic farming systems produce lower yields compared with conventional agriculture. However, they are more profitable and environmentally friendly, and deliver equally or more nutritious foods that contain less (or no) pesticide residues, compared with conventional farming. Moreover, initial evidence indicates that organic agricultural systems deliver greater ecosystem services and social benefits. Although organic agriculture has an untapped role to play when it comes to the establishment of sustainable farming systems, no single approach will safely feed the planet. Rather, a blend of organic and other innovative farming systems is needed. Significant barriers exist to adopting these systems, however, and a diversity of policy instruments will be required to facilitate their development and implementation.

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.

High Bee and Wasp Diversity in a Heterogeneous Tropical Farming System Compared to Protected Forest

PubMed Central

Schüepp, Christof; Rittiner, Sarah; Entling, Martin H.

2012-01-01

It is a globally important challenge to meet increasing demands for resources and, at the same time, protect biodiversity and ecosystem services. Farming is usually regarded as a major threat to biodiversity due to its expansion into natural areas. We compared biodiversity of bees and wasps between heterogeneous small-scale farming areas and protected forest in northern coastal Belize, Central America. Malaise traps operated for three months during the transition from wet to dry season. Farming areas consisted of a mosaic of mixed crop types, open habitat, secondary forest, and agroforestry. Mean species richness per site (alpha diversity), as well as spatial and temporal community variation (beta diversity) of bees and wasps were equal or higher in farming areas compared to protected forest. The higher species richness and community variation in farmland was due to additional species that did not occur in the forest, whereas most species trapped in forest were also found in farming areas. The overall regional species richness (gamma diversity) increased by 70% with the inclusion of farming areas. Our results suggest that small-scale farming systems adjacent to protected forest may not only conserve, but even favour, biodiversity of some taxonomic groups. We can, however, not exclude possible declines of bee and wasp diversity in more intensified farmland or in landscapes completely covered by heterogeneous farming systems. PMID:23300598

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

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).

78 FR 37101 - Funding and Fiscal Affairs, Loan Policies and Operations, and Funding Operations; Liquidity and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-20

... amends its liquidity regulation to strengthen liquidity risk management at Farm Credit System (System... regulation to strengthen liquidity risk management at Farm Credit System (System) banks, improve the quality...

Energy balance in olive oil farms: comparison of organic and conventional farming systems.

NASA Astrophysics Data System (ADS)

Moreno, Marta M.; Meco, Ramón; Moreno, Carmen

2013-04-01

The viability of an agricultural production system not only depends on the crop yields, but especially on the efficient use of available resources. However, the current agricultural systems depend heavily on non-renewable energy consumption in the form of fertilizers, fossil fuels, pesticides and machinery. In developed countries, the economic profitability of different productive systems is dependent on the granting of subsidies of diverse origin that affect both production factors (or inputs) and the final product (or output). Leaving such external aids, energy balance analysis reveals the real and most efficient form of management for each agroclimatic region, and is also directly related to the economic activity and the environmental state. In this work we compare the energy balance resulting from organic and conventional olive oil farms under the semi-arid conditions of Central Spain. The results indicate that the mean energy supplied to the organic farms was sensitively lower (about 30%) in comparison with the conventional management, and these differences were more pronounced for the biggest farms (> 15 ha). Mean energy outputs were about 20% lower in the organic system, although organic small farms (< 15 ha) resulted more productive than the conventional small ones. However, these lower outputs were compensated by the major market value obtained from the organic products. Chemical fertilizers and pesticides reached about 60% of the total energy inputs in conventional farming; in the organic farms, however, this ratio scarcely reached 25%. Human labor item only represented a very small amount of the total energy input in both cases (less than 1%). As conclusions, both management systems were efficient from an energy point of view. The value of the organic production should be focused on the environmental benefits it provides, which are not usually considered in the conventional management on not valuing the damage it produces to the environment. Organic farming would improve the energy efficiency in these environmental conditions, offering a sustainable production with minimal inputs.

Multiregional input-output model for China's farm land and water use.

PubMed

Guo, Shan; Shen, Geoffrey Qiping

2015-01-06

Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.

Carbon footprint of dairy goat milk production in New Zealand.

PubMed

Robertson, Kimberly; Symes, Wymond; Garnham, Malcolm

2015-07-01

The aim of this study was to assess the cradle-to-farm gate carbon footprint of indoor and outdoor dairy goat farming systems in New Zealand, identifying hotspots and discussing variability and methodology. Our study was based on the International Organization for Standardization standards for life cycle assessment, although only results for greenhouse gas emissions are presented. Two functional units were included: tonnes of CO2-equivalents (CO2e) per hectare (ha) and kilograms of CO2e per kilogram of fat- and protein-corrected milk (FPCM). The study covered 5 farms, 2 farming systems, and 3yr. Two methods for the calculation of enteric methane emissions were assessed. The Lassey method, as used in the New Zealand greenhouse gas inventory, provided a more robust estimate of emissions from enteric fermentation and was used in the final calculations. The alternative dry matter intake method was shown to overestimate emissions due to use of anecdotal assumptions around actual consumption of feed. Economic allocation was applied to milk and co-products. Scenario analysis was performed on the allocation method, nitrogen content of manure, manure management, and supplementary feed choice. The average carbon footprint for the indoor farms (n=3) was 11.05 t of CO2e/ha and 0.81kg of CO2e/kg of FPCM. For the outdoor farms (n=2), the average was 5.38 t of CO2e/ha and 1.03kg of CO2e/kg of FPCM. The average for all 5 farms was 8.78 t of CO2e/ha and 0.90kg of CO2e/kg of FPCM. The results showed relatively high variability due to differences in management practices between farms. The 5 farms covered 10% of the total dairy goat farms but may not be representative of an average farm. Methane from enteric fermentation was a major emission source. The use of supplementary feed was highly variable but an important contributor to the carbon footprint. Nitrous oxide can contribute up to 18% of emissions. Indoor goat farming systems produced milk with a significantly higher carbon footprint per area of land farmed compared with outdoor farming systems, although the 2 systems were not significantly different when results were expressed per kilogram of FPCM, at 0.81kg CO2e and 1.03kg CO2e per kg of FPCM, respectively. Both systems had footprints less than other reported dairy goat carbon footprints and on par with those for New Zealand dairy cows. The methodology used to determine enteric methane is important for an accurate and meaningful assessment. The choice of manure management system and supplementary feed can substantially affect the carbon footprint. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

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.

Experimental study of the impact of large-scale wind farms on land-atmosphere exchanges

NASA Astrophysics Data System (ADS)

Zhang, wei; Markfort, Corey; Porté-Agel, Fernando

2013-04-01

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. CO2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interactions and subsequent environmental impacts are complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics and atmospheric thermal stability. In particular, surface scalar flux is influenced by wind farms and needs to be appropriately parameterized in meso-scale and/or high-resolution numerical models. Wind-tunnel experiments of model wind farms with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a neutral turbulent boundary layer with a surface heat source. Turbulent flow and fluxes over and through the wind farm were measured using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors within the quasi-developed flow regime. Although the overall surface heat flux change produced by the wind farms was found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. The difference between the minimum and maximum surface heat fluxes could be up to 12% and 7% in aligned and staggered wind farms, respectively. This finding is important for planning intensive agriculture practices and optimizing agricultural land use with regard to wind energy project development. The well-controlled wind-tunnel experiments presented here also provide a first comprehensive dataset on turbulent flow and scalar transport in wind farms, which can be further used to develop and validate new parameterizations for surface scalar fluxes in numerical models.