NASA Astrophysics Data System (ADS)
Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.
2015-12-01
The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.
USDA-ARS?s Scientific Manuscript database
Cover crops influence soil nitrogen (N) mineralization-immobilization-turnover cycles (MIT), thus influencing N availability to a subsequent crop. Dynamic simulation models of the soil/crop system, if properly calibrated and tested, can simulate carbon (C) and N dynamics of a terminated cover crop a...
Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover
NASA Astrophysics Data System (ADS)
Ochsner, T.; Venterea, R. T.
2009-12-01
Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching will also be examined.
USDA-ARS?s Scientific Manuscript database
Cropping systems over the past century have developed greater crop specialization, more effectively conserve our soil and water resources, and are more resilient. The purpose of this chapter is to discuss the evolution of cropping systems in the Northern Great Plains and provide an approach to crop...
NASA Astrophysics Data System (ADS)
Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.
2015-12-01
While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.
Effects of dynamic agricultural decision making in an ecohydrological model
NASA Astrophysics Data System (ADS)
Reichenau, T. G.; Krimly, T.; Schneider, K.
2012-04-01
Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop distribution and constant management. Results show that the influence of the modeled dynamic management adaptation on variables like transpiration, carbon uptake, or nitrate leaching from the vadose zone is stronger than the influence of a dynamic choice of crops. Climate change was found to have a stronger impact on this modeled choice of crops than the agro-political framework. These results suggest that scenario studies in areas with a large share of arable land should take into account management adaptations to changing climate.
USDA-ARS?s Scientific Manuscript database
Agricultural system models have become important tools in studying water and nitrogen (N) dynamics, as well as crop growth, under different management practices. Complexity in input parameters often leads to significant uncertainty when simulating dynamic processes such as nitrate leaching or crop y...
Dynamic optimization of CELSS crop photosynthetic rate by computer-assisted feedback control
NASA Astrophysics Data System (ADS)
Chun, C.; Mitchell, C. A.
1997-01-01
A procedure for dynamic optimization of net photosynthetic rate (Pn) for crop production in Controlled Ecological Life-Support Systems (CELSS) was developed using leaf lettuce as a model crop. Canopy Pn was measured in real time and fed back for environmental control. Setpoints of photosynthetic photon flux (PPF) and CO_2 concentration for each hour of the crop-growth cycle were decided by computer to reach a targeted Pn each day. Decision making was based on empirical mathematical models combined with rule sets developed from recent experimental data. Comparisons showed that dynamic control resulted in better yield per unit energy input to the growth system than did static control. With comparable productivity parameters and potential for significant energy savings, dynamic control strategies will contribute greatly to the sustainability of space-deployed CELSS.
NASA Technical Reports Server (NTRS)
Volk, Tyler
1987-01-01
The production of food for human life support for advanced space missions will require the management of many different crops. The research to design these food production capabilities along with the waste management to recycle human metabolic wastes and inedible plant components are parts of Controlled Ecological Life Support Systems (CELSS). Since complete operating CELSS were not yet built, a useful adjunct to the research developing the various pieces of a CELSS are system simulation models that can examine what is currently known about the possible assembly of subsystems into a full CELSS. The growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) are examined for their general similarities and differences within the context of their important effects upon the dynamics of the gases, liquids, and solids in the CELSS. Data for the four crops currently under active research in the CELSS program using high-production hydroponics are presented. Two differential equations are developed and applied to the general characteristics of each crop growth pattern. Model parameters are determined by closely approximating each crop's data.
The review of dynamic monitoring technology for crop growth
NASA Astrophysics Data System (ADS)
Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong
2010-10-01
In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.
NASA Astrophysics Data System (ADS)
Chen, C. R.; Chen, C. F.; Nguyen, S. T.
2014-12-01
The rice cropping systems in the Vietnamese Mekong Delta (VMD) has been undergoing major changes to cope with developing agro-economics, increasing population and changing climate. Information on rice cropping practices and changes in cropping systems is critical for policymakers to devise successful strategies to ensure food security and rice grain exports for the country. The primary objective of this research is to map rice cropping systems and predict future dynamics of rice cropping systems using the MODIS time-series data of 2002, 2006, and 2010. First, a phenology-based classification approach was applied for the classification and assessment of rice cropping systems in study region. Second, the Cellular Automata-Markov (CA-Markov) models was used to simulate the rice-cropping system map of VMD for 2010. The comparisons between the classification maps and the ground reference data indicated satisfactory results with overall accuracies and Kappa coefficients, respectively, of 81.4% and 0.75 for 2002, 80.6% and 0.74 for 2006 and 85.5% and 0.81 for 2010. The simulated map of rice cropping system for 2010 was extrapolated by CA-Markov model based on the trend of rice cropping systems during 2002~2006. The comparison between predicted scenario and classification map for 2010 presents a reasonably closer agreement. In conclusion, the CA-Markov model performs a powerful tool for the dynamic modeling of changes in rice cropping systems, and the results obtained demonstrate that the approach produces satisfactory results in terms of accuracy, quantitative forecast and spatial pattern changes. Meanwhile, the projections of the future changes would provide useful inputs to the agricultural policy for effective management of the rice cropping practices in VMD.
Soler, C M Tojo; Bado, V B; Traore, K; Bostick, W McNair; Jones, J W; Hoogenboom, G
2011-10-01
In recent years, simulation models have been used as a complementary tool for research and for quantifying soil carbon sequestration under widely varying conditions. This has improved the understanding and prediction of soil organic carbon (SOC) dynamics and crop yield responses to soil and climate conditions and crop management scenarios. The goal of the present study was to estimate the changes in SOC for different cropping systems in West Africa using a simulation model. A crop rotation experiment conducted in Farakô-Ba, Burkina Faso was used to evaluate the performance of the cropping system model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) for simulating yield of different crops. Eight crop rotations that included cotton, sorghum, peanut, maize and fallow, and three different management scenarios, one without N (control), one with chemical fertilizer (N) and one with manure applications, were studied. The CSM was able to simulate the yield trends of various crops, with inconsistencies for a few years. The simulated SOC increased slightly across the years for the sorghum-fallow rotation with manure application. However, SOC decreased for all other rotations except for the continuous fallow (native grassland), in which the SOC remained stable. The model simulated SOC for the continuous fallow system with a high degree of accuracy normalized root mean square error (RMSE)=0·001, while for the other crop rotations the simulated SOC values were generally within the standard deviation (s.d.) range of the observed data. The crop rotations that included a supplemental N-fertilizer or manure application showed an increase in the average simulated aboveground biomass for all crops. The incorporation of this biomass into the soil after harvest reduced the loss of SOC. In the present study, the observed SOC data were used for characterization of production systems with different SOC dynamics. Following careful evaluation of the CSM with observed soil organic matter (SOM) data similar to the study presented here, there are many opportunities for the application of the CSM for carbon sequestration and resource management in Sub-Saharan Africa.
Although earthworms are known to influence agroecosystem processes, there are relatively few long-term studies addressing population dynamics under cropping systems in which earthworm populations were intentionally altered. We assessed earthworm communities from fall 1994 to spr...
NASA Technical Reports Server (NTRS)
Volk, Tyler
1992-01-01
The goal of this research is to develop a progressive series of mathematical models for the CELSS hydroponic crops. These models will systematize the experimental findings from the crop researchers in the CELSS Program into a form useful to investigate system-level considerations, for example, dynamic studies of the CELSS Initial Reference Configurations. The crop models will organize data from different crops into a common modeling framework. This is the fifth semiannual report for this project. The following topics are discussed: (1) use of field crop models to explore phasic control of CELSS crops for optimizing yield; (2) seminar presented at Purdue CELSS NSCORT; and (3) paper submitted on analysis of bioprocessing of inedible plant materials.
Impacts of Cover Crops on Water and Nutrient Dynamics in Agroecosystems
NASA Astrophysics Data System (ADS)
Williard, K.; Swanberg, S.; Schoonover, J.
2013-05-01
Intensive cropping systems of corn (Zea Mays L.) and soybeans (Glycine max) are commonly leaky systems with respect to nitrogen (N). Reactive N outputs from agroecosystems can contribute to eutrophication and hypoxic zones in downstream water bodies and greenhouse gas (N2O) emissions. Incorporating cover crops into temperate agroecosystem rotations has been promoted as a tool to increase nitrogen use efficiency and thus limit reactive N outputs to the environment. Our objective was determine how cereal rye (Secale cereal L.) and annual ryegrass (Lolium multiflorum) cover crops impact nutrient and soil water dynamics in an intensive corn and soybean cropping rotation in central Illinois. Cover crops were planted in mid to late October and terminated in early April prior to corn or soybean planting. In the spring just prior to cover crop termination, soil moisture levels were lower in the cover crop plots compared to no cover plots. This can be a concern for the subsequent crop in relatively dry years, which the Midwestern United States experienced in 2012. No cover plots had greater nutrient leaching below the rooting zone compared to cover crop areas, as expected. The cover crops were likely scavenging nutrients during the fall and early spring and should provide nutrients to the subsequent crop via decomposition and mineralization of the cover crop residue. Over the long term, cover crop systems should produce greater inputs and cycling of carbon and N, increasing the productivity of crops due to the long-term accumulation of soil organic matter. This study demonstrates that there may be short term trade-offs in reduced soil moisture levels that should be considered alongside the long term nutrient scavenging and recycling benefits of cover crops.
Penet, Laurent; Cornet, Denis; Blazy, Jean-Marc; Alleyne, Angela; Barthe, Emilie; Bussière, François; Guyader, Sébastien; Pavis, Claudie; Pétro, Dalila
2016-01-01
Loss of varietal diversity is a worldwide challenge to crop species at risk for genetic erosion, while the loss of biological resources may hinder future breeding objectives. Loss of varieties has been mostly investigated in traditional agricultural systems where variety numbers are dramatically high, or for most economically important crop species for which comparison between pre-intensive and modern agriculture was possible. Varietal dynamics, i.e., turnover, or gains and losses of varieties by farmers, is nevertheless more rarely studied and while we currently have good estimates of genetic or varietal diversity for most crop species, we have less information as to how on farm agro-diversity changes and what cause its dynamics. We therefore investigated varietal dynamics in the agricultural yam system in the Caribbean island of Guadeloupe. We interviewed producers about varieties they cultivated in the past compared to their current varieties, in addition to characterizing yam cropping characteristics and both farm level and producers socio-economic features. We then used regression tree analyses to investigate the components of yam agro-diversity, varietal dynamics and impact of anthracnose on varieties. Our data demonstrated that no dramatic loss of varieties occurred within the last decades. Cultivation changes mostly affected widespread cultivars while frequency of uncommon varieties stayed relatively stable. Varietal dynamics nevertheless followed sub-regional patterns, and socio-economic influences such as producer age or farm crop diversity. Recurrent anthracnose epidemics since the 1970s did not alter varietal dynamics strongly, but sometimes translated into transition from Dioscorea alata to less susceptible species or into a decrease of yam cultivation. Factors affecting changes in agro-diversity were not relating to agronomy in our study, and surprisingly there were different processes delineating short term from long term varietal dynamics, independently of disease risk. Our results highlighted the importance of understanding varietal dynamics, an often overlooked component of agriculture sustainability, in addition to evolutionary forces shaping agro-diversity and genetic diversity distribution within crops. It is also crucial to understand how processes involved do scale up worldwide and for different crop species, so as not to mislead on-farm conservation efforts and efficacy of agro-diversity preservation.
Penet, Laurent; Cornet, Denis; Blazy, Jean-Marc; Alleyne, Angela; Barthe, Emilie; Bussière, François; Guyader, Sébastien; Pavis, Claudie; Pétro, Dalila
2016-01-01
Loss of varietal diversity is a worldwide challenge to crop species at risk for genetic erosion, while the loss of biological resources may hinder future breeding objectives. Loss of varieties has been mostly investigated in traditional agricultural systems where variety numbers are dramatically high, or for most economically important crop species for which comparison between pre-intensive and modern agriculture was possible. Varietal dynamics, i.e., turnover, or gains and losses of varieties by farmers, is nevertheless more rarely studied and while we currently have good estimates of genetic or varietal diversity for most crop species, we have less information as to how on farm agro-diversity changes and what cause its dynamics. We therefore investigated varietal dynamics in the agricultural yam system in the Caribbean island of Guadeloupe. We interviewed producers about varieties they cultivated in the past compared to their current varieties, in addition to characterizing yam cropping characteristics and both farm level and producers socio-economic features. We then used regression tree analyses to investigate the components of yam agro-diversity, varietal dynamics and impact of anthracnose on varieties. Our data demonstrated that no dramatic loss of varieties occurred within the last decades. Cultivation changes mostly affected widespread cultivars while frequency of uncommon varieties stayed relatively stable. Varietal dynamics nevertheless followed sub-regional patterns, and socio-economic influences such as producer age or farm crop diversity. Recurrent anthracnose epidemics since the 1970s did not alter varietal dynamics strongly, but sometimes translated into transition from Dioscorea alata to less susceptible species or into a decrease of yam cultivation. Factors affecting changes in agro-diversity were not relating to agronomy in our study, and surprisingly there were different processes delineating short term from long term varietal dynamics, independently of disease risk. Our results highlighted the importance of understanding varietal dynamics, an often overlooked component of agriculture sustainability, in addition to evolutionary forces shaping agro-diversity and genetic diversity distribution within crops. It is also crucial to understand how processes involved do scale up worldwide and for different crop species, so as not to mislead on-farm conservation efforts and efficacy of agro-diversity preservation. PMID:28066500
USDA-ARS?s Scientific Manuscript database
Sustainable biomass feedstock production systems involve biomass generation from non-agricultural or marginal lands with minimal external inputs. Switch grass based alley cropping systems have been proposed as biomass feedstock crop systems in marginal lands. In many areas in the Midwest United Stat...
Model development for prediction of soil water dynamics in plant production.
Hu, Zhengfeng; Jin, Huixia; Zhang, Kefeng
2015-09-01
Optimizing water use in agriculture and medicinal plants is crucially important worldwide. Soil sensor-controlled irrigation systems are increasingly becoming available. However it is questionable whether irrigation scheduling based on soil measurements in the top soil could make best use of water for deep-rooted crops. In this study a mechanistic model was employed to investigate water extraction by a deep-rooted cabbage crop from the soil profile throughout crop growth. The model accounts all key processes governing water dynamics in the soil-plant-atmosphere system. Results show that the subsoil provides a significant proportion of the seasonal transpiration, about a third of water transpired over the whole growing season. This suggests that soil water in the entire root zone should be taken into consideration in irrigation scheduling, and for sensor-controlled irrigation systems sensors in the subsoil are essential for detecting soil water status for deep-rooted crops.
Impact of Seasonal Variability in Water, Plant and Soil Nutrient Dynamics in Agroecosystems
NASA Astrophysics Data System (ADS)
Pelak, N. F., III; Revelli, R.; Porporato, A. M.
2017-12-01
Agroecosystems cover a significant fraction of the Earth's surface, making their water and nutrient cycles a major component of global cycles across spatial and temporal scales. Most agroecosystems experience seasonality via variations in precipitation, temperature, and radiation, in addition to human activities which also occur seasonally, such as fertilization, irrigation, and harvesting. These seasonal drivers interact with the system in complex ways which are often poorly characterized. Crop models, which are widely used for research, decision support, and prediction of crop yields, are among the best tools available to analyze these systems. Though normally constructed as a set of dynamical equations forced by hydroclimatic variability, they are not often analyzed using dynamical systems theory and methods from stochastic ecohydrology. With the goal of developing this viewpoint and thus elucidating the roles of key feedbacks and forcings on system stability and on optimal fertilization and irrigation strategies, we develop a minimal dynamical system which contains the key components of a crop model, coupled to a carbon and nitrogen cycling model, driven by seasonal fluctuations in water and nutrient availability, temperature, and radiation. External drivers include seasonally varying climatic conditions and random rainfall forcing, irrigation and fertilization as well as harvesting. The model is used to analyze the magnitudes and interactions of the effects of seasonality on carbon and nutrient cycles, crop productivity, nutrient export of agroecosystems, and optimal management strategies with reference to productivity, sustainability and profitability. The impact of likely future climate scenarios on these systems is also discussed.
Simulating crop growth with Expert-N-GECROS under different site conditions in Southwest Germany
NASA Astrophysics Data System (ADS)
Poyda, Arne; Ingwersen, Joachim; Demyan, Scott; Gayler, Sebastian; Streck, Thilo
2016-04-01
When feedbacks between the land surface and the atmosphere are investigated by Atmosphere-Land surface-Crop-Models (ALCM) it is fundamental to accurately simulate crop growth dynamics as plants directly influence the energy partitioning at the plant-atmosphere interface. To study both the response and the effect of intensive agricultural crop production systems on regional climate change in Southwest Germany, the crop growth model GECROS (YIN & VAN LAAR, 2005) was calibrated based on multi-year field data from typical crop rotations in the Kraichgau and Swabian Alb regions. Additionally, the SOC (soil organic carbon) model DAISY (MÜLLER et al., 1998) was implemented in the Expert-N model tool (ENGEL & PRIESACK, 1993) and combined with GECROS. The model was calibrated based on a set of plant (BBCH, LAI, plant height, aboveground biomass, N content of biomass) and weather data for the years 2010 - 2013 and validated with the data of 2014. As GECROS adjusts the root-shoot partitioning in response to external conditions (water, nitrogen, CO2), it is suitable to simulate crop growth dynamics under changing climate conditions and potentially more frequent stress situations. As C and N pools and turnover rates in soil as well as preceding crop effects were expected to considerably influence crop growth, the model was run in a multi-year, dynamic way. Crop residues and soil mineral N (nitrate, ammonium) available for the subsequent crop were accounted for. The model simulates growth dynamics of winter wheat, winter rape, silage maize and summer barley at the Kraichgau and Swabian Alb sites well. The Expert-N-GECROS model is currently parameterized for crops with potentially increasing shares in future crop rotations. First results will be shown.
USDA-ARS?s Scientific Manuscript database
The dynamic conservation and sustainable utilization of native crop genetic resources are crucial for food sovereignty of Native American communities. Indigenous knowledge of crop diversity when linked to food traditions, local practices and social norms provide the basis for building sovereign comm...
Adapting crop rotations to climate change in regional impact modelling assessments.
Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank
2018-03-01
The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used to develop improved regional impact assessments for situations where multi-crop rotations better represent predominant agricultural systems. Copyright © 2017 Elsevier B.V. All rights reserved.
Loeb, Gregory M.
2018-01-01
Invasive, polyphagous crop pests subsist on a number of crop and non-crop resources. While knowing the full range of host species is important, a seasonal investigation into the use of non-crop plants adjacent to cropping systems provide key insights into some of the factors determining local population dynamics. This study investigated the infestation of non-crop plants by the invasive Drosophila suzukii (Matsumura), a pest of numerous economically important stone and small fruit crops, by sampling fruit-producing non-crop hosts adjacent to commercial plantings weekly from June through November in central New York over a two-year period. We found D. suzukii infestation rates (number of flies emerged/kg fruit) peaked mid-August through early September, with Rubus allegheniensis Porter and Lonicera morrowii Asa Gray showing the highest average infestation in both years. Interannual infestation patterns were similar despite a lower number of adults caught in monitoring traps the second year, suggesting D. suzukii host use may be density independent. PMID:29301358
Impacts of crop growth dynamics on soil quality at the regional scale
NASA Astrophysics Data System (ADS)
Gobin, Anne
2014-05-01
Agricultural land use and in particular crop growth dynamics can greatly affect soil quality. Both the amount of soil lost from erosion by water and soil organic matter are key indicators for soil quality. The aim was to develop a modelling framework for quantifying the impacts of crop growth dynamics on soil quality at the regional scale with test case Flanders. A framework for modelling the impacts of crop growth on soil erosion and soil organic matter was developed by coupling the dynamic crop cover model REGCROP (Gobin, 2010) to the PESERA soil erosion model (Kirkby et al., 2009) and to the RothC carbon model (Coleman and Jenkinson, 1999). All three models are process-based, spatially distributed and intended as a regional diagnostic tool. A geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System). Crop allometric models were developed from variety trials to calculate crop residues for common crops in Flanders and subsequently derive stable organic matter fluxes to the soil. Results indicate that crop growth dynamics and crop rotations influence soil quality for a very large percentage. soil erosion mainly occurs in the southern part of Flanders, where silty to loamy soils and a hilly topography are responsible for soil loss rates of up to 40 t/ha. Parcels under maize, sugar beet and potatoes are most vulnerable to soil erosion. Crop residues of grain maize and winter wheat followed by catch crops contribute most to the total carbon sequestered in agricultural soils. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. This implies that agricultural policies that impact on agricultural land management influence soil quality for a large percentage. The coupled REGCROP-PESERA-ROTHC model allows for quantifying the impact of seasonal and year-to-year crop growth dynamics on soil quality. When coupled to a multi-annual crop rotation database both spatial and temporal analysis becomes possible and allows for decision support at both farm and regional level. The framework is therefore suited for further scenario analysis and impact assessment. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.
Impacts of biofuel expansion on soil quality and carbon dynamics in a central Iowa watershed
USDA-ARS?s Scientific Manuscript database
Crop residues (plant litter) on the soil surface helps decrease soil erosion, increase water infiltration, increase soil organic matter, and improve soil quality. Thus, management of crop residues is an integral part of most conservation tillage systems. Crop residue cover is used to classify soil t...
An integrated soil-crop system model for water and nitrogen management in North China
Liang, Hao; Hu, Kelin; Batchelor, William D.; Qi, Zhiming; Li, Baoguo
2016-01-01
An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China. PMID:27181364
The stochastic resonance for the incidence function model of metapopulation
NASA Astrophysics Data System (ADS)
Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei
2017-06-01
A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.
Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System.
Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang
2017-03-03
In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R²) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively.
Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System
Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang
2017-01-01
In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R2) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively. PMID:28273815
Noah-MP-Crop: Introducing dynamic crop growth in the Noah-MP land surface model
NASA Astrophysics Data System (ADS)
Liu, Xing; Chen, Fei; Barlage, Michael; Zhou, Guangsheng; Niyogi, Dev
2016-12-01
Croplands are important in land-atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled Weather Research and Forecasting/Noah with multiparameterization (Noah-MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed-leaf area index (LAI)-driven methods in Noah-MP, the Noah-MP-Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah-MP-Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah-MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah-MP-Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah-MP allows further crop-related studies and development.
Productivity and nutrient cycling in bioenergy cropping systems
NASA Astrophysics Data System (ADS)
Heggenstaller, Andrew Howard
One of the greatest obstacles confronting large-scale biomass production for energy applications is the development of cropping systems that balance the need for increased productive capacity with the maintenance of other critical ecosystem functions including nutrient cycling and retention. To address questions of productivity and nutrient dynamics in bioenergy cropping systems, we conducted two sets of field experiments during 2005-2007, investigating annual and perennial cropping systems designed to generate biomass energy feedstocks. In the first experiment we evaluated productivity and crop and soil nutrient dynamics in three prototypical bioenergy double-crop systems, and in a conventionally managed sole-crop corn system. Double-cropping systems included fall-seeded forage triticale (x Triticosecale Wittmack), succeeded by one of three summer-adapted crops: corn (Zea mays L.), sorghum-sudangrass [Sorghum bicolor (L.) Moench], or sunn hemp (Crotalaria juncea L.). Total dry matter production was greater for triticale/corn and triticale/sorghum-sudangrass compared to sole-crop corn. Functional growth analysis revealed that photosynthetic duration was more important than photosynthetic efficiency in determining biomass productivity of sole-crop corn and double-crop triticale/corn, and that greater yield in the tiritcale/corn system was the outcome of photosynthesis occurring over an extended duration. Increased growth duration in double-crop systems was also associated with reductions in potentially leachable soil nitrogen relative to sole-crop corn. However, nutrient removal in harvested biomass was also greater in the double-crop systems, indicating that over the long-term, double-cropping would mandate increased fertilizer inputs. In a second experiment we assessed the effects of N fertilization on biomass and nutrient partitioning between aboveground and belowground crop components, and on carbon storage by four perennial, warm-season grasses: big bluestem (Andropogon geradii Vitman), switchgrass (Panicum virgatum L.), indiangrass [ Sorghastrum nutans (L.) Nash], and eastern gamagrass (Tripsacum dactyloides L.). Generally, the optimum rate of fertilization for biomass yield by the grasses was 140 kg N ha-1. Nitrogen inputs also had pronounced but grass-specific effects on biomass and nutrient partitioning, and on carbon storage. For big bluestem and switchgrass, 140 kg N ha -1. maximized root biomass, favored allocation of nutrients to roots over shoots, and led to net increases in carbon storage over the study duration. In contrast, for indiangrass and eastern gamagrass, root biomass and root nutrient allocation were generally adversely affected by N fertilization and carbon storage increased only with 0 or 65 kg N ha-1. For all grasses, 220 kg N ha -1 tended to shift allocation of nutrients to shoots over roots and resulted in no net increase in carbon storage. Optimal nitrogen management strategies for perennial, warm-season grass energy crops should take into consideration the effects of N on biomass yield as well as factors such as nutrient and carbon balance that will also impact economic feasibility and environmental sustainability.
A generic model to simulate air-borne diseases as a function of crop architecture.
Casadebaig, Pierre; Quesnel, Gauthier; Langlais, Michel; Faivre, Robert
2012-01-01
In a context of pesticide use reduction, alternatives to chemical-based crop protection strategies are needed to control diseases. Crop and plant architectures can be viewed as levers to control disease outbreaks by affecting microclimate within the canopy or pathogen transmission between plants. Modeling and simulation is a key approach to help analyze the behaviour of such systems where direct observations are difficult and tedious. Modeling permits the joining of concepts from ecophysiology and epidemiology to define structures and functions generic enough to describe a wide range of epidemiological dynamics. Additionally, this conception should minimize computing time by both limiting the complexity and setting an efficient software implementation. In this paper, our aim was to present a model that suited these constraints so it could first be used as a research and teaching tool to promote discussions about epidemic management in cropping systems. The system was modelled as a combination of individual hosts (population of plants or organs) and infectious agents (pathogens) whose contacts are restricted through a network of connections. The system dynamics were described at an individual scale. Additional attention was given to the identification of generic properties of host-pathogen systems to widen the model's applicability domain. Two specific pathosystems with contrasted crop architectures were considered: ascochyta blight on pea (homogeneously layered canopy) and potato late blight (lattice of individualized plants). The model behavior was assessed by simulation and sensitivity analysis and these results were discussed against the model ability to discriminate between the defined types of epidemics. Crop traits related to disease avoidance resulting in a low exposure, a slow dispersal or a de-synchronization of plant and pathogen cycles were shown to strongly impact the disease severity at the crop scale.
RUIZ-RAMOS, MARGARITA; MÍNGUEZ, M. INÉS
2006-01-01
• Background Plant structural (i.e. architectural) models explicitly describe plant morphology by providing detailed descriptions of the display of leaf and stem surfaces within heterogeneous canopies and thus provide the opportunity for modelling the functioning of plant organs in their microenvironments. The outcome is a class of structural–functional crop models that combines advantages of current structural and process approaches to crop modelling. ALAMEDA is such a model. • Methods The formalism of Lindenmayer systems (L-systems) was chosen for the development of a structural model of the faba bean canopy, providing both numerical and dynamic graphical outputs. It was parameterized according to the results obtained through detailed morphological and phenological descriptions that capture the detailed geometry and topology of the crop. The analysis distinguishes between relationships of general application for all sowing dates and stem ranks and others valid only for all stems of a single crop cycle. • Results and Conclusions The results reveal that in faba bean, structural parameterization valid for the entire plant may be drawn from a single stem. ALAMEDA was formed by linking the structural model to the growth model ‘Simulation d'Allongement des Feuilles’ (SAF) with the ability to simulate approx. 3500 crop organs and components of a group of nine plants. Model performance was verified for organ length, plant height and leaf area. The L-system formalism was able to capture the complex architecture of canopy leaf area of this indeterminate crop and, with the growth relationships, generate a 3D dynamic crop simulation. Future development and improvement of the model are discussed. PMID:16390842
NASA Astrophysics Data System (ADS)
Gower, Drew B.; Dell'Angelo, Jampel; McCord, Paul F.; Caylor, Kelly K.; Evans, Tom P.
2016-11-01
In dryland environments, characterized by low and frequently variable rainfall, smallholder farmers must take crop water sensitivity into account along with other characteristics like seed availability and market price when deciding what to plant. In this paper we use the results of surveys conducted among smallholders located near Mount Kenya to identify clusters of farmers devoting different fractions of their land to subsistence and market crops. Additionally, we explore the tradeoffs between water-insensitive but low-value subsistence crops and a water-sensitive but high-value market crop using a numerical model that simulates soil moisture dynamics and crop production over multiple growing seasons. The cluster analysis shows that most farmers prefer to plant either only subsistence crops or only market crops, with a minority choosing to plant substantial fractions of both. The model output suggests that the value a farmer places on a successful growing season, a measure of risk aversion, plays a large role in whether the farmer chooses a subsistence or market crop strategy. Furthermore, access to irrigation, makes market crops more appealing, even to very risk-averse farmers. We then conclude that the observed clustering may result from different levels of risk aversion and access to irrigation.
Crop Management to Cope with Global Change: A Systems Perspective Aided by Information Technologies
USDA-ARS?s Scientific Manuscript database
Optimizing crop management must consider the dynamic interaction of abiotic and biotic factors within the context of economic, environmental, sociological, and policy constraints. A wide array of information technologies exists to assist producers, consultants, scientists, agribusiness, action agenc...
USDA-ARS?s Scientific Manuscript database
Under an integrated crop-livestock production system, plant and animal residues become an important nutrient stock. Grazing management could affect both plant and animal residue amount and quality, thereby influencing nutrient dynamics through modifications in nutrient release rates. The objective o...
Good, J M; Murphy, W S; Brodie, B B
1973-04-01
During a 6-year study of 1-, 2-, and 3-year crop rotations, population densities of Pratylenchus brachyurus, Trichodorus christiei, and Meloidogyne incognita were significantly affected by the choice of crops but not by length of crop rotation. The density of P. brachyurus and T. christiei increased rapidly on milo (Sorghum vulgate). In addition, populations of P. brachyurus increased significantly in cropping systems that involved crotalaria (C. rnucronata), millet (Setaria italica), and sudangrass (Sorghum sudanense). Lowest numbers of P. brachyurus occurred where okra (Hibiscus esculentus) was grown or where land was fallow. The largest increase in populations of T. christiei occurred in cropping systems that involved millet, sudangrass, and okra whereas the smallest increase occurred in cropping systems that involved crotalaria or fallow. A winter cover of rye (Secale cereale) had no distinguishable effect on population densities of P. brachyurus or T. christiei. Meloidogyne incognita was detected during the fourth year in both newly cleared and old agricultural land when okra was included in the cropping system. Detectable populations of M. incognita did not develop in any of the other cropping systems. Yields of tomato transplants were higher on the newly cleared land than on the old land. Highest yields were obtained when crotalaria was included in the cropping system. Lowest yields were obtained when milo, or fallow were included in the cropping system. Length of rotation had no distinguishable effect on yields of tomato transplants.
NASA Astrophysics Data System (ADS)
van Walsum, P. E. V.
2011-11-01
Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.
Pervin, Lia; Islam, Md Saiful
2015-02-01
The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.
Simulating soil organic carbon in a wheat–fallow system using the Daycent model
USDA-ARS?s Scientific Manuscript database
Crop management practices that contribute to soil organic carbon (SOC) sequestration can improve productivity and long-term sustainability. We present a modeling study on influence of (>80 years) various long-term crop residue and nutrient management practices on SOC dynamics under conventional and ...
Behera, Rabi Narayan; Nayak, Debendra Kumar; Andersen, Peter; Måren, Inger Elisabeth
2016-02-01
Human population growth in the developing world drives land-use changes, impacting food security. In India, the dramatic change in demographic dynamics over the past century has reduced traditional agricultural land-use through increasing commercialization. Here, we analyze the magnitude and implications for the farming system by the introduction of cash-cropping, replacing the traditional slash and burn rotations (jhum), of the tribal people on the Meghalaya Plateau, northeast India, by means of agricultural census data and field surveys conducted in seven villages. Land-use change has brought major alterations in hill agricultural practices, enhanced cash-cropping, promoted mono-cropping, changed food consumption patterns, underpinned the emergence of a new food system, and exposed farmers and consumers to the precariousness of the market, all of which have both long- and short-term food security implications. We found dietary diversity to be higher under jhum compared to any of the cash-crop systems, and higher under traditional cash-cropping than under modern cash-cropping.
Minimising losses to predation during microalgae cultivation.
Flynn, Kevin J; Kenny, Philip; Mitra, Aditee
2017-01-01
We explore approaches to minimise impacts of zooplanktonic pests upon commercial microalgal crops using system dynamics models to describe algal growth controlled by light and nutrient availability and zooplankton growth controlled by crop abundance and nutritional quality. Losses of microalgal crops are minimised when their growth is fastest and, in contrast, also when growing slowly under conditions of nutrient exhaustion. In many culture systems, however, dwindling light availability due to self-shading in dense suspensions favours slow growth under nutrient sufficiency. Such a situation improves microalgal quality as prey, enhancing zooplankton growth, and leads to rapid crop collapse. Timing of pest entry is important; crop losses are least likely in established, nutrient-exhausted microalgal communities grown for high C-content (e.g. for biofuels). A potentially useful approach is to promote a low level of P-stress that does not adversely affect microalgal growth but which produces a crop that is suboptimal for zooplankton growth.
To, Jennifer Pc; Zhu, Jinming; Benfey, Philip N; Elich, Tedd
2010-09-08
Root system architecture (RSA) describes the dynamic spatial configuration of different types and ages of roots in a plant, which allows adaptation to different environments. Modifications in RSA enhance agronomic traits in crops and have been implicated in soil organic carbon content. Together, these fundamental properties of RSA contribute to the net carbon balance and overall sustainability of biofuels. In this article, we will review recent data supporting carbon sequestration by biofuel crops, highlight current progress in studying RSA, and discuss future opportunities for optimizing RSA for biofuel production and soil carbon sequestration.
Silvie, P J; Menzel, C A; Mello, A; Coelho, A G
2010-01-01
Direct seeding mulch-based cropping systems under a preliminary cover crop such as millet are common in some areas of Brazil. Lepidopteran pests that damage cotton, soybean and maize crops can proliferate on cover crops, so preventive chemical treatments are necessary. Very little data is available on these pests on cover crops. This paper presents the dynamics of Spodoptera frugiperda, S. eridania, Mocis latipes and Diatraea saccharalis caterpillars monitored at Primavera do Leste, Mato Grosso state (Brazil) during the of 2005/2006 and 2006/2007 cropping seasons on four cover crops, i.e. finger millet (Eleusine coracana), pearl millet (Pennisetum glaucum), sorghum (Sorghum bicolor) and ruzigrass (Brachiaria ruziziensis). The pests were visually counted on plants within a 1 m2 transect (wooden frame). Caterpillars were reared to facilitate identification of collected species and parasitoids. Many S. frugiperda caterpillars were observed on millet in 2005, with a maximum of 37 caterpillars/m2. On sorghum, we found 30 caterpillars/m2, or 0.83 caterpillars/plant. The Diatraea borer attacked sorghum later than the other pests. M. latipes was also observed on millet. The millet cover crop had to be dried for at least 1 month before direct drilling the main cotton crop in order to impede S. frugiperda infestations on cotton plantlets, thus avoiding the need for substantial resowing. The comparative methodological aspects are discussed.
USDA-ARS?s Scientific Manuscript database
Soil organic C and N are important indicators of agricultural sustainability, yet numerous field studies have revealed a multitude of responses in the extent and rate of change imposed by conservation management, and therefore, a lack of clarity on responses. We conducted an evaluation of total and...
USDA-ARS?s Scientific Manuscript database
Soil microorganisms play essential roles in soil organic matter dynamics and nutrient cycling in agroecosystems and have been used as soil quality indicators. The response of soil microbial communities to land management is complex and the long-term impacts of cropping systems on soil microbes is l...
The use of seasonal forecasts in a crop failure early warning system for West Africa
NASA Astrophysics Data System (ADS)
Nicklin, K. J.; Challinor, A.; Tompkins, A.
2011-12-01
Seasonal rainfall in semi-arid West Africa is highly variable. Farming systems in the region are heavily dependent on the monsoon rains leading to large variability in crop yields and a population that is vulnerable to drought. The existing crop yield forecasting system uses observed weather to calculate a water satisfaction index, which is then related to expected crop yield (Traore et al, 2006). Seasonal climate forecasts may be able to increase the lead-time of yield forecasts and reduce the humanitarian impact of drought. This study assesses the potential for a crop failure early warning system, which uses dynamic seasonal forecasts and a process-based crop model. Two sets of simulations are presented. In the first, the crop model is driven with observed weather as a control run. Observed rainfall is provided by the GPCP 1DD data set, whilst observed temperature and solar radiation data are given by the ERA-Interim reanalysis. The crop model used is the groundnut version of the General Large Area Model for annual crops (GLAM), which has been designed to operate on the grids used by seasonal weather forecasts (Challinor et al, 2004). GLAM is modified for use in West Africa by allowing multiple planting dates each season, replanting failed crops and producing parameter sets for Spanish- and Virginia- type West African groundnut. Crop yields are simulated for three different assumptions concerning the distribution and relative abundance of Spanish- and Virginia- type groundnut. Model performance varies with location, but overall shows positive skill in reproducing observed crop failure. The results for the three assumptions are similar, suggesting that the performance of the system is limited by something other than information on the type of groundnut grown. In the second set of simulations the crop model is driven with observed weather up to the forecast date, followed by ECMWF system 3 seasonal forecasts until harvest. The variation of skill with forecast date is assessed along with the extent to which forecasts can be improved by bias correction of the rainfall data. Two forms of bias correction are applied: a novel method of spatially bias correcting daily data, and statistical bias correction of the frequency and intensity distribution. Results are presented using both observed yields and the control run as the reference for verification. The potential for current dynamic seasonal forecasts to form part of an operational system giving timely and accurate warnings of crop failure is discussed. Traore S.B. et al., 2006. A Review of Agrometeorological Monitoring Tools and Methods Used in the West African Sahel. In: Motha R.P. et al., Strengthening Operational Agrometeorological Services at the National Level. Technical Bulletin WAOB-2006-1 and AGM-9, WMO/TD No. 1277. Pages 209-220. www.wamis.org/agm/pubs/agm9/WMO-TD1277.pdf Challinor A.J. et al., 2004. Design and optimisation of a large-area process based model for annual crops. Agric. For. Meteorol. 124, 99-120.
McDaniel, M. D.; Grandy, A. S.; Tiemann, L. K.; ...
2016-08-11
Agricultural crop rotations have been shown to increase soil carbon (C), nitrogen (N), and microbial biomass. The mechanisms behind these increases remain unclear, but may be linked to the diversity of crop residue inputs to soil organic matter (SOM). Here, we used a residue mixture incubation to examine how variation in long-term diversity of plant communities in agroecosystems influences decomposition of residue mixtures, thus providing a comparison of the effects of plant diversification on decomposition in the long term (via crop rotation) and short term (via residue mixtures). Three crop residue mixtures, ranging in diversity from two to four species,more » were incubated for 360 d with soils from five crop rotations, ranging from monoculture corn (mC) to a complex five-crop rotation. In response, we measured fundamental soil pools and processes underlying C and N cycling. These included soil respiration, inorganic N, microbial biomass, and extracellular enzymes. We hypothesized that soils with more diverse cropping histories would show greater synergistic mixture effects than mC. For most variables (except extracellular enzymes), crop rotation history, or the long-term history of plant diversity in the field, had a stronger effect on soil processes than mixture composition. In contrast to our hypothesis, the mC soil had nearly three and seven times greater synergistic mixture effects for respiration and microbial biomass N, respectively, compared with soils from crop rotations. This was due to the low response of the mC soils to poor quality residues (corn and wheat), likely resulting from a lack of available C and nutrients to cometabolize these residues. These results indicate that diversifying crop rotations in agricultural systems alter the decomposition dynamics of new residue inputs, which may be linked to the benefits of increasing crop rotation diversity on soil nutrient cycling, SOM dynamics, and yields.« less
NASA Astrophysics Data System (ADS)
Szymanski, L. M.; Sanford, G. R.; Heckman, K. A.; Jackson, R. D.; Marin-Spiotta, E.
2016-12-01
In the face of climate change, the global production of bioenergy crops has increased in response to policies calling for non-fossil energy sources as a means to mitigate rising atmospheric carbon (C) concentrations. To provide overall C sequestration benefits, identifying biomass crops that can maintain or enhance soil resources is desirable for sustainable bioenergy production. The objective of our study was to compare the effects of four bioenergy cropping systems on SOM dynamics in two agricultural soils: Mollisols at the University of Wisconsin Agricultural Research Station in Arlington, Wisconsin and Alfisols at Kellogg Biological Station in Hickory Corners, Michigan, USA. We used fresh soils collected in 2013 and archived soils collected in 2008 to measure differences among biofuel crops after 5 years of management. Using a 365-day laboratory soil incubation and radiocarbon measurements of bulk soil and respired C, we separated soils into three SOM pools and determined their corresponding turnover times. Total soil C respired from surface soils increased in the order: mixed species perennials > monoculture perennials > monoculture annuals. More C was associated with the active fraction in the sandy loam Alfisol and with the slow-cycling fraction in the silt loam Mollisol. Radiocarbon content of respired CO2 did not differ between corn and switchgrass, but did differ between 2008 and 2013. The respiration of more radiocarbon-depleted C after 5 years of cultivation may be due to an initial flux of young C following tillage in 2008 or to depletion of labile plant inputs with continued harvest. All bioenergy cropping systems lost soil C after 5 years. Monoculture perennial switchgrass systems did not provide significant C sequestration benefits, as expected, compared to monoculture annual corn systems. Bioenergy crop land-use change affects soil C dynamics, with implications for assessing C costs associated with biofuel production.
Spatio-Temporal Dynamics of Maize Yield Water Constraints under Climate Change in Spain
Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis
2014-01-01
Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent “hot-spots” in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity. PMID:24878747
Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.
Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis
2014-01-01
Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.
Integrated Systems Mitigate Land Degradation and Improve Agricultural System Sustainability
NASA Astrophysics Data System (ADS)
Landblom, Douglas; Senturklu, Songul; Cihacek, Larry; Brevik, Eric
2017-04-01
Rain-fed agricultural production supported by exogenous inputs is not sustainable because a continuous influx of expensive inputs (fertilizer, chemicals, fossil fuel, labor, tillage, and other) is required. Alternatives to traditional management allow natural occurring dynamic soil processes to provide the necessary microbial activity that supports nutrient cycling in balance with nature. Research designed to investigate the potential for integrated systems to replace expensive inputs has shown that healthy soils rich in soil organic matter (SOM) are the foundation upon which microbial nutrient cycling can reduce and eventually replace expensive fertilizer. No-till seed placement technology effectively replaces multiple-pass cultivation conserving stored soil water in semi-arid farming systems. In multi-crop rotations, cool- and warm-season crops are grown in sequence to meet goals of the integrated farming and ranching system, and each crop in the rotation complements the subsequent crop by supplying a continuous flow of essential SOM for soil nutrient cycling. Grazing animals serve an essential role in the system's sustainability as non-mechanized animal harvesters that reduce fossil fuel consumption and labor, and animal waste contributes soil nutrients to the system. Integrated systems' complementarity has contributed to greater soil nutrient cycling and crop yields, fertilizer reduction or elimination, greater yearling steer grazing net return, reduced cow wintering costs grazing crop residues, increased wildlife sightings, and reduced environmental footprint. Therefore, integrating crop and animal systems can reverse soil quality decline and adopting non-traditional procedures has resulted in a wider array of opportunities for sustainable agriculture and profitability.
NASA Astrophysics Data System (ADS)
Kumari, S.; Sharma, P.; Srivastava, A.; Rastogi, D.; Sehgal, V. K.; Dhakar, R.; Roy, S. B.
2017-12-01
Vegetation dynamics and surface meteorology are tightly coupled through the exchange of momentum, moisture and heat between the land surface and the atmosphere. In this study, we use a recently developed coupled atmosphere-crop growth dynamics model to study these exchanges and their effects in a spring wheat cropland in northern India. In particular, we investigate the role of irrigation in controlling crop growth rates, surface meteorology, and sensible and latent heat fluxes. The model is developed by implementing a crop growth module based on the Simple and Universal Crop growth Simulator (SUCROS) model in the Weather Research Forecasting (WRF) mesoscale atmospheric model. The crop module calculates photosynthesis rates, carbon assimilation, and biomass partitioning as a function of environmental factors and crop development stage. The leaf area index (LAI) and root depth calculated by the crop module is then fed to the Noah-MP land module of WRF to calculate land-atmosphere fluxes. The crop model is calibrated using data from an experimental spring wheat crop site in the Indian Agriculture Research Institute. The coupled model is capable of simulating the observed spring wheat phenology. Irrigation is simulated by changing the soil moisture levels from 50% - 100% of field capacity. Results show that the yield first increases with increasing soil moisture and then starts decreasing as we further increase the soil moisture. Yield attains its maximum value with soil moisture at the level of 60% water of FC. At this level, high LAI values lead to a decrease in the Bowen Ratio because more energy is transferred to the atmosphere as latent heat rather than sensible heat resulting in a cooling effect on near-surface air temperatures. Apart from improving simulation of land-atmosphere interactions, this coupled modeling approach can form the basis for the seamless crop yield and seasonal scale weather outlook prediction system.
Based on long-term monitoring conducted in Chang-ning county, a pilot site of the ‘Grain for Green Program’ (GFGP), an integrated emergy and economic method was applied to evaluate the dynamic ecological-economic performance of 3 kinds of bamboo systems planted on slo...
USDA-ARS?s Scientific Manuscript database
Understanding the effects of fertilizer addition and crop removal on long-term change in soil test phosphorus (STP) and soil test potassium (STK) is crucial for maximizing the use of grower inputs on claypan soils. Due to variable nutrient supply from subsoils and variable crop removal across fields...
Seasonal Population Dynamics of Three Potato Pests in Washington State.
D'Auria, Elizabeth M; Wohleb, Carrie H; Waters, Timothy D; Crowder, David W
2016-08-01
Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculella Zeller), the beet leafhopper (Circulifer tenellus Baker), and the green peach aphid (Myzus persicae Sulzer). Each of these pests directly damages potato foliage or tubers; C. tenellus and M. persicae also transmit pathogens that can drastically reduce potato yields. We monitored the seasonal population dynamics of these pests by conducting weekly sampling on a network of commercial farms from 2007 to 2014. Using these data, we developed phenology models to characterize the seasonal population dynamics of each pest based on accumulated degree-days (DD). All three pests exhibited consistent population dynamics across seasons that were mediated by temperature. Of the three pests, C. tenellus was generally the first detected in potato crops, with 90% of adults captured by 936 DD. In contrast, populations of P. operculella and M. persicae built up more slowly over the course of the season, with 90% cumulative catch by 1,590 and 2,634 DD, respectively. Understanding these seasonal patterns could help potato producers plan their IPM strategies while allowing them to move away from calendar-based applications of insecticides. More broadly, our results show how long-term monitoring studies that explore dynamics of multiple pest species can aid in developing IPM strategies in crop systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Fernandes, Francisco S; Godoy, Wesley A C; Ramalho, Francisco S; Garcia, Adriano G; Santos, Bárbara D B; Malaquias, José B
2018-01-01
Population dynamics of aphids have been studied in sole and intercropping systems. These studies have required the use of more precise analytical tools in order to better understand patterns in quantitative data. Mathematical models are among the most important tools to explain the dynamics of insect populations. This study investigated the population dynamics of aphids Aphis gossypii and Aphis craccivora over time, using mathematical models composed of a set of differential equations as a helpful analytical tool to understand the population dynamics of aphids in arrangements of cotton and cowpea. The treatments were sole cotton, sole cowpea, and three arrangements of cotton intercropped with cowpea (t1, t2 and t3). The plants were infested with two aphid species and were evaluated at 7, 14, 28, 35, 42, and 49 days after the infestations. Mathematical models were used to fit the population dynamics of two aphid species. There were good fits for aphid dynamics by mathematical model over time. The highest population peak of both species A. gossypii and A. craccivora was found in the sole crops, and the lowest population peak was found in crop system t2. These results are important for integrated management programs of aphids in cotton and cowpea.
Liu, Ping-li; Zhang, Xiao-lin; Xiong, Zheng-qin; Huang, Tai-qing; Ding, Min; Wang, Jin-yang
2011-09-01
To investigate the dynamic distribution patterns of nitrous oxide (N2O) in the soil profiles in paddy fields with different rice-upland crop rotation systems, a special soil gas collection device was adopted to monitor the dynamics of N2O at the soil depths 7, 15, 30, and 50 cm in the paddy fields under both flooding and drainage conditions. Two rotation systems were installed, i.e., wheat-single rice and oilseed rape-double rice, each with or without nitrogen (N) application. Comparing with the control, N application promoted the N2O production in the soil profiles significantly (P < 0.01), and there existed significant correlations in the N2O concentration among the four soil depths during the whole observation period (P < 0.01). In the growth seasons of winter wheat and oilseed rape under drainage condition and with or without N application, the N2O concentrations at the soil depths 30 cm and 50 cm were significantly higher than those at the soil depths 7 cm and 15 cm; whereas in the early rice growth season under flooding condition and without N application, the N2O concentrations at the soil depth 7 cm and 15 cm were significantly higher than those at the soil depths 30 cm and 50 cm (P < 0.05). No significant differences were observed in the N2O concentrations at the test soil depths among the other rice cropping treatments. The soil N2O concentrations in the treatments without N application peaked in the transitional period from the upland crops cropping to rice planting, while those in the treatments with N application peaked right after the second topdressing N of upland crops. Relatively high soil N2O concentrations were observed at the transitional period from the upland crops cropping to rice planting.
Grab, Heather; Blitzer, Eleanor J.; Danforth, Bryan; Loeb, Greg; Poveda, Katja
2017-01-01
One of the greatest challenges in sustainable agricultural production is managing ecosystem services, such as pollination, in ways that maximize crop yields. Most efforts to increase services by wild pollinators focus on management of natural habitats surrounding farms or non-crop habitats within farms. However, mass flowering crops create resource pulses that may be important determinants of pollinator dynamics. Mass bloom attracts pollinators and it is unclear how this affects the pollination and yields of other co-blooming crops. We investigated the effects of mass flowering apple on the pollinator community and yield of co-blooming strawberry on farms spanning a gradient in cover of apple orchards in the landscape. The effect of mass flowering apple on strawberry was dependent on the stage of apple bloom. During early and peak apple bloom, pollinator abundance and yield were reduced in landscapes with high cover of apple orchards. Following peak apple bloom, pollinator abundance was greater on farms with high apple cover and corresponded with increased yields on these farms. Spatial and temporal overlap between mass flowering and co-blooming crops alters the strength and direction of these dynamics and suggests that yields can be optimized by designing agricultural systems that avoid competition while maximizing facilitation. PMID:28345653
A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results
NASA Astrophysics Data System (ADS)
di, L.; Yang, Z.
2009-12-01
Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.
NASA Technical Reports Server (NTRS)
Volk, Tyler
1993-01-01
During the past several years, the NASA Program in Controlled Ecological Life Support Systems (CELSS) has continued apace with crop research and logistic, technological, and scientific strides. These include the CELSS Test Facility planned for the space station and its prototype Engineering Development Unit, soon to be active at Ames Research Center (as well as the advanced crop growth research chamber at Ames); the large environmental growth chambers and the planned human test bed facility at Johnson Space Center; the NSCORT at Purdue with new candidate crops and diverse research into the CELSS components; the gas exchange data for soy, potatoes, and wheat from Kennedy Space Center (KSC); and the high-precision gas exchange data for wheat from Utah State University (USU). All these developments, taken together, speak to the need for crop modeling as a means to connect the findings of the crop physiologists with the engineers designing the system. A need also exists for crop modeling to analyze and predict the gas exchange data from the various locations to maximize the scientific yield from the experiments. One fruitful approach employs what has been called the 'energy cascade'. Useful as a basis for CELSS crop growth experimental design, the energy cascade as a generic modeling approach for CELSS crops is a featured accomplishment in this report. The energy cascade is a major tool for linking CELSS crop experiments to the system design. The energy cascade presented here can help collaborations between modelers and crop experimenters to develop the most fruitful experiments for pushing the limits of crop productivity. Furthermore, crop models using the energy cascade provide a natural means to compare, feature for feature, the crop growth components between different CELSS experiments, for example, at Utah State University and Kennedy Space Center.
NASA Astrophysics Data System (ADS)
Robertson, G. P.; McSwiney, C. P.
2003-12-01
Agriculture is responsible for 21-25% of the global anthropic CO2 flux, 55-60% of the anthropic CH4 flux, and 65-80% of the anthopic flux of N2O. A number of CO2 stabilization strategies target agricultural production practices, and the potential for simultaneously abating fluxes of the non-CO2 greenhouse gases is substantial. But so is the potential for creating greenhouse gas (GHG) liabilities, the unintentional increase in one or more GHGs by activities that mitigate another. Whole-system accounting provides a means for including all GHG-contributing processes in the same cropping system analysis in order to illuminate major liabilities and synergies. We contrast a field crop system in the upper U.S. midwest with unmanaged successional ecosystems in the same landscape, and provide evidence that N2O flux - the major contributor to radiative forcing in row-crop systems - can be abated with little loss of crop productivity.
Computational fluid dynamics applications to improve crop production systems
USDA-ARS?s Scientific Manuscript database
Computational fluid dynamics (CFD), numerical analysis and simulation tools of fluid flow processes have emerged from the development stage and become nowadays a robust design tool. It is widely used to study various transport phenomena which involve fluid flow, heat and mass transfer, providing det...
NASA Astrophysics Data System (ADS)
Szymanski, L. M.; Marin-Spiotta, E.; Sanford, G. R.; Jackson, R. D.; Heckman, K. A.
2015-12-01
Bioenergy crops have the potential to provide a low carbon-intensive alternative to fossil fuels. More than a century of agricultural research has shown that conventional cropping systems can reduce soil organic matter (SOM) reservoirs, which cause long-term soil nutrient loss and C release to the atmosphere. In the face of climate change and other human disruptions to biogeochemical cycles, identifying biofuel crops that can maintain or enhance soil resources is desirable for the sustainable production of bioenergy. The objective of our study was to compare the effects of four biofuel crop treatments on SOM dynamics in two agricultural soils: Mollisols at Arlington Agricultural Research Station in Wisconsin and Alfisols at Kellogg Biological Station in Michigan, USA. We used fresh soils collected in 2013 and archived soils from 2008 to measure the effects of five years of crop management. Using a one-year long laboratory soil incubation coupled with a regression model and radiocarbon measurements, we separated soils into three SOM pools and their corresponding C turnover times. We found that the active pool, or biologically available C, was more sensitive to management and is an earlier indicator of changes to soil C dynamics than bulk soil C measurements. There was no effect of treatment on the active pool size at either site; however, the percent C in the active pool decreased, regardless of crop type, in surface soils with high clay content. At depth, the response of the slow pool differed between annual and perennial cropping systems. The distribution of C among SOM fractions varied between the two soil types, with greater C content associated with the active fraction in the coarser textured-soil and greater C content associated with the slow-cycling fraction in the soils with high clay content. These results suggest that the effects of bioenergy crops on soil resources will vary geographically, with implications for the carbon-cost of biocrop production.
Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P
2015-01-01
Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Key Points Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands PMID:26709335
Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P
2015-06-01
Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands.
NASA Astrophysics Data System (ADS)
Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.
2015-04-01
To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is well suited for the use of Sentinel-2's continuous and manifold data stream.
Mortality and Population Dynamics of Bemisia tabaci within a Multi-Crop System
USDA-ARS?s Scientific Manuscript database
The population dynamics of mobile polyphagous pests is governed by a complex set of interacting factors that involve multiple host-plants, seasonality, movement and demography. Bemisia tabaci is a multivoltine insect with no diapause that maintains population continuity by moving from one host to a...
Land-use legacies regulate decomposition dynamics following bioenergy crop conversion
Kallenbach, Cynthia M.; Stuart Grandy, A.
2014-07-14
Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter andmore » when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.« less
Soy moratorium impacts on soybean and deforestation dynamics in Mato Grosso, Brazil.
Kastens, Jude H; Brown, J Christopher; Coutinho, Alexandre Camargo; Bishop, Christopher R; Esquerdo, Júlio César D M
2017-01-01
Previous research has established the usefulness of remotely sensed vegetation index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to characterize the spatial dynamics of agriculture in the state of Mato Grosso (MT), Brazil. With these data it has become possible to track MT agriculture, which accounts for ~85% of Brazilian Amazon soy production, across periods of several years. Annual land cover (LC) maps support investigation of the spatiotemporal dynamics of agriculture as they relate to forest cover and governance and policy efforts to lower deforestation rates. We use a unique, spatially extensive 9-year (2005-2013) ground reference dataset to classify, with approximately 80% accuracy, MODIS VI data, merging the results with carefully processed annual forest and sugarcane coverages developed by Brazil's National Institute for Space Research to produce LC maps for MT for the 2001-2014 crop years. We apply the maps to an evaluation of forest and agricultural intensification dynamics before and after the Soy Moratorium (SoyM), a governance effort enacted in July 2006 to halt deforestation for the purpose of soy production in the Brazilian Amazon. We find the pre-SoyM deforestation rate to be more than five times the post-SoyM rate, while simultaneously observing the pre-SoyM forest-to-soy conversion rate to be more than twice the post-SoyM rate. These observations support the hypothesis that SoyM has played a role in reducing both deforestation and subsequent use for soy production. Additional analyses explore the land use tendencies of deforested areas and the conceptual framework of horizontal and vertical agricultural intensification, which distinguishes production increases attributable to cropland expansion into newly deforested areas as opposed to implementation of multi-cropping systems on existing cropland. During the 14-year study period, soy production was found to shift from predominantly single-crop systems to majority double-crop systems.
New Approaches to Capture High Frequency Agricultural Dynamics in Africa through Mobile Phones
NASA Astrophysics Data System (ADS)
Evans, T. P.; Attari, S.; Plale, B. A.; Caylor, K. K.; Estes, L. D.; Sheffield, J.
2015-12-01
Crop failure early warning systems relying on remote sensing constitute a new critical resource to assess areas where food shortages may arise, but there is a disconnect between the patterns of crop production on the ground and the environmental and decision-making dynamics that led to a particular crop production outcome. In Africa many governments use mid-growing season household surveys to get an on-the-ground assessment of current agricultural conditions. But these efforts are cost prohibitive over large scales and only offer a one-time snapshot at a particular time point. They also rely on farmers to recall past decisions and farmer recall may be imperfect when answering retrospectively on a decision made several months back (e.g. quantity of seed planted). We introduce a novel mobile-phone based approach to acquire information from farmers over large spatial extents, at high frequency at relatively low-cost compared to household survey approaches. This system makes compromises in number of questions which can feasibly be asked of a respondent (compared to household interviews), but the benefit of capturing weekly data from farmers is very exciting. We present data gathered from farmers in Kenya and Zambia to understand key dimensions of agricultural decision making such as choice of seed variety/planting date, frequency and timing of weeding/fertilizing and coping strategies such as pursuing off-farm labor. A particularly novel aspect of this work is reporting from farmers of what their expectation of end-season harvest will be on a week-by-week basis. Farmer's themselves can serve as sentinels of crop failure in this system. And farmers responses to drought are as much driven by their expectations of looming crop failure that may be different from that gleaned from remote sensing based assessment. This work is one piece of a larger design to link farmers to high-density meteorological data in Africa as an additional tool to improve crop failure early warning systems and understand adaptation to climate variability.
Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system
NASA Astrophysics Data System (ADS)
Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.
2015-12-01
Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments
NASA Astrophysics Data System (ADS)
Gunda, T.; Bazuin, J. T.; Nay, J.; Yeung, K. L.
2017-03-01
Access to seasonal climate forecasts can benefit farmers by allowing them to make more informed decisions about their farming practices. However, it is unclear whether farmers realize these benefits when crop choices available to farmers have different and variable costs and returns; multiple countries have programs that incentivize production of certain crops while other crops are subject to market fluctuations. We hypothesize that the benefits of forecasts on farmer livelihoods will be moderated by the combined impact of differing crop economics and changing climate. Drawing upon methods and insights from both physical and social sciences, we develop a model of farmer decision-making to evaluate this hypothesis. The model dynamics are explored using empirical data from Sri Lanka; primary sources include survey and interview information as well as game-based experiments conducted with farmers in the field. Our simulations show that a farmer using seasonal forecasts has more diversified crop selections, which drive increases in average agricultural income. Increases in income are particularly notable under a drier climate scenario, when a farmer using seasonal forecasts is more likely to plant onions, a crop with higher possible returns. Our results indicate that, when water resources are scarce (i.e. drier climate scenario), farmer incomes could become stratified, potentially compounding existing disparities in farmers’ financial and technical abilities to use forecasts to inform their crop selections. This analysis highlights that while programs that promote production of certain crops may ensure food security in the short-term, the long-term implications of these dynamics need careful evaluation.
NASA Astrophysics Data System (ADS)
Poyda, Arne; Wizemann, Hans-Dieter; Ingwersen, Joachim; Wulfmeyer, Volker; Streck, Thilo
2017-04-01
The impact of agricultural land use on soil organic carbon (SOC) dynamics has been widely studied in the past few decades, particularly in context of the SOC forcing or mitigation potential of global climate change. Grassland utilization can increase or maintain SOC stocks. Arable cropping tends to decrease SOC stocks, at least for some time after land use change (SMITH, 2008). In the long run, it can be assumed that SOC reaches a steady state where the production of roots and aboveground crop residues and possibly organic fertilization level out soil respiration. To study the effects of crop type, year and regional site conditions on CO2 exchange and C budgets of arable cropping systems in Southwest Germany, eddy covariance measurements were conducted on a total of six sites in the two climatically contrasting regions of Kraichgau and Swabian Alb since 2009. Main crops were winter wheat, silage maize and winter rapeseed but also winter barley, summer barley and spelt were cultivated on the Swabian Alb sites. Cover crops were grown between winter and summer crops on all sites. Net ecosystem exchange (NEE) data were gap-filled following REICHSTEIN et al. (2005) and partitioned into ecosystem respiration (RECO) and gross primary production (GPP) using seasonally differing temperature response functions of nighttime NEE. Furthermore, different approaches for filling long data gaps of several months in winter were evaluated. Considering C inputs by organic fertilizers and C removals by harvest, C budgets were calculated per site and year. First results indicate that the variability of NEE fluxes between different crops is much higher compared to the variability between different years of a certain crop. However, regional differences in soil and weather conditions significantly influence plant growth dynamics and thus CO2 exchange.
Sheridan, C; Depuydt, P; De Ro, M; Petit, C; Van Gysegem, E; Delaere, P; Dixon, M; Stasiak, M; Aciksöz, S B; Frossard, E; Paradiso, R; De Pascale, S; Ventorino, V; De Meyer, T; Sas, B; Geelen, D
2017-02-01
Plant growth promoting microorganisms (PGPMs) of the plant root zone microbiome have received limited attention in hydroponic cultivation systems. In the framework of a project aimed at the development of a biological life support system for manned missions in space, we investigated the effects of PGPMs on four common food crops (durum and bread wheat, potato and soybean) cultivated in recirculating hydroponic systems for a whole life cycle. Each crop was inoculated with a commercial PGPM mixture and the composition of the microbial communities associated with their root rhizosphere, rhizoplane/endosphere and with the recirculating nutrient solution was characterised through 16S- and ITS-targeted Illumina MiSeq sequencing. PGPM addition was shown to induce changes in the composition of these communities, though these changes varied both between crops and over time. Microbial communities of PGPM-treated plants were shown to be more stable over time. Though additional development is required, this study highlights the potential benefits that PGPMs may confer to plants grown in hydroponic systems, particularly when cultivated in extreme environments such as space.
An Integrated Biogeochemical and Biophysical Analysis of Bioenergy Crops
NASA Astrophysics Data System (ADS)
Liang, M.; Song, Y.; Barman, R.; Jain, A. K.
2010-12-01
Bioenergy crops are becoming increasingly important with growing concerns about the energy demand and climate change and the need to replace fossil fuels with carbon-neutral renewable sources of energy. The transition to a biofuel-based energy supply raises many questions such as: how and where to grow energy crops, what will be the impacts of growing large scale biofuel crops on climate system, the hydrological cycle and soil biogeochemistry. We are developing and applying an integrated system modeling framework to investigate the biophysical, physiological, and biogeochemical systems governing important processes that regulate crop growth such as water, energy and nutrient cycles. The framework has a two-big-leaf canopy scheme for photosynthesis, stomatal conductance, leaf temperature and energy fluxes. The soil/snow hydrology consists of 10 layers for soil and up to 5 layers for snow. The biogeochemistry component explicitly accounts for coupled carbon and nitrogen dynamics. The feedstocks currently considered include corn stover, Miscanthus and switchgrass. The parameters used for simulation of each crop have been calibrated using field experimental data from the US. The use of this modeling capability will be demonstrated through its applications to study the environmental effects (through changes in albedo and evapotranspiration) of biofuel production as well as the effective management practice in the United States.
NASA Astrophysics Data System (ADS)
Wagner, M.; Wang, M.; Miguez-Macho, G.; Miller, J. N.; Bagley, J. E.; Bernacchi, C.; Georgescu, M.
2016-12-01
Perennial bioenergy crops, such as switchgrass and miscanthus, have been posed as a more sustainable energy pathway relative to annual bioenergy crops due to their reduced carbon footprint and ability to grow on abandoned and degraded land, thereby, avoiding competition with food crops. Previous studies that replaced annual bioenergy crops with perennial crops noted regional cooling associated with enhanced ET due to their deeper rooting systems extracting deeper soil moisture. This study provides a more realistic assessment by (1) analyzing perennial bioenergy expansion only in suitable abandoned and degraded farmlands, and (2) using field scale measurements of albedo in conjunction with known vegetation fraction and leaf area index (LAI) values. High-resolution (2 km grid spacing) simulations were performed using a state-of-the-art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model system over the Southern Plains of the U.S., during a normal precipitation year (2007) and a drought year (2011). Our results show that perennial bioenergy crop expansion leads to regional cooling (1-2 oC), that is driven primarily by enhanced reflection of shortwave radiation, and secondarily, by enhanced ET. Perennial bioenergy crop expansion was also shown to mitigate drought impacts through moistening and cooling of the near-surface environment. These impacts, however, were reduced during the drought year as a result of differential environmental conditions, when compared to those of the normal cimate year. This study serves as a major step towards assessing the sustainability of perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.
NASA Astrophysics Data System (ADS)
van Walsum, P. E. V.; Supit, I.
2012-06-01
Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.
Designing Crop Simulation Web Service with Service Oriented Architecture Principle
NASA Astrophysics Data System (ADS)
Chinnachodteeranun, R.; Hung, N. D.; Honda, K.
2015-12-01
Crop simulation models are efficient tools for simulating crop growth processes and yield. Running crop models requires data from various sources as well as time-consuming data processing, such as data quality checking and data formatting, before those data can be inputted to the model. It makes the use of crop modeling limited only to crop modelers. We aim to make running crop models convenient for various users so that the utilization of crop models will be expanded, which will directly improve agricultural applications. As the first step, we had developed a prototype that runs DSSAT on Web called as Tomorrow's Rice (v. 1). It predicts rice yields based on a planting date, rice's variety and soil characteristics using DSSAT crop model. A user only needs to select a planting location on the Web GUI then the system queried historical weather data from available sources and expected yield is returned. Currently, we are working on weather data connection via Sensor Observation Service (SOS) interface defined by Open Geospatial Consortium (OGC). Weather data can be automatically connected to a weather generator for generating weather scenarios for running the crop model. In order to expand these services further, we are designing a web service framework consisting of layers of web services to support compositions and executions for running crop simulations. This framework allows a third party application to call and cascade each service as it needs for data preparation and running DSSAT model using a dynamic web service mechanism. The framework has a module to manage data format conversion, which means users do not need to spend their time curating the data inputs. Dynamic linking of data sources and services are implemented using the Service Component Architecture (SCA). This agriculture web service platform demonstrates interoperability of weather data using SOS interface, convenient connections between weather data sources and weather generator, and connecting various services for running crop models for decision support.
Deep soil layer is fundamental for evaluating carbon accumulation in agroecosystems
NASA Astrophysics Data System (ADS)
Dal Ferro, Nicola; Morari, Francesco; Simonetti, Gianluca; Polese, Riccardo; Berti, Antonio
2015-04-01
Soil organic carbon (SOC) is essential to secure key ecosystem services such as the provision of food and other biomass production, the filtering, buffering and transformation capacity and the climate regulation. It has been estimated that approximately 57% of the globally emitted C (8.7 Gt y-1) to the atmosphere is adsorbed by biospheric C pools, ascertaining the potential soil C sink capacity of managed ecosystems at 55 to 78 Gt, of which only 50 to 66% attainable. Therefore it is essential the full knowledge of soil management practices that can affect SOC dynamics and, in turn, climate change. Several studies focussed on the evaluation of the best cropping management practices to accumulate C in the soil profile. Nevertheless, in most cases soil analyses were made in the topsoil (generally in the 0-30 cm layer), ignoring the effect of C translocation in the deeper soil profile as a result of tillage practices, crop root deepening etc. In this context, in a long-term experiment established in the early 1960s, we quantified the SOC accumulation within the soil profile (0-90 cm) and evaluate the effects of different cropping system on SOC dynamics. The experiment is located at the experimental farm of the University of Padova, in northeastern Italy. The trial compares four rotations with three levels of mineral fertilisation and with or without organic fertilisation. The rotations considered are: continuous crops (grain maize, forage maize, winter wheat and permanent meadow); two-year (maize-wheat); four-year (sugarbeet, soybean, wheat, maize) and six-year (maize, sugarbeet, maize, wheat, alfalfa, alfalfa) with different levels of mineral, organic and mixed fertilisations. Crops with superficially developed rooting systems (e.g. permanent meadow) highly increased SOC only in the topsoil. This effect was enhanced by the contribution of organic amendment-C. Root-derived carbon played a pivotal role also in the deepest soil profile (60-90 cm) by increasing the SOC translocation. Considering the whole profile, the highest C accumulation was observed in cropping systems with high biomass production and deep rooting systems. Results indicated that for estimating the effects of cropping systems and agricultural practices on C accumulation, analyses in the topsoil can be misleading and it is necessary to consider the whole profile.
Crop rotations and poultry litter impact dynamic soil chemical properties and soil biota long-term
USDA-ARS?s Scientific Manuscript database
Dynamic soil physiochemical interactions with conservation agricultural practices and soil biota are largely unknown. Therefore, this study aims to quantify long-term (12-yr) impacts of cover crops, poultry litter, crop rotations, and conservation tillage and their interactions on soil physiochemica...
Mapping and monitoring of crop intensity, calendar and irrigation using multi-temporal MODIS data
NASA Astrophysics Data System (ADS)
Xiao, X.; Boes, S.; Mulukutla, G.; Proussevitch, A.; Routhier, M.
2005-12-01
Agriculture is the most extensive land use and water use on the Earth. Because of the diverse range of natural environments and human needs, agriculture is also the most complicated land use and water use system, which poses an enormous challenge to the scientific community, the public and decision-makers. Updated and geo-referenced information on crop intensity (number of crops per year), calendar (planting date, harvesting date) and irrigation is critically needed to better understand the impacts of agriculture on biogeochemical cycles (e.g., carbon, nitrogen, trace gases), water and climate dynamics. Here we present an effort to develop a novel approach for mapping and monitoring crop intensity, calendar and irrigation, using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) image data. Our algorithm employed three vegetation indices that are sensitive to the seasonal dynamics of leaf area index, light absorption by leaf chlorophyll and land surface water content. Our objective is to generate geospatial databases of crop intensity, calendar and irrigation at 500-m spatial resolution and at 8-day temporal resolution. In this presentation, we report a preliminary geospatial dataset of paddy rice crop intensity, calendar and irrigation in Asia, which is developed from the 8-day composite images of MODIS in 2002. The resultant dataset could be used in many applications, including hydrological and climate modeling.
NASA Astrophysics Data System (ADS)
Roger-Estrade, Jean; Boizard, Hubert; Peigné, Josephine; Sasal, Maria Carolina; Guimaraes, Rachel; Piron, Denis; Tomis, Vincent; Vian, Jean-François; Cadoux, Stephane; Ralisch, Ricardo; Filho, Tavares; Heddadj, Djilali; de Battista, Juan; Duparque, Annie
2016-04-01
In France, agronomists have studied the effects of cropping systems on soil structure, using a field method based on a visual description of soil structure. The "profil cultural" method (Manichon and Gautronneau, 1987) has been designed to perform a field diagnostic of the effects of tillage and compaction on soil structure dynamics. This method is of great use to agronomists improving crop management for a better preservation of soil structure. However, this method was developed and mainly used in conventional tillage systems, with ploughing. As several forms of reduced, minimum and no tillage systems are expanding in many parts of the world, it is necessary to re-evaluate the ability of this method to describe and interpret soil macrostructure in unploughed situations. In unploughed fields, soil structure dynamics of untilled layers is mainly driven by compaction and regeneration by natural agents (climatic conditions, root growth and macrofauna) and it is of major importance to evaluate the importance of these natural processes on soil structure regeneration. These concerns have led us to adapt the standard method and to propose amendments based on a series of field observations and experimental work in different situations of cropping systems, soil types and climatic conditions. We improved the description of crack type and we introduced an index of biological activity, based on the visual examination of clods. To test the improved method, a comparison with the reference method was carried out and the ability of the "profil cultural" method to make a diagnosis was tested on five experiments in France, Brazil and Argentina. Using the improved method, the impact of cropping systems on soil functioning was better assessed when natural processes were integrated into the description.
NASA Astrophysics Data System (ADS)
Jacquemin, Ingrid; Henrot, Alexandra-Jane; Fontaine, Corentin M.; Dendoncker, Nicolas; Beckers, Veronique; Debusscher, Bos; Tychon, Bernard; Hambuckers, Alain; François, Louis
2016-04-01
Dynamic vegetation models (DVM) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil, to study the role of the vegetation in the carbon cycle. These models are now directly coupled with climate models in order to evaluate feedbacks between vegetation and climate. But DVM characteristics allow numerous other applications, leading to amelioration of some of their modules (e.g., evaluating sensitivity of the hydrological module to land surface changes) and developments (e.g., coupling with other models like agent-based models), to be used in ecosystem management and land use planning studies. It is in this dynamic context about DVMs that we have adapted the CARAIB (CARbon Assimilation In the Biosphere) model. One of the main improvements is the implementation of a crop module, allowing the assessment of climate change impacts on crop yields. We try to validate this module at different scales: - from the plot level, with the use of eddy-covariance data from agricultural sites in the FLUXNET network, such as Lonzée (Belgium) or other Western European sites (Grignon, Dijkgraaf,…), - to the country level, for which we compare the crop yield calculated by CARAIB to the crop yield statistics for Belgium and for different agricultural regions of the country. Another challenge for the CARAIB DVM was to deal with the landscape dynamics, which is not directly possible due to the lack of consideration of anthropogenic factors in the system. In the framework of the VOTES and the MASC projects, CARAIB is coupled with an agent-based model (ABM), representing the societal component of the system. This coupled module allows the use of climate and socio-economic scenarios, particularly interesting for studies which aim at ensuring a sustainable approach. This module has particularly been exploited in the VOTES project, where the objective was to provide a social, biophysical and economic assessment of the ecosystem services in four municipalities under urban pressure in the center of Belgium. The biophysical valuation was carried out with the coupled module, allowing a quantitative evaluation of key ecosystem services as a function of three climatic and socio-economic scenarios.
Production versus environmental impact trade-offs for Swiss cropping systems: a model-based approach
NASA Astrophysics Data System (ADS)
Necpalova, Magdalena; Lee, Juhwan; Six, Johan
2017-04-01
There is a growing need to improve sustainability of agricultural systems. The key focus remains on optimizing current production systems in order to deliver food security at low environmental costs. It is therefore essential to identify and evaluate agricultural management practices for their potential to maintain or increase productivity and mitigate climate change and N pollution. Previous research on Swiss cropping systems has been concentrated on increasing crop productivity and soil fertility. Thus, relatively little is known about management effects on net soil greenhouse gas (GHG) emissions and environmental N losses in the long-term. The aim of this study was to extrapolate findings from Swiss long-term field experiments and to evaluate the system-level sustainability of a wide range of cropping systems under conditions beyond field experimentation by comparing their crop productivity and impacts on soil carbon, net soil GHG emissions, NO3 leaching and soil N balance over 30 years. The DayCent model was previously parameterized for common Swiss crops and crop-specific management practices and evaluated for productivity, soil carbon dynamics and N2O emissions from Swiss cropping systems. Based on a prediction uncertainty criterion for crop productivity and soil carbon (rRMSE<0.3), in total 39 cropping systems were selected. Each system was evaluated under soil and climate conditions representative of Therwil, Frick, Reckenholz and Changins sites with four replications. Soil inputs were sampled from normal probability distributions defined by available site-specific data using the Latin hypercube sampling method. Net soil GHG emissions were derived from changes in soil carbon, N2O emissions and CH4 oxidation and the annual net global warming potential (GWP) was calculated using IPCC (2014). For statistical analyses, the systems were grouped into the following categories: (a) farming system: organic (ORG), integrated (IN) and mineral (MIN); (b) tillage: conventional (CT), reduced (RT) and no-till (NT); (c) cover cropping: no cover cropping (NCC), winter cover cropping (CC) and winter green manuring (GM). The productivity of Swiss cropping systems was mainly driven by total N inputs to the systems. The GWP of systems ranged from -450 to 1309 kg CO2 eq ha-1 yr-1. All studied systems, except for ORG-RT-GM systems, acted as a source of net soil GHG emissions with the relative contribution of soil N2O emissions to GWP of more than 60%. The GWP of systems with CT decreased consistently with increasing use of organic manures (MIN>IN>ORG). NT relative to RT management showed to be more effective in reducing GWP from MIN systems due to reduced soil N2O emissions and positive effects on soil C sequestration. GM relative to CC management was shown to be more effective in mitigating NO3 leaching and overall N losses from MIN systems; particularly in combination with NT management. GM management also increased soil N balance of MIN and ORG systems relative to CC management, which caused an additional N removal through CC harvest. Our results suggest that there is a substantial potential for improvement and optimizing the sustainability of Swiss cropping systems across sites especially in the context of climate change mitigation and adaptation.
Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA
NASA Astrophysics Data System (ADS)
Fraisse, C.
2014-12-01
AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.
Dynamic control of photosynthetic photon flux for lettuce production in CELSS
NASA Technical Reports Server (NTRS)
Chun, C.; Mitchell, C. A.
1996-01-01
A new dynamic control of photosynthetic photon flux (PPF) was tested using lettuce canopies growing in the Minitron II plant-growth/canopy gas-exchange system. Canopy photosynthetic rates (Pn) were measured in real time and fedback for further environment control. Pn can be manipulated by changing PPF, which is a good environmental parameter for dynamic control of crop production in a Controlled Ecological Life-Support Systems CELSS. Decision making that combines empirical mathematical models with rule sets developed from recent experimental data was tested. With comparable yield indices and potential for energy savings, dynamic control strategies will contribute greatly to the sustainability of space-deployed CELSS.
Understanding Arsenic Dynamics in Agronomic Systems to Predict and Prevent Uptake by Crop Plants
This review is on arsenic in agronomic systems, and covers processes that influence the entry of arsenic into the human food supply. The scope is from sources of arsenic (natural and anthropogenic) in soils, biogeochemical and rhizosphere processes that control arsenic speciatio...
Biological aspects of weed dynamics in no-till systems
USDA-ARS?s Scientific Manuscript database
Scientists and producers in the Eurasian steppe are interested in no-till crop production, but are concerned that, without tillage, weed density will escalate in croplands. In the United States, producers have used no-till systems for several decades and weed density has not increased. In this pap...
Regional simulation of soil nitrogen dynamics and balance in Swiss cropping systems
NASA Astrophysics Data System (ADS)
Lee, Juhwan; Necpalova, Magdalena; Six, Johan
2017-04-01
We evaluated the regional-scale potential of various crop and soil management practices to reduce the dependency of crop N demand on external N inputs and N losses to the environment. The estimates of soil N balance were simulated and compared under alternative and conventional crop production across all Swiss cropland. Alternative practices were all combinations of organic fertilization, reduced tillage and winter cover cropping. Using the DayCent model, we simulated changes in crop N yields as well as the contribution of inputs and outputs to soil N balance by alternative practices, which was complemented with corresponding measurements from available long-term field experiments and site-level simulations. In addition, the effects of reducing (between 0% and 80% of recommended application rates) or increasing chemical fertilizer input rates (between 120% and 300% of recommended application rates) on system-level N dynamics were also simulated. Modeled yields at recommended N rates were only 37-87% of the maximum yield potential across common Swiss crops, and crop productivity were sensitive to the level of external N inputs, except for grass-clover mixture, soybean and peas. Overall, differences in soil N input and output decreased or increased proportionally with changing the amount of N input only from the recommended rate. As a result, there was no additional difference in soil N balance in response to N application rates. Nitrate leaching accounted for 40-81% of total N output differences, while up to 47% of total N output occurred through harvest and straw removal. Regardless of crops, yield potential became insensitive to high N rates. Differences in N2O and N2 emissions slightly increased with increasing N inputs, in which each gas was only responsible for about 1% of changes in total N output. Overall, there was a positive soil N balance under alternative practices. Particularly, considerable improvement in soil N balance was expected when slowly decomposed organic fertilizer was used in combination with cover cropping and/or reduced tillage. However, the increase in soil N balance was due to the decreases in harvested yield and nitrate leaching under these organic cropping based practices. Instead, the use of fast decomposed organic matter with cover cropping could be considered to avoid any yield penalty while decreasing nitrate leaching, hence reducing total N output. In order to effectively reduce N losses from soils, approaches to utilize multiple alternative options should be taken into account at the regional scale.
NASA Astrophysics Data System (ADS)
Maddalena, D. M.; L'Heureux, J.; Hoffman, F. M.
2017-12-01
Fruit and Tree Nut production in the US averaged 14% of total annual production, or roughly $28 billion in total revenue for the most recent 5 year period (2011 - 2015). The success of these crops is highly dependent on environmental conditions. Cold snaps before winter dormancy, early frosts in spring, and lack of sufficient chilling hours can reduce productivity, inflict wood damage, and lead to economic loss. Climate change can increase the likelihood of these threats and may have long-term implications for the areas where these crops are grown due to the migration of ecoregions as climate patters shift. We delineate ecoregions using multi-attribute spatio-temporal clustering and calculate chilling unit accumulation under past, present, and future climate scenarios using measured and modeled data. These results are then compared to current agroregions in the US to calculate risk dynamics, potential economic loss, and to map future agroregion scenarios. Our results offer considerations for food system sustainability under a shifting climate.
NASA Astrophysics Data System (ADS)
Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.
2015-06-01
We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.
A STELLA model to estimate water and nitrogen dynamics in a short-rotation woody crop plantation
Ying Ouyang; Jiaen Zhang; Theodor D. Leininger; Brent R. Frey
2015-01-01
Although short-rotation woody crop biomass production technology has demonstrated a promising potential to supply feedstocks for bioenergy production, the water and nutrient processes in the woody crop planation ecosystem are poorly understood. In this study, a computer model was developed to estimate the dynamics of water and nitrogen (N) species (e.g., NH4...
Electronic Dimmable Ballasts for High-Intensity Discharge Sodium Vapor and Metal Halide Lamps
NASA Technical Reports Server (NTRS)
Boulanger, Richard
2002-01-01
Two types of high-intensity discharge lamps were tested using dimmable ballasts. The main purpose for evaluating this lighting system was to determine its efficacy for saving power. Whereas previous variable level lighting systems for HID lamps in Advanced Life Support applications were adjustable in two or three steps using capacitive switching, this system allows for continuously adjustable lamp output. This type of lighting system when used as part of an Advanced Life Support biomass production system would provide only the amount of light energy a crop needed at any particular point in its growth cycle. Since most of the equivalent system mass in an ALS system is from the light energy required to grow the crops, controlling that light energy dynamically over a continuous range of operation would dramatically reduce the power consumption and reduce system mass.
Bosch, J; Bosch, J; Kemp, W P
2002-02-01
The development of a bee species as a new crop pollinator starts with the identification of a pollination-limited crop production deficit and the selection of one or more candidate pollinator species. The process continues with a series of studies on the developmental biology, pollinating efficacy, nesting behaviour, preference for different nesting substrates, and population dynamics of the candidate pollinator. Parallel studies investigate the biology of parasites, predators and pathogens. The information gained in these studies is combined with information on the reproductive biology of the crop to design a management system. Complete management systems should provide guidelines on rearing and releasing methods, bee densities required for adequate pollination, nesting materials, and control against parasites, predators and pathogens. Management systems should also provide methods to ensure a reliable pollinator supply. Pilot tests on a commercial scale are then conducted to test and eventually refine the management system. The process culminates with the delivery of a viable system to manage and sustain the new pollinator on a commercial scale. The process is illustrated by the development of three mason bees, Osmia cornifrons (Radoszkowski), O. lignaria Say and O. cornuta (Latreille) as orchard pollinators in Japan, the USA and Europe, respectively.
USDA-ARS?s Scientific Manuscript database
Nutrient loss from agricultural fields is one of the main factors influencing surface- and ground-water quality. Typical fertilizer nitrogen (N) consumption rates in vegetable production systems and horticultural crops in Puerto Rico, fluctuate between 112 to 253 kg N/ha. Nitrogen use efficiency of ...
Calibration of a crop model to irrigated water use using a genetic algorithm
USDA-ARS?s Scientific Manuscript database
Near-term consumption of groundwater for irrigated agriculture in the High Plains Aquifer supports a dynamic bio-socio-economic system, all parts of which will be impacted by a future transition to sustainable usage that matches natural recharge rates. Plants are the foundation of this system and so...
NASA Astrophysics Data System (ADS)
Henson, W.; Baillie, M. N.; Martin, D.
2017-12-01
Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and precision of hydrologic decision models. Ultimately, further refinement to the parcel level will completely capture the changing topology of agricultural land use.
A high-throughput method for GMO multi-detection using a microfluidic dynamic array.
Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J
2014-02-01
The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.
NASA Astrophysics Data System (ADS)
Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.
2015-12-01
Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.
Linking crop yield anomalies to large-scale atmospheric circulation in Europe.
Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J
2017-06-15
Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melintescu, A.; Galeriu, D.; Diabate, S.
2015-03-15
The processes involved in tritium transfer in crops are complex and regulated by many feedback mechanisms. A full mechanistic model is difficult to develop due to the complexity of the processes involved in tritium transfer and environmental conditions. First, a review of existing models (ORYZA2000, CROPTRIT and WOFOST) presenting their features and limits, is made. Secondly, the preparatory steps for a robust model are discussed, considering the role of dry matter and photosynthesis contribution to the OBT (Organically Bound Tritium) dynamics in crops.
NASA Astrophysics Data System (ADS)
Autovino, Dario; Negm, Amro; Rallo, Giovanni; Provenzano, Giuseppe
2016-04-01
In Mediterranean countries characterized by limited water resources for agricultural and societal sectors, irrigation management plays a major role to improve water use efficiency at farm scale, mainly where irrigation systems are correctly designed to guarantee a suitable application efficiency and the uniform water distribution throughout the field. In the last two decades, physically-based agro-hydrological models have been developed to simulate mass and energy exchange processes in the soil-plant-atmosphere (SPA) system. Mechanistic models like HYDRUS 2D/3D (Šimunek et al., 2011) have been proposed to simulate all the components of water balance, including actual crop transpiration fluxes estimated according to a soil potential-dependent sink term. Even though the suitability of these models to simulate the temporal dynamics of soil and crop water status has been reported in the literature for different horticultural crops, a few researches have been considering arboreal crops where the higher gradients of root water uptake are the combination between the localized irrigation supply and the three dimensional root system distribution. The main objective of the paper was to assess the performance of HYDRUS-2D model to evaluate soil water contents and transpiration fluxes of an olive orchard irrigated with two different water distribution systems. Experiments were carried out in Castelvetrano (Sicily) during irrigation seasons 2011 and 2012, in a commercial farm specialized in the production of table olives (Olea europaea L., var. Nocellara del Belice), representing the typical variety of the surrounding area. During the first season, irrigation water was provided by a single lateral placed along the plant row with four emitters per plant (ordinary irrigation), whereas during the second season a grid of emitters laid on the soil was installed in order to irrigate the whole soil surface around the selected trees. The model performance was assessed based on the comparison between measured and simulated soil water content and actual transpiration fluxes, under the hypothesis to neglect the contribute of the tree capacitance. Moreover, two different crop water stress functions and in particular the linear model proposed by Feddes et al. (1978) and the S-shape model suggested by van Genuchten et al. (1987), were considered. The result of the study evidenced that for the investigated crop and under the examined conditions, HYDRUS-2D model reproduces fairly well the dynamic of soil water contents at different distances from the emitters (RMSE<0.09 cm3 cm-3) and actual crop transpiration fluxes (RMSE<0.11 mm d-1), whose estimations can be slightly improved by assuming a S-shape crop water stress function. Key-words: Olive tree, HYDRUS-2D, Soil water content, Actual transpiration fluxes
Modeling carbon dynamics and social drivers of bioenergy agroecosystems
NASA Astrophysics Data System (ADS)
Hunt, Natalie D.
Meeting society's energy needs through bioenergy feedstock production presents a significant and urgent challenge, as it can aid in achieving energy independence goals and mitigating climate change. With federal biofuel production standards to be met within the next decade, and with no commercial scale production or markets currently in place, many questions regarding the sustainability and social feasibility of bioenergy still persist. Clarifying these uncertainties requires the incorporation of biogeochemical, biophysical, and socioeconomic modeling tools. Chapter 2 validated the biogeochemical cycling model AGRO-BGC by comparing model estimates with empirical observations from corn and perennial C4 grass systems across Wisconsin and Illinois. AGRO-BGC, in its first application to an annual cropping system, was found to be a robust model for simulating carbon dynamics of an annual cropping system. Chapter 3 investigated the long-term implications of bioenergy feedstock harvest on soil productivity and erosion in annual corn and perennial switchgrass agroecosystems using AGRO-BGC and the soil erosion model RUSLE2. Modeling environments included biophysical landscape characteristics and management practices of bioenergy feedstock production systems. This study found that intensifying aboveground residue harvest reduces soil productivity over time, and the magnitude of these losses is greater in corn than in switchgrass systems. Results of this study will aid in the design of sustainable bioenergy feedstock management practices. Chapter 4 provided evidence that combining biophysical crop canopy characteristics with satellite-derived vegetation indices offers suitable estimates of crop canopy phenology for corn and soybeans in Southwest Wisconsin farms. LANDSAT based vegetation indices, when combined with a light use efficiency model, provide yield estimates in agreement with farmer reports, providing an efficient and accurate means of estimating crop yields from satellite data. The most important stakeholder in bioenergy sustainability and feasibility research is the farmer. Chapter 5 identified and measured the influence of bioenergy feedstock choice drivers using logistic regression choice models constructed from survey and geospatial data. The strongest choice drivers among farmers willing to participate in a proposed bioenergy feedstock production program included socioeconomic, biophysical, and environmental attitudes. Outcomes of this research will be useful in designing further bioenergy policy and economic incentives.
Coupled Crop/Hydrology Model to Estimate Expanded Irrigation Impact on Water Resources
NASA Astrophysics Data System (ADS)
Handyside, C. T.; Cruise, J.
2017-12-01
A coupled agricultural and hydrologic systems model is used to examine the environmental impact of irrigation in the Southeast. A gridded crop model for the Southeast is used to determine regional irrigation demand. This irrigation demand is used in a regional hydrologic model to determine the hydrologic impact of irrigation. For the Southeast to maintain/expand irrigated agricultural production and provide adaptation to climate change and climate variability it will require integrated agricultural and hydrologic system models that can calculate irrigation demand and the impact of the this demand on the river hydrology. These integrated models can be used as (1) historical tools to examine vulnerability of expanded irrigation to past climate extremes (2) future tools to examine the sustainability of expanded irrigation under future climate scenarios and (3) a real-time tool to allow dynamic water resource management. Such tools are necessary to assure stakeholders and the public that irrigation can be carried out in a sustainable manner. The system tools to be discussed include a gridded version of the crop modeling system (DSSAT). The gridded model is referred to as GriDSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model developed by the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service) (WaSSI). The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model includes all other competing uses of water. Examples of use the crop model coupled with the hydrologic model include historical analyses which show the change in hydrology as additional acres of irrigated land are added to water sheds. The first order change in hydrology is computed in terms of changes in the Water Availability Stress Index (WASSI) which is the ratio of water demand (irrigation, public water supply, industrial use, etc.) and water availability from the hydrologic model. Also, statistics such as the number of times certain WASSI thresholds are exceeded are calculated to show the impact of expanded irrigation during times of hydrologic drought and the coincident use of water by other sectors. Also, integrated downstream impacts of irrigation are also calculated through changes in flows through the whole river systems.
Observing Crop-Height Dynamics Using a UAV
NASA Astrophysics Data System (ADS)
Ziliani, M. G.; Parkes, S. D.; McCabe, M.
2017-12-01
Retrieval of vegetation height during a growing season is a key indicator for monitoring crop status, offering insight to the forecast yield relative to previous planting cycles. Improvement in Unmanned Aerial Vehicle (UAV) technologies, supported by advances in computer vision and photogrammetry software, has enabled retrieval of crop heights with much higher spatial resolution and coverage. These methodologies retrieve a Digital Surface Map (DSM), which combine terrain and crop elements to obtain a Crop Surface Map (CSM). Here we describe an automated method for deriving high resolution CSMs from a DSM, using RGB imagery from a UAV platform. Importantly, the approach does not require the need for a digital terrain map (DTM). The method involves distinguishing between vegetation and bare-ground cover pixels, using vegetation index maps from the RGB orthomosaic derived from the same flight as the DSM. We show that the absolute crop height can be extracted to within several centimeters, exploiting the data captured from a single UAV flight. In addition, the method is applied across five surveys during a maize growing cycle and compared against a terrain map constructed from a baseline UAV survey undertaken prior to crop growth. Results show that the approach is able to reproduce the observed spatial variability of the crop height within the maize field throughout the duration of the growing season. This is particularly valuable since it may be employed to detect intra-field problems (i.e. fertilizer variability, inefficiency in the irrigation system, salinity etc.) at different stages of the season, from which remedial action can be initiated to mitigate against yield loss. The method also demonstrates that UAV imagery combined with commercial photogrammetry software can determine a CSM from a single flight without the requirement of a prior DTM. This, together with the dynamic crop height estimation, provide useful information with which to inform precision agricultural management at the local scale.
NASA Astrophysics Data System (ADS)
McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.
2016-12-01
A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.
Reed-Jones, Neiunna L.; Marine, Sasha Cahn; Everts, Kathryne L.
2016-01-01
Cover crops provide several ecosystem services, but their impact on enteric bacterial survival remains unexplored. The influence of cover cropping on foodborne pathogen indicator bacteria was assessed in five cover crop/green manure systems: cereal rye, hairy vetch, crimson clover, hairy vetch-rye and crimson clover-rye mixtures, and bare ground. Cover crop plots were inoculated with Escherichia coli and Listeria innocua in the fall of 2013 and 2014 and tilled into the soil in the spring to form green manure. Soil samples were collected and the bacteria enumerated. Time was a factor for all bacterial populations studied in all fields (P < 0.001). E. coli levels declined when soil temperatures dipped to <5°C and were detected only sporadically the following spring. L. innocua diminished somewhat but persisted, independently of season. In an organic field, the cover crop was a factor for E. coli in year 1 (P = 0.004) and for L. innocua in year 2 (P = 0.011). In year 1, E. coli levels were highest in the rye and hairy vetch-rye plots. In year 2, L. innocua levels were higher in hairy vetch-rye (P = 0.01) and hairy vetch (P = 0.03) plots than in the rye plot. Bacterial populations grew (P < 0.05) or remained the same 4 weeks after green manure incorporation, although initial reductions in L. innocua numbers were observed after tilling (P < 0.05). Green manure type was a factor only for L. innocua abundance in a transitional field (P < 0.05). Overall, the impacts of cover crops/green manures on bacterial population dynamics in soil varied, being influenced by bacterial species, time from inoculation, soil temperature, rainfall, and tillage; this reveals the need for long-term studies. PMID:26729724
Elia, Antonio; Conversa, Giulia
2015-01-01
Reduced water availability and environmental pollution caused by nitrogen (N) losses have increased the need for rational management of irrigation and N fertilization in horticultural systems. Decision support systems (DSS) could be powerful tools to assist farmers to improve irrigation and N fertilization efficiency. Currently, fertilization by drip irrigation system (fertigation) is used for many vegetable crops around the world. The paper illustrates the theoretical basis, the methodological approach and the structure of a DSS called GesCoN for fertigation management in open field vegetable crops. The DSS is based on daily water and N balance, considering the water lost by evapotranspiration (ET) and the N content in the aerial part of the crop (N uptake) as subtraction and the availability of water and N in the wet soil volume most effected by roots as the positive part. For the water balance, reference ET can be estimated using the Penman-Monteith (PM) or the Priestley-Taylor and Hargreaves models, specifically calibrated under local conditions. Both single or dual Kc approach can be used to calculate crop ET. Rain runoff and deep percolation are considered to calculate the effective rainfall. The soil volume most affected by the roots, the wet soil under emitters and their interactions are modeled. Crop growth is modeled by a non-linear logistic function on the basis of thermal time, but the model takes into account thermal and water stresses and allows an in-season calibration through a dynamic adaptation of the growth rate to the specific genetic and environmental conditions. N crop demand is related to DM accumulation by the N critical curve. N mineralization from soil organic matter is daily estimated. The DSS helps users to evaluate the daily amount of water and N fertilizer that has to be applied in order to fulfill the water and N-crop requirements to achieve the maximum potential yield, while reducing the risk of nitrate outflows.
NASA Astrophysics Data System (ADS)
Bhardwaj, A. K.; Hamilton, S. K.; van Dam, R. L.; Diker, K.; Basso, B.; Glbrc-Sustainability Thrust-4. 3 Biogeochemistry
2010-12-01
Root-zone soil moisture constitutes an important variable for hydrological and agronomic models. In agriculture, crop yields are directly related to soil moisture, levels that are most important in the root zone area of the soil. One of the most accurate in-situ methods that has established itself as a recognized standard around the world uses Time Domain Reflectometry (TDR) to determine volumetric water content of the soil. We used automated field-to-desk TDR based systems to monitor temporal (1-hr interval) soil moisture variability in 10 different bioenergy cropping systems at the Great Lakes Bioenergy Research Center’s (GLBRC) sustainability research site in south western Michigan, U.S.A. These crops range from high-diversity, low-input grass mixes to low-diversity, high-input crop monocultures. We equipped the 28 x 40 m vegetation plots with 30 cm long TDR probes at seven depths from 10 cm to 1.25 m below surface. The parent material at the site consists of coarse sandy glacial tills in which a soil with an approximately 50cm thick A-Bt horizon has developed. Additional equipment permanently installed for each system includes soil moisture access tubes, multi-depth temperature sensors, and multi-electrode resistivity arrays. The access tubes were monitored using a portable TDR system at bi-weekly intervals. 2D dipole-dipole electrical resistivity tomography (ERT) data are collected in 4-week intervals, while a subset of the electrodes is used for bi-hourly monitoring. The continuous scans (1 hr) provided us the real time changes in water content, replenishment and depletion, providing indications of water uptake by plant roots and potential seasonal water limitation of biomass accumulation. The results show significant seasonal variations between the crops and cropping systems. Significant relationships were observed between soil moisture stress, above-ground biomass and rooting characteristics. The overall goal of the study is to quantify the components of water balance, and identify water quality and water use implications of these cropping systems.Key Words
Multimodel ensembles of wheat growth: many models are better than one.
Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W; Rötter, Reimund P; Boote, Kenneth J; Ruane, Alex C; Thorburn, Peter J; Cammarano, Davide; Hatfield, Jerry L; Rosenzweig, Cynthia; Aggarwal, Pramod K; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richie; Grant, Robert F; Heng, Lee; Hooker, Josh; Hunt, Leslie A; Ingwersen, Joachim; Izaurralde, Roberto C; Kersebaum, Kurt Christian; Müller, Christoph; Kumar, Soora Naresh; Nendel, Claas; O'leary, Garry; Olesen, Jørgen E; Osborne, Tom M; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Semenov, Mikhail A; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; White, Jeffrey W; Wolf, Joost
2015-02-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. © 2014 John Wiley & Sons Ltd.
Multimodel Ensembles of Wheat Growth: More Models are Better than One
NASA Technical Reports Server (NTRS)
Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide;
2015-01-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
Multimodel Ensembles of Wheat Growth: Many Models are Better than One
NASA Technical Reports Server (NTRS)
Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alexander C.; Thorburn, Peter J.; Cammarano, Davide;
2015-01-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring
Ammad Uddin, Mohammad; Mansour, Ali; Le Jeune, Denis; Ayaz, Mohammad; Aggoune, el-Hadi M.
2018-01-01
In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use. PMID:29439496
UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring.
Uddin, Mohammad Ammad; Mansour, Ali; Jeune, Denis Le; Ayaz, Mohammad; Aggoune, El-Hadi M
2018-02-11
In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use.
Green and blue water demand from large-scale land acquisitions in Africa
Johansson, Emma Li; Fader, Marianela; Seaquist, Jonathan W.; Nicholas, Kimberly A.
2016-01-01
In the last decade, more than 22 million ha of land have been contracted to large-scale land acquisitions in Africa, leading to increased pressures, competition, and conflicts over freshwater resources. Currently, 3% of contracted land is in production, for which we model site-specific water demands to indicate where freshwater appropriation might pose high socioenvironmental challenges. We use the dynamic global vegetation model Lund–Potsdam–Jena managed Land to simulate green (precipitation stored in soils and consumed by plants through evapotranspiration) and blue (extracted from rivers, lakes, aquifers, and dams) water demand and crop yields for seven irrigation scenarios, and compare these data with two baseline scenarios of staple crops representing previous water demand. We find that most land acquisitions are planted with crops that demand large volumes of water (>9,000 m3⋅ha−1) like sugarcane, jatropha, and eucalyptus, and that staple crops have lower water requirements (<7,000 m3⋅ha−1). Blue water demand varies with irrigation system, crop choice, and climate. Even if the most efficient irrigation systems were implemented, 18% of the land acquisitions, totaling 91,000 ha, would still require more than 50% of water from blue water sources. These hotspots indicate areas at risk for transgressing regional constraints for freshwater use as a result of overconsumption of blue water, where socioenvironmental systems might face increased conflicts and tensions over water resources. PMID:27671634
A process-based agricultural model for the irrigated agriculture sector in Alberta, Canada
NASA Astrophysics Data System (ADS)
Ammar, M. E.; Davies, E. G.
2015-12-01
Connections between land and water, irrigation, agricultural productivity and profitability, policy alternatives, and climate change and variability are complex, poorly understood, and unpredictable. Policy assessment for agriculture presents a large potential for development of broad-based simulation models that can aid assessment and quantification of policy alternatives over longer temporal scales. The Canadian irrigated agriculture sector is concentrated in Alberta, where it represents two thirds of the irrigated land-base in Canada and is the largest consumer of surface water. Despite interest in irrigation expansion, its potential in Alberta is uncertain given a constrained water supply, significant social and economic development and increasing demands for both land and water, and climate change. This paper therefore introduces a system dynamics model as a decision support tool to provide insights into irrigation expansion in Alberta, and into trade-offs and risks associated with that expansion. It is intended to be used by a wide variety of users including researchers, policy analysts and planners, and irrigation managers. A process-based cropping system approach is at the core of the model and uses a water-driven crop growth mechanism described by AquaCrop. The tool goes beyond a representation of crop phenology and cropping systems by permitting assessment and quantification of the broader, long-term consequences of agricultural policies for Alberta's irrigation sector. It also encourages collaboration and provides a degree of transparency that gives confidence in simulation results. The paper focuses on the agricultural component of the systems model, describing the process involved; soil water and nutrients balance, crop growth, and water, temperature, salinity, and nutrients stresses, and how other disciplines can be integrated to account for the effects of interactions and feedbacks in the whole system. In later stages, other components such as livestock production systems and agricultural production economics will be integrated to the agricultural model to make the systems tool. It will capture feedback loops, time delays, and the nonlinearities of the system. Moreover, the model is designed for quick reconfiguration to different regions given parametrized crop data.
NASA Astrophysics Data System (ADS)
Koo, J.; Wood, S.; Cenacchi, N.; Fisher, M.; Cox, C.
2012-12-01
HarvestChoice (harvestchoice.org) generates knowledge products to guide strategic investments to improve the productivity and profitability of smallholder farming systems in sub-Saharan Africa (SSA). A keynote component of the HarvestChoice analytical framework is a grid-based overlay of SSA - a cropping simulation platform powered by process-based, crop models. Calibrated around the best available representation of cropping production systems in SSA, the simulation platform engages the DSSAT Crop Systems Model with the CENTURY Soil Organic Matter model (DSSAT-CENTURY) and provides a virtual experimentation module with which to explore the impact of a range of technological, managerial and environmental metrics on future crop productivity and profitability, as well as input use. For each of 5 (or 30) arc-minute grid cells in SSA, a stack of model input underlies it: datasets that cover soil properties and fertility, historic and future climate scenarios and farmers' management practices; all compiled from analyses of existing global and regional databases and consultations with other CGIAR centers. Running a simulation model is not always straightforward, especially when certain cropping systems or management practices are not even practiced by resource-poor farmers yet (e.g., precision agriculture) or they were never included in the existing simulation framework (e.g., water harvesting). In such cases, we used DSSAT-CENTURY as a function to iteratively estimate relative responses of cropping systems to technology-driven changes in water and nutrient balances compared to zero-adoption by farmers, while adjusting model input parameters to best mimic farmers' implementation of technologies in the field. We then fed the results of the simulation into to the economic and food trade model framework, IMPACT, to assess the potential implications on future food security. The outputs of the overall simulation analyses are packaged as a web-accessible database and published on the web with an interface that allows users to explore the simulation results in each country with user-defined baseline and what-if scenarios. The results are dynamically presented on maps, charts, and tables. This paper discusses the development of the simulation platform and its underlying data layers, a case study that assessed the role of potential crop management technology development, and the development of a web-based application that visualizes the simulation results.
Colbach, Nathalie; Darmency, Henri; Fernier, Alice; Granger, Sylvie; Le Corre, Valérie; Messéan, Antoine
2017-05-01
Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FLORSYS; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.
Global Estimates of Trace Gas Fluxes Affected by Land Use Change and Irrigation of Major Crops
NASA Astrophysics Data System (ADS)
Ojima, D. S.; del Grosso, S.; Parton, W. J.; Keough, C.
2005-12-01
Cropland conversions have altered many fertile regions of the earth and have modified the biogeochemical and hydrological cycling in these regions. These croplands are significant sources of N trace gas emissions however, the extent of changing trace gas emission due to land management changes and irrigation need further analysis. We use the DAYCENT biogeochemical model which is a daily time step version of the CENTURY model. DAYCENT simulates fluxes of N2O between croplands and the atmosphere for major crop types, and allows for a dynamic representation of GHG fluxes that accounts for environmental conditions, soil characteristics, climate, specific crop qualities, and fertilizer and irrigation management practices. DAYCENT is applied to all world cropland regions. Global datasets of weather, soils, native vegetation and cropping fractions were mapped to an approximate 2° x 2° resolution. Non-spatial data (such as planting date and fertilizer application rates) were assigned as point values for each region (i.e. country), and were assumed to be similar within crop types across the region. Three major crops were simulated (corn, wheat and soybeans) under both irrigated and non-irrigated conditions. Results indicate that N2O emission for maize and soy bean increase between 3 to 10%, where as wheat emission decline by about 1% when irrigated systems are compared to non-irrigated systems.
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
Preceding crop affects soybean aphid abundance and predator-prey dynamics in soybean
USDA-ARS?s Scientific Manuscript database
Crop rotations alter the soil environment and physiology of the subsequent crop in ways that may affect herbivore abundance. Soybean aphids are a consistent pest of soybean throughout North America, but little work has focused on how preceding crops may affect aphid populations. In a replicated expe...
Aubertot, Jean-Noël; Robin, Marie-Hélène
2013-01-01
The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop. PMID:24019908
Aubertot, Jean-Noël; Robin, Marie-Hélène
2013-01-01
The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop.
Estimating Biofuel Feedstock Water Footprints Using System Dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Inman, Daniel; Warner, Ethan; Stright, Dana
Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of manymore » feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user-friendly interface for on-demand, spatially explicit, water use scenario analysis for many US agricultural crops. Built-in controls permit users to quickly make modifications to the model assumptions, such as those affecting yield, and to see the implications of those results in real time. BioSpatial H2O's dynamic capabilities and adjustable climate data allow for analyses of water use and management scenarios to inform current and potential future bioenergy policies. The model could also be adapted for scenario analysis of alternative climatic conditions and comparison of multiple crops. The results of such an analysis would help identify risks associated with water use competition among feedstocks in certain regions. Results could also inform research and development efforts that seek to reduce water-related risks of biofuel pathways.« less
Dynamic drought risk assessment using crop model and remote sensing techniques
NASA Astrophysics Data System (ADS)
Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.
2017-02-01
Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.
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.
Qiu, Linjing; Hao, Mingde; Wu, Yiping
2017-01-15
Although many studies have been conducted on crop yield in rain-fed agriculture, the possible impacts of climate change on the carbon (C) dynamics of rain-fed rotation systems, particularly their direction and magnitude at the long-term scale, are still poorly understood. In this study, the sensitivity of C dynamics of a typical rotation system to elevated CO 2 and changed temperature and precipitation were first tested using the CENTURY model, based on data collected from a 30-year field experiment of a corn-wheat-wheat-millet (CWWM) rotation system in the tableland of the Loess Plateau. The possible responses of crop biomass C and soil organic C (SOC) accumulation were then evaluated under scenarios representing the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicated that elevated CO 2 and increased precipitation exerted positive effect on biomass C in CWWM rotation system, while increasing the temperature by 1°C, 2°C and 4°C had negative effects on biomass C due to opposite responses of corn and winter wheat to warming. SOC accumulation was enhanced by increased CO 2 concentration and precipitation but impaired by increased temperature. Under future RCP scenarios with dynamic CO 2 , the biomass C of corn exhibited decrease during the period of 2046-2075 under RCP4.5 and the period of 2016-2075 under RCP8.5 due to reduced precipitation and a warmer climate. In contrast, winter wheat would benefit from increased CO 2 and temperature and was projected to have larger biomass C under both RCP scenarios. Although the climate condition had large differences between RCP4.5 and RCP8.5, the projected SOC had similar trends under two scenarios due to CO 2 fertilizer effect and precipitation fluctuation. These results implied that crop biomass C and SOC accumulation in a warmer environment are strongly related to precipitation, and increase in field water storage should be emphasized in coping with future climate. Copyright © 2016 Elsevier B.V. All rights reserved.
Integration of lessons from recent research for “Earth to Mars” life support systems
NASA Astrophysics Data System (ADS)
Nelson, M.; Dempster, W. F.; Allen, J. P.
Development of reliable and robust strategies for long-term life support for planetary exploration must be built from real-time experimentation to verify and improve system components. Also critical is incorporating a range of viable options to handle potential short-term life system imbalances. This paper revisits some of the conceptual framework for a Mars base prototype which has been developed by the authors along with others previously advanced ("Mars on Earth ®") in the light of three years of experimentation in the Laboratory Biosphere, further investigation of system alternatives and the advent of other innovative engineering and agri-ecosystem approaches. Several experiments with candidate space agriculture crops have demonstrated the higher productivity possible with elevated light levels and improved environmental controls. For example, crops of sweet potatoes exceeded original Mars base prototype projections by an average of 46% (53% for best crop) ultradwarf (Apogee) wheat by 9% (23% for best crop), pinto bean by 13% (31% for best crop). These production levels, although they may be increased with further optimization of lighting regimes, environmental parameters, crop density etc. offer evidence that a soil-based system can be as productive as the hydroponic systems which have dominated space life support scenarios and research. But soil also offers distinct advantages: the capability to be created on the Moon or Mars using in situ space resources, reduces long-term reliance on consumables and imported resources, and more readily recycling and incorporating crew and crop waste products. In addition, a living soil contains a complex microbial ecosystem which helps prevent the buildup of trace gases or compounds, and thus assist with air and water purification. The atmospheric dynamics of these crops were studied in the Laboratory Biosphere adding to the database necessary for managing the mixed stands of crops essential for supplying a nutritionally adequate diet in space. This paper explores some of the challenges of small bioregenerative life support: air-sealing and facility architecture/design, balance of short-term variations of carbon dioxide and oxygen through staggered plantings, options for additional atmospheric buffers and sinks, lighting/energy efficiency engineering, crop and waste product recycling approaches, and human factor considerations in the design and operation of a Mars base. An "Earth to Mars" project, forging the ability to live sustainably in space (as on Earth) requires continued research and testing of these components and integrated subsystems; and developing a step-by-step learning process.
Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.
2018-03-14
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less
NASA Astrophysics Data System (ADS)
Gunda, T.; Turner, B. L.; Tidwell, V. C.
2018-04-01
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.
Chapman, Alexander; Darby, Stephen
2016-07-15
Challenging dynamics are unfolding in social-ecological systems around the globe as society attempts to mitigate and adapt to climate change while sustaining rapid local development. The IPCC's 5th assessment suggests these changing systems are susceptible to unforeseen and dangerous 'emergent risks'. An archetypal example is the Vietnamese Mekong Delta (VMD) where the river dyke network has been heightened and extended over the last decade with the dual objectives of (1) adapting the delta's 18 million inhabitants and their livelihoods to increasingly intense river-flooding, and (2) developing rice production through a shift from double to triple-cropping. Negative impacts have been associated with this shift, particularly in relation to its exclusion of fluvial sediment deposition from the floodplain. A deficit in our understanding of the dynamics of the rice-sediment system, which involve unintuitive delays, feedbacks, and tipping points, is addressed here, using a system dynamics (SD) approach to inform sustainable adaptation strategies. Specifically, we develop and test a new SD model which simulates the dynamics between the farmers' economic system and their rice agriculture operations, and uniquely, integrates the role of fluvial sediment deposition within their dyke compartment. We use the model to explore a range of alternative rice cultivation strategies. Our results suggest that the current dominant strategy (triple-cropping) is only optimal for wealthier groups within society and over the short-term (ca. 10years post-implementation). The model suggests that the policy of opening sluice gates and leaving paddies fallow during high-flood years, in order to encourage natural sediment deposition and the nutrient replenishment it supplies, is both a more equitable and a more sustainable policy. But, even with this approach, diminished supplies of sediment-bound nutrients and the consequent need to compensate with artificial fertilisers will mean that smaller-scale farmers in the VMD are more vulnerable to accruing debt. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu
2017-01-01
India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future. PMID:28753605
A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu
2017-01-01
India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.
USDA-ARS?s Scientific Manuscript database
DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...
Intelligent Planning and Scheduling for Controlled Life Support Systems
NASA Technical Reports Server (NTRS)
Leon, V. Jorge
1996-01-01
Planning in Controlled Ecological Life Support Systems (CELSS) requires special look ahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The results suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main characteristics of CELSS from the planning and scheduling perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main characteristics of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paradigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CELSS.
NASA Astrophysics Data System (ADS)
Wagner-Riddle, C.; Tenuta, M.
2014-12-01
Soil N2O fluxes (direct emissions) are highly variable in time and space due to soil, weather and management drivers. In cold climates, freeze/thaw cycles and short growing seasons can enhance soil N2O production contributing to the temporal variability of fluxes. Year-round measurements of N2O fluxes in multiple cropping systems are needed to decrease the uncertainty of annual emission estimates and to devise mitigation practices for emission reduction in cold climates. We have deployed a micrometeorological flux-gradient approach coupled to a tunable diode laser absorption spectroscopy system at two long-term sites in Canada: Elora, Ontario (2000-2014) and Glenlea, Manitoba (2006-2014). Quasi-simultaneous half-hourly flux measurements on four 4-ha fields within a level and aerodynamically homogeneous landscape were obtained allowing for comparison of crop type and/or management practices within and between years. Annual crops such as corn, soybeans, wheat, and barley received typical inorganic fertilizer and/or manure applications, and best management practices such as timing of application and reduced tillage were studied. Perennial grass-alfalfa hayfields were compared to annual crops during selected time periods. Here we synthesize the long-term datasets from these two sites, and quantify the overall contribution of non-growing season (mainly freeze/thaw cycles) and growing season (mainly nitrogen application) to annual emission totals. Uncertainties of regional estimates for cold-climates will be assessed using these long-term datasets.
Zhang, Kefeng; Bosch-Serra, Angela D.; Boixadera, Jaume; Thompson, Andrew J.
2015-01-01
Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm3 cm-3 and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha-l for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was discussed. PMID:26098946
Zhang, Kefeng; Bosch-Serra, Angela D; Boixadera, Jaume; Thompson, Andrew J
2015-01-01
Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3) cm(-3) and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l) for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was discussed.
CFD Simulation of Aerial Crop Spraying
NASA Astrophysics Data System (ADS)
Omar, Zamri; Qiang, Kua Yong; Mohd, Sofian; Rosly, Nurhayati
2016-11-01
Aerial crop spraying, also known as crop dusting, is made for aerial application of pesticides or fertilizer. An agricultural aircraft which is converted from an aircraft has been built to combine with the aerial crop spraying for the purpose. In recent years, many studies on the aerial crop spraying were conducted because aerial application is the most economical, large and rapid treatment for the crops. The main objective of this research is to study the airflow of aerial crop spraying system using Computational Fluid Dynamics. This paper is focus on the effect of aircraft speed and nozzle orientation on the distribution of spray droplet at a certain height. Successful and accurate of CFD simulation will improve the quality of spray during the real situation and reduce the spray drift. The spray characteristics and efficiency are determined from the calculated results of CFD. Turbulence Model (k-ɛ Model) is used for the airflow in the fluid domain to achieve a more accurate simulation. Furthermore, spray simulation is done by setting the Flat-fan Atomizer Model of Discrete Phase Model (DPM) at the nozzle exit. The interaction of spray from each flat-fan atomizer can also be observed from the simulation. The evaluation of this study is validation and grid dependency study using field data from industry.
Volatile Organic Compound Emissions by Agricultural Crops
NASA Astrophysics Data System (ADS)
Ormeno, E.; Farres, S.; Gentner, D.; Park, J.; McKay, M.; Karlik, J.; Goldstein, A.
2008-12-01
Biogenic Volatile Organic Compounds (BVOCs) participate in ozone and aerosol formation, and comprise a substantial fraction of reactive VOC emission inventories. In the agriculturally intensive Central Valley of California, emissions from crops may substantially influence regional air quality, but emission potentials have not been extensively studied with advanced instrumentation for many important crops. Because crop emissions may vary according to the species, and California emission inventories are constructed via a bottom-up approach, a better knowledge of the emission rate at the species-specific level is critical for reducing uncertainties in emission inventories and evaluating emission model performance. In the present study we identified and quantified the BVOCs released by dominant agricultural crops in California. A screening study to investigate both volatile and semivolatile BVOC fractions (oxygenated VOCs, isoprene, monoterepenes, sesquiterpenes, etc.) was performed for 25 crop species (at least 3 replicates plants each), including branch enclosures of woody species (e.g. peach, mandarin, grape, pistachio) and whole plant enclosures for herbaceous species (e.g. onion, alfalfa, carrot), through a dynamic cuvette system with detection by PTRMS, in-situ GCMS/FID, and collection on carbon-based adsorbents followed by extraction and GCMS analysis. Emission data obtained in this study will allow inclusion of these crops in BVOC emission inventories and air quality simulations.
Sustainable harvest: managing plasticity for resilient crops
Bloomfield, Justin A; Rose, Terry J; King, Graham J
2014-01-01
Maintaining crop production to feed a growing world population is a major challenge for this period of rapid global climate change. No consistent conceptual or experimental framework for crop plants integrates information at the levels of genome regulation, metabolism, physiology and response to growing environment. An important role for plasticity in plants is assisting in homeostasis in response to variable environmental conditions. Here, we outline how plant plasticity is facilitated by epigenetic processes that modulate chromatin through dynamic changes in DNA methylation, histone variants, small RNAs and transposable elements. We present examples of plant plasticity in the context of epigenetic regulation of developmental phases and transitions and map these onto the key stages of crop establishment, growth, floral initiation, pollination, seed set and maturation of harvestable product. In particular, we consider how feedback loops of environmental signals and plant nutrition affect plant ontogeny. Recent advances in understanding epigenetic processes enable us to take a fresh look at the crosstalk between regulatory systems that confer plasticity in the context of crop development. We propose that these insights into genotype × environment (G × E) interaction should underpin development of new crop management strategies, both in terms of information-led agronomy and in recognizing the role of epigenetic variation in crop breeding. PMID:24891039
Learning to Control Advanced Life Support Systems
NASA Technical Reports Server (NTRS)
Subramanian, Devika
2004-01-01
Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for advanced life support.
Land management: data availability and process understanding for global change studies.
Erb, Karl-Heinz; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Pongratz, Julia; Don, Axel; Kloster, Silvia; Kuemmerle, Tobias; Fetzel, Tamara; Fuchs, Richard; Herold, Martin; Haberl, Helmut; Jones, Chris D; Marín-Spiotta, Erika; McCallum, Ian; Robertson, Eddy; Seufert, Verena; Fritz, Steffen; Valade, Aude; Wiltshire, Andrew; Dolman, Albertus J
2017-02-01
In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Desjardins, R.; Smith, W.; Qi, Z.; Grant, B.; VanderZaag, A.
2017-12-01
Biophysical models are needed for assessing science-based mitigation options to improve the efficiency and sustainability of agricultural cropping systems. In order to account for trade-offs between environmental indicators such as GHG emissions, soil C change, and water quality it is important that models can encapsulate the complex array of interrelated biogeochemical processes controlling water, nutrient and energy flows in the agroecosystem. The Denitrification Decomposition (DNDC) model is one of the most widely used process-based models, and is arguably the most sophisticated for estimating GHG emissions and soil C&N cycling, however, the model simulates only simple cascade water flow. The purpose of this study was to compare the performance of DNDC to a comprehensive water flow model, the Root Zone Water Quality Model (RZWQM2), to determine which processes in DNDC may be limiting and recommend improvements. Both models were calibrated and validated for simulating crop biomass, soil hydrology, and nitrogen loss to tile drains using detailed observations from a corn-soybean rotation in Iowa, with and without cover crops. Results indicated that crop yields, biomass and the annual estimation of nitrogen and water loss to tiles drains were well simulated by both models (NSE > 0.6 in all cases); however, RZWQM2 performed much better for simulating soil water content, and the dynamics of daily water flow (DNDC: NSE -0.32 to 0.28; RZWQM2: NSE 0.34 to 0.70) to tile drains. DNDC overestimated soil water content near the soil surface and underestimated it deeper in the profile which was presumably caused by the lack of a root distribution algorithm, the inability to simulate a heterogeneous profile and lack of a water table. We recommend these improvements along with the inclusion of enhanced water flow and a mechanistic tile drainage sub-model. The accurate temporal simulation of water and N strongly impacts several biogeochemical processes.
Reed-Jones, Neiunna L; Marine, Sasha Cahn; Everts, Kathryne L; Micallef, Shirley A
2016-01-04
Cover crops provide several ecosystem services, but their impact on enteric bacterial survival remains unexplored. The influence of cover cropping on foodborne pathogen indicator bacteria was assessed in five cover crop/green manure systems: cereal rye, hairy vetch, crimson clover, hairy vetch-rye and crimson clover-rye mixtures, and bare ground. Cover crop plots were inoculated with Escherichia coli and Listeria innocua in the fall of 2013 and 2014 and tilled into the soil in the spring to form green manure. Soil samples were collected and the bacteria enumerated. Time was a factor for all bacterial populations studied in all fields (P < 0.001). E. coli levels declined when soil temperatures dipped to <5°C and were detected only sporadically the following spring. L. innocua diminished somewhat but persisted, independently of season. In an organic field, the cover crop was a factor for E. coli in year 1 (P = 0.004) and for L. innocua in year 2 (P = 0.011). In year 1, E. coli levels were highest in the rye and hairy vetch-rye plots. In year 2, L. innocua levels were higher in hairy vetch-rye (P = 0.01) and hairy vetch (P = 0.03) plots than in the rye plot. Bacterial populations grew (P < 0.05) or remained the same 4 weeks after green manure incorporation, although initial reductions in L. innocua numbers were observed after tilling (P < 0.05). Green manure type was a factor only for L. innocua abundance in a transitional field (P < 0.05). Overall, the impacts of cover crops/green manures on bacterial population dynamics in soil varied, being influenced by bacterial species, time from inoculation, soil temperature, rainfall, and tillage; this reveals the need for long-term studies. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
USDA-ARS?s Scientific Manuscript database
The dynamics of microbial communities associated with dying cover crops are of interest because of potential impacts on disease in a subsequent crop, and because of the importance of microbial activity on plant residue to soil organic matter dynamics and nutrient cycling. High throughput amplicon se...
Mishra, Abhinav; Pang, Hao; Buchanan, Robert L; Schaffner, Donald W; Pradhan, Abani K
2017-01-15
The majority of foodborne outbreaks in the United States associated with the consumption of leafy greens contaminated with Escherichia coli O157:H7 have been reported during the period of July to November. A dynamic system model consisting of subsystems and inputs to the system (soil, irrigation, cattle, wild pig, and rainfall) simulating a hypothetical farm was developed. The model assumed two crops of lettuce in a year and simulated planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. As predicted by the baseline model for crops harvested in different months from conventional fields, an estimated 13 out of 257 (5.05%) first crops harvested in July would have at least one plant with at least 1 CFU of E. coli O157:H7. Predictions indicate that no first crops would be contaminated with at least 1 CFU of E. coli O157:H7 for other months (April to June). The maximum E. coli O157:H7 concentration in a plant was higher in the second crop (27.10 CFU) than in the first crop (9.82 CFU). For the second crop, the probabilities of having at least one plant with at least 1 CFU of E. coli O157:H7 in a crop were predicted as 15/228 (6.6%), 5/333 (1.5%), 14/324 (4.3%), and 6/115 (5.2%) in August, September, October, and November, respectively. For organic fields, the probabilities of having at least one plant with ≥1 CFU of E. coli O157:H7 in a crop (3.45%) were predicted to be higher than those for the conventional fields (2.15%). This study is the first attempt toward developing a mathematical system model to understand the pathway of E. coli O157:H7 in the production of leafy greens. Results of the presented system model indicate that the seasonality of outbreaks of E. coli O157:H7-associated contamination of leafy greens was in good agreement with the prevalence of this pathogen in cattle and wild pig feces in a major leafy greens-producing region in California. On the basis of comparisons among the results of different scenarios, it can be recommended that the concentration of E. coli O157:H7 in leafy greens can be reduced considerably if contamination of soil with wild pig and cattle feces is mitigated. Copyright © 2016 American Society for Microbiology.
Mishra, Abhinav; Pang, Hao; Buchanan, Robert L.
2016-01-01
ABSTRACT The majority of foodborne outbreaks in the United States associated with the consumption of leafy greens contaminated with Escherichia coli O157:H7 have been reported during the period of July to November. A dynamic system model consisting of subsystems and inputs to the system (soil, irrigation, cattle, wild pig, and rainfall) simulating a hypothetical farm was developed. The model assumed two crops of lettuce in a year and simulated planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. As predicted by the baseline model for crops harvested in different months from conventional fields, an estimated 13 out of 257 (5.05%) first crops harvested in July would have at least one plant with at least 1 CFU of E. coli O157:H7. Predictions indicate that no first crops would be contaminated with at least 1 CFU of E. coli O157:H7 for other months (April to June). The maximum E. coli O157:H7 concentration in a plant was higher in the second crop (27.10 CFU) than in the first crop (9.82 CFU). For the second crop, the probabilities of having at least one plant with at least 1 CFU of E. coli O157:H7 in a crop were predicted as 15/228 (6.6%), 5/333 (1.5%), 14/324 (4.3%), and 6/115 (5.2%) in August, September, October, and November, respectively. For organic fields, the probabilities of having at least one plant with ≥1 CFU of E. coli O157:H7 in a crop (3.45%) were predicted to be higher than those for the conventional fields (2.15%). IMPORTANCE This study is the first attempt toward developing a mathematical system model to understand the pathway of E. coli O157:H7 in the production of leafy greens. Results of the presented system model indicate that the seasonality of outbreaks of E. coli O157:H7-associated contamination of leafy greens was in good agreement with the prevalence of this pathogen in cattle and wild pig feces in a major leafy greens-producing region in California. On the basis of comparisons among the results of different scenarios, it can be recommended that the concentration of E. coli O157:H7 in leafy greens can be reduced considerably if contamination of soil with wild pig and cattle feces is mitigated. PMID:27836846
NASA Astrophysics Data System (ADS)
Durand, P.
The integrated nitrogen model INCA (Integrated Nitrogen in Catchments) was used to analyse the nitrogen dynamics in a small rural catchment in Western France. The agrosystem studied is very complex, with: extensive use of different organic fertilisers, a variety of crop rotations, a structural excess of nitrogen (i.e. more animal N produced by the intensive farming than the N requirements of the crops and pastures), and nitrate retention in both hydrological stores and riparian zones. The original model features were adapted here to describe this complexity. The calibration results are satisfactory, although the daily variations in stream nitrate are not simulated in detail. Different climate scenarios, based on observed climate records, were tested; all produced a worsening of the pollution in the short term. Scenarios of alternative agricultural practices (reduced fertilisation and catch crops) were also analysed, suggesting that a reduction by 40% of the fertilisation combined with the introduction of catch crops would be necessary to stop the degradation of water quality.
Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael
2016-01-01
Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector’s life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis’ life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector–based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector. PMID:27159134
Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael
2016-01-01
Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.
Dong, Kun; Dong, Yan; Wang, Hai-Long; Zhang, Li-Min; Zan, Qing-An; Chen, Bin; Li, Zheng-Yue
2014-01-01
A series of rice pest injuries (due to pathogens, insects, and weeds) were surveyed in 286 farmers' fields for major rice varieties of three rice cropping zones of Yunnan Province, Southwest China. The composition and dynamics of main pest species were analyzed, and the trend of rice pest succession in Yunnan was discussed based upon landmark publications. The results showed that the three rice cropping zones had different pest characteristics as regard to main species, dynamics and combined injuries. Sheath rot, bacterial leaf blight, rice stripe, leaf hoppers, armyworms and stem borers were serious in the japonica rice zone. Sheath blight and rice stripe were serious in the japonica-indica interlacing zone. Leaf blast, sheath blight, leaf folders and weeds above rice crop canopy were serious in the indica rice zone. False smut, plant hoppers and weeds below rice crop canopy were ubiquitous and serious in the three kinds of rice cropping zones. Many kinds of weed infestation emerged in the whole rice cropping seasons. Echinochloa crusgalli, Sagittaria pygmaea, Potamogeton distinctus and Spirodela polyrhiza were the main species of weeds in the rice cropping zones of Yunnan. Overall, levels of combined injuries due to pests in the japonica rice zone and the indica rice zone were higher than that in the japonica-indica interlacing zone. In terms of the trend of rice pest succession in Yunnan, injuries due to false smut, sheath blight and plant hoppers seemed to be in a worse tendency in all rice cropping zones of Yunnan, while dominants species of weeds in the paddy fields are shifting from the annual weeds to the perennial malignant weeds.
Directional reflectance factor distributions of a cotton row crop
NASA Technical Reports Server (NTRS)
Kimes, D. S.; Newcomb, W. W.; Schutt, J. B.; Pinter, P. J., Jr.; Jackson, R. D.
1984-01-01
The directional reflectance factor distribution spanning the entire exitance hemisphere was measured for a cotton row crop (Gossypium barbadense L.) with 39 percent ground cover. Spectral directional radiances were taken in NOAA satellite 7 AVHRR bands 1 and 2 using a three-band radiometer with restricted 12 deg full angle field of view at half peak power points. Polar co-ordinate system plots of directional reflectance factor distributions and three-dimensional computer graphic plots of scattered flux were used to study the dynamics of the directional reflectance factor distribution as a function of spectral band, geometric structure of the scene, solar zenith and azimuth angles, and optical properties of the leaves and soil. The factor distribution of the incomplete row crops was highly polymodal relative to that for complete vegetation canopies. Besides the enhanced reflectance for the antisolar point, a reflectance minimum was observed towards the forwardscatter direction in the principle plane of the sun. Knowledge of the mechanics of the observed dynamics of the data may be used to provide rigorous validation for two- or three-dimensional radiative transfer models, and is important in interpreting aircraft and satellite data where the solar angle varies widely.
Estimating yield gaps at the cropping system level.
Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G
2017-05-01
Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.
MEASUREMENT OF NITROGEN OXIDE EMISSIONS FROM AN AGRICULTURAL SOIL WITH A DYNAMIC CHAMBER SYSTEM
Biogenic soil emissions of nitric oxide (NO) were measured from an intensively managed agricultural row crop (corn, Zea mays) during a 4 week period May 15 through June 9, 1995). The site was located in Washington County, near the town of Plymouth, which is in the Lower Coastal P...
USDA-ARS?s Scientific Manuscript database
The years of intensive tillage in many countries, including Cambodia, have caused significant decline in agriculture’s natural resources that could threaten the future of agricultural production and sustainability worldwide. Long-term tillage system and site-specific crop management can affect chang...
USDA-ARS?s Scientific Manuscript database
Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most important diseases in the United States. Epidemiological regions were determined based on epidemic patterns, cropping systems, geographic barriers, weather patterns, and inoculum exchanges. Areas where Ps...
USDA-ARS?s Scientific Manuscript database
Decomposition and nutrient release of winter annual forages in integrated crop-livestock systems could be affected by the resultant alterations in structure and quality of residues caused by grazing, but little information is available to test this hypothesis. Information on residue dynamics is need...
Putting mechanisms into crop production models
USDA-ARS?s Scientific Manuscript database
Crop simulation models dynamically predict processes of carbon, nitrogen, and water balance on daily or hourly time-steps to the point of predicting yield and production at crop maturity. A brief history of these models is reviewed, and their level of mechanism for assimilation and respiration, ran...
Contrasting effects of landscape composition on crop yield mediated by specialist herbivores.
Perez-Alvarez, Ricardo; Nault, Brian A; Poveda, Katja
2018-04-01
Landscape composition not only affects a variety of arthropod-mediated ecosystem services, but also disservices, such as herbivory by insect pests that may have negative effects on crop yield. Yet, little is known about how different habitats influence the dynamics of multiple herbivore species, and ultimately their collective impact on crop production. Using cabbage as a model system, we examined how landscape composition influenced the incidence of three specialist cruciferous pests (aphids, flea beetles, and leaf-feeding Lepidoptera), lepidopteran parasitoids, and crop yield across a gradient of landscape composition in New York, USA. We expected that landscapes with a higher proportion of cropland and lower habitat diversity would lead to an increase in pest pressure of the specialist herbivores and a reduction in crop yield. However, results indicated that neither greater cropland area nor lower landscape diversity influenced pest pressure or yield. Rather, pest pressure and yield were best explained by the presence of non-crop habitats (i.e., meadows) in the landscape. Specifically, cabbage was infested with fewer Lepidoptera in landscapes with a higher proportion of meadows likely resulting from increased parasitism. Conversely, cabbage was infested with more flea beetles and aphids as the proportion of meadows in the landscape increased, suggesting that these pests benefit from non-crop habitats. Furthermore, path analysis confirmed that these landscape-mediated effects on pest populations can have either positive or negative cascading effects on crop yield. Our findings illustrate how different pest species within the same cropping system show contrasting responses to landscape composition with respect to both the direction and spatial scale of the relationship. Such tradeoffs resulting from the complex interaction between multiple-pests, natural enemies, and landscape composition must be considered, if we are to manage landscapes for pest suppression benefits. © 2018 by the Ecological Society of America.
VegScape: U.S. Crop Condition Monitoring Service
NASA Astrophysics Data System (ADS)
mueller, R.; Yang, Z.; Di, L.
2013-12-01
Since 1995, the US Department of Agriculture (USDA)/National Agricultural Statistics Service (NASS) has provided qualitative biweekly vegetation condition indices to USDA policymakers and the public on a weekly basis during the growing season. Vegetation indices have proven useful for assessing crop condition and identifying the areal extent of floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. With growing emphasis on more extreme weather events and food security issues rising to the forefront of national interest, a new vegetation condition monitoring system was developed. The new vegetation condition portal named VegScape was initiated at the start of the 2013 growing season. VegScape delivers web mapping service based interactive vegetation indices. Users can use an interactive map to explore, query and disseminate current crop conditions. Vegetation indices like Normal Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and mean, median, and ratio comparisons to prior years can be constructed for analytical purposes and on-demand crop statistics. The NASA MODIS satellite with 250 meter (15 acres) resolution and thirteen years of data history provides improved spatial and temporal resolutions and delivers improved detailed timely (i.e., daily) crop specific condition and dynamics. VegScape thus provides supplemental information to support NASS' weekly crop reports. VegScape delivers an agricultural cultivated crop mask and the most recent Cropland Data Layer (CDL) product to exploit the agricultural domain and visualize prior years' planted crops. Additionally, the data can be directly exported to Google Earth for web mashups or delivered via web mapping services for uses in other applications. VegScape supports the ethos of data democracy by providing free and open access to digital geospatial data layers using open geospatial standards, thereby supporting transparent and collaborative government initiatives. NASS developed VegScape in cooperation with the Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA. VegScape Ratio to Median NDVI
NASA Astrophysics Data System (ADS)
Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.
2014-12-01
The complex interactions and feedbacks between humans and water are very essential issues but are poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable to improve our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed for the Tarim River Basin in Western China, and is used to illustrate the explanatory power of such a model. The study area is the mainstream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four parts, i.e., social sub-system, economic sub-system, ecological sub-system, and hydrological sub-system. In each modeling unit, four coupled ordinary differential equations are used to simulate the dynamics of the social sub-system represented by human population, the economic sub-system represented by irrigated crop area, the ecological sub-system represented by natural vegetation cover and the hydrological sub-system represented by stream discharge. The coupling and feedback processes of the four dominant sub-systems (and correspondingly four state variables) are integrated into several internal system characteristics interactively and jointly determined by themselves and by other coupled systems. For example, the stream discharge is coupled to the irrigated crop area by the colonization rate and mortality rate of the irrigated crop area in the upper reach and the irrigated area is coupled to stream discharge through irrigation water consumption. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. In the modeling framework, the state of each subsystem is holistically described by one state variable and the framework is flexible enough to comprise more processes and constitutive relationships if they are needed to illustrate the interaction and feedback mechanisms of the human-water system.
Historical and simulated ecosystem carbon dynamics in Ghana: Land use, management, and climate
Tan, Z.; Tieszen, L.L.; Tachie-Obeng, E.; Liu, S.; Dieye, A.M.
2009-01-01
We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha−1 in 1900 to 77.0 Mg C ha−1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha−1 to 21.2 Mg C ha−1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha−1 and by 42% with 60 kg N ha−1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.
Historical and simulated ecosystem carbon dynamics in Ghana: land use, management, and climate
NASA Astrophysics Data System (ADS)
Tan, Z.; Tieszen, L. L.; Tachie-Obeng, E.; Liu, S.; Dieye, A. M.
2009-01-01
We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha-1 in 1900 to 77.0 Mg C ha-1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha-1 to 21.2 Mg C ha-1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha-1 and by 42% with 60 kg N ha-1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.
NASA Astrophysics Data System (ADS)
Jaiswal, D.; Long, S.; Parton, W. J.; Hartman, M.
2012-12-01
A coupled modeling system of crop growth model (BioCro) and biogeochemical model (DayCent) has been developed to assess the two-way interactions between plant growth and biogeochemistry. Crop growth in BioCro is simulated using a detailed mechanistic biochemical and biophysical multi-layer canopy model and partitioning of dry biomass into different plant organs according to phenological stages. Using hourly weather records, the model partitions light between dynamically changing sunlit and shaded portions of the canopy and computes carbon and water exchange with the atmosphere and through the canopy for each hour of the day, each day of the year. The model has been parameterized for the bioenergy crops sugarcane, Miscanthus and switchgrass, and validation has shown it to predict growth cycles and partitioning of biomass to a high degree of accuracy. As such it provides an ideal input for a soil biogeochemical model. DayCent is an established model for predicting long-term changes in soil C & N and soil-atmosphere exchanges of greenhouse gases. At present, DayCent uses a relatively simple productivity model. In this project BioCro has replaced this simple model to provide DayCent with a productivity and growth model equal in detail to its biogeochemistry. Dynamic coupling of these two models to produce CroCent allows for differential C: N ratios of litter fall (based on rates of senescence of different plant organs) and calibration of the model for realistic plant productivity in a mechanistic way. A process-based approach to modeling plant growth is needed for bioenergy crops because research on these crops (especially second generation feedstocks) has started only recently, and detailed agronomic information for growth, yield and management is too limited for effective empirical models. The coupled model provides means to test and improve the model against high resolution data, such as that obtained by eddy covariance and explore yield implications of different crop and soil management.
Soil CO2 flux in alley-cropping systems composed of black locust and poplar trees, Germany
NASA Astrophysics Data System (ADS)
Medinski, Tetiana; Freese, Dirk; Boehm, Christian
2013-04-01
The understanding of soil carbon dynamics after establishment of alley-cropping systems is crucial for mitigation of greenhouse CO2 gas. This study investigates soil CO2 fluxes in alley-cropping systems composed of strips of black locust (Robinia pseudoacacia L.) and poplar (Max 1) trees and adjacent to them crop strips (Lupinus). Soil CO2 flux was measured monthly over a period from March to November 2012, using a LI-COR LI-8100A automated device. Concurrently with CO2 flux measurements, soil and air temperature and soil moisture were recorded within 10 cm of each collar. Soil samples were collected nearby each soil collar for microbial C and hot water-extractable C analyses. At each study plot, root biomass was measured to a depth of 15 cm. In all vegetation types, soil CO2 flux increased from May to August, showing a significant positive correlation with air and soil temperature, which can be a reflection of increase in photosynthesis over the warm summer months. CO2 flux was the highest in poplar followed by black locust and lupines. The relationships between CO2 flux, microbial biomass and hot water-extractable carbon were not straightforward. Among the measured parameters, root density was found to be the main factor to explain the higher CO2 flux in tree strips.
How can soil organic carbon stocks in agriculture be maintained or increased?
NASA Astrophysics Data System (ADS)
Don, Axel; Leifeld, Jens
2015-04-01
CO2 emissions from soils are 10 times higher than anthropogenic CO2 emissions from fossil burning with around 60 Pg C a-1. At the same time around 60 Pg of carbon is added to the soils as litter from roots and leaves. Thus, the balance between both fluxes is supposed to be zero for the global earth system in steady state without human perturbations. However, the global carbon flux has been altered by humans since thousands of years by extracting biomass carbon as food, feed and fiber with global estimate of 40% of net primary productivity (NPP). This fraction is low in forests but agricultural systems, in particular croplands, are systems with a high net exported carbon fraction. Soils are mainly input driven systems. Agricultural soils depend on input to compensate directly for i) respiration losses, ii) extraction of carbon (and nitrogen) and depletion (e.g. via manure) or indirectly via enhances NPP (e.g. via fertilization management). In a literature review we examined the role of biomass extraction and carbon input via roots, crop residues and amendments (manure, slurry etc.) to agricultural soil's carbon stocks. Recalcitrance of biomass carbon was found to be of minor importance for long-term carbon storage. Thus, also the impact of crop type on soil carbon dynamics seems mainly driven by the amount of crop residuals of different crop types. However, we found distinct differences in the efficiency of C input to refill depleted soil C stocks between above ground C input or below ground root litter C input, with root-C being more efficient due to slower turnover rates. We discuss the role of different measures to decrease soil carbon turnover (e.g. decreased tillage intensity) as compared to measures that increase C input (e.g. cover crops) in the light of global developments in agricultural management with ongoing specialization and segregation between catch crop production and dairy farms.
Mind the Roots: Phenotyping Below-Ground Crop Diversity and Its Influence on Final Yield
NASA Astrophysics Data System (ADS)
Nieters, C.; Guadagno, C. R.; Lemli, S.; Hosseini, A.; Ewers, B. E.
2017-12-01
Changes in global climate patterns and water regimes are having profound impacts on worldwide crop production. An ever-growing population paired with increasing temperatures and unpredictable periods of severe drought call for accurate modeling of future crop yield. Although novel approaches are being developed in high-throughput, above-ground image phenotyping, the below-ground plant system is still poorly phenotyped. Collection of plant root morphology and hydraulics are needed to inform mathematical models to reliably estimate yields of crops grown in sub-optimal conditions. We used Brassica rapa to inform our model as it is a globally cultivated crop with several functionally diverse cultivars. Specifically, we use 7 different accessions from oilseed (R500 and Yellow Sarson), leafy type (Pac choi and Chinese cabbage), a vegetable turnip, and two Wisconsin Fast Plants (Imb211 and Fast Plant self-compatible), which have shorter life cycles and potentially large differences in allocation to roots. Bi-weekly, we harvested above and below-ground biomass to compare the varieties in terms of carbon allocation throughout their life cycle. Using WinRhizo software, we analyzed root system length and surface area to compare and contrast root morphology among cultivars. Our results confirm that root structural characteristics are crucial to explain plant water use and carbon allocation. The root:shoot ratio reveals a significant (p < 0.01) difference among crop accession. To validate the procedure across different varieties and life stages we also compared surface area results from the image-based technology to dry biomass finding a strong linear relationship (R2= 0.85). To assess the influence of a diverse above-ground morphology on the root system we also measured above-ground anatomical and physiological traits such as gas exchange, chlorophyll content, and chlorophyll a fluorescence. A thorough analysis of the root system will clarify carbon dynamics and hydraulics at the whole-plant level, improving final yield predictions.
Impacts of crop rotations on soil organic carbon sequestration
NASA Astrophysics Data System (ADS)
Gobin, Anne; Vos, Johan; Joris, Ingeborg; Van De Vreken, Philippe
2013-04-01
Agricultural land use and crop rotations can greatly affect the amount of carbon sequestered in the soil. We developed a framework for modelling the impacts of crop rotations on soil carbon sequestration at the field scale with test case Flanders. A crop rotation geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System) to elicit the most common crop rotation on major soil types in Flanders. In order to simulate the impact of crop cover on carbon sequestration, the Roth-C model was adapted to Flanders' environment and coupled to common crop rotations extracted from the IACS geodatabases and statistical databases on crop yield. Crop allometric models were used to calculate crop residues from common crops in Flanders and subsequently derive stable organic matter fluxes to the soil (REGSOM). The REGSOM model was coupled to Roth-C model was run for 30 years and for all combinations of seven main arable crops, two common catch crops and two common dosages of organic manure. The common crops are winter wheat, winter barley, sugar beet, potato, grain maize, silage maize and winter rapeseed; the catch crops are yellow mustard and Italian ryegrass; the manure dosages are 35 ton/ha cattle slurry and 22 ton/ha pig slurry. Four common soils were simulated: sand, loam, sandy loam and clay. In total more than 2.4 million simulations were made with monthly output of carbon content for 30 years. Results demonstrate that crop cover dynamics influence carbon sequestration for a very large percentage. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. Crop residues of grain maize and winter wheat followed by catch crops contribute largely to the total carbon sequestered. This implies that agricultural policies that impact on agricultural land management influence soil carbon sequestration for a large percentage. The framework is therefore suited for further scenario analysis and impact assessment in order to support agri-environmental policy decisions.
The Implications of Growing Bioenergy Crops on Water Resources, Carbon and Nitrogen Dynamics
NASA Astrophysics Data System (ADS)
Jain, A. K.; Song, Y.; Kheshgi, H. S.
2016-12-01
What is the potential for the crops Corn, Miscanthus and switchgrass to meet future energy demands in the U.S.A., and would they mitigate climate change by offsetting fossil fuel greenhouse gas (GHG) emissions? The large-scale cultivation of these bioenergy crops itself could also drive climate change through changes in albedo, evapotranspiration (ET), and GHG emissions. Whether these climate effects will mitigate or exacerbate climate change in the short- and long-term is uncertain. This uncertainty stems from our incomplete understanding of the effects of expanded bioenergy crop production on terrestrial water and energy balance, carbon and nitrogen dynamics, and their interactions. This study aims to understand the implications of growing large-scale bioenergy crops on water resources, carbon and nitrogen dynamics in the United States using a data-modeling framework (ISAM) that we developed. Our study indicates that both Miscanthus and Cave-in-Rock switchgrass can attain high and stable yield over parts of the Midwest, however, this high production is attained at the cost of increased soil water loss as compared to current natural vegetation. Alamo switchgrass can attain high and stable yield in the southern US without significant influence on soil water quantity.
USDA-ARS?s Scientific Manuscript database
In natural settings such as under field conditions, the plant available soil nutrients in conjunction with other environmental factors such as, solar radiation, temperature, precipitation, and atmospheric carbon dioxide (CO2) concentration determine crop adaptation and productivity. Therefore, crop...
Dynamic precision phenotyping reveals mechanism of crop tolerance to root herbivory
USDA-ARS?s Scientific Manuscript database
The western corn rootworm, Diabrotica virgifera virgifera (LeConte) is a major pest of maize, Zea mays L. Over the years, this pest has repeatedly shown its resilience and adaptability not only to traditional crop management strategies including chemical pesticides and crop rotation, but also to de...
USDA-ARS?s Scientific Manuscript database
Integrated crop-livestock systems can help achieve greater environmental quality from disparate crop and livestock systems by recycling nutrients and taking advantage of synergies between systems. We investigated crop and animal production responses in integrated crop-livestock systems with two typ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chescheir, George M.; Nettles, Jami E,; Youssef, Mohamed
Growing switchgrass (Panicum virgatum L.) as an intercrop in managed loblolly pine (Pinus taeda L.) plantations has emerged as a potential source of bioenergy feedstock. Utilizing land resources between pine trees to produce an energy crop can potentially reduce the demand for land resources used to produce food; however, converting conventionally managed forest land to this new intercropping system constitutes changes in land use and associated management practices, which may affect the environmental and economic sustainability of the land. The overall objective of this project is to evaluate the environmental effects of large-scale forest bioenergy crop production and utilize thesemore » results to optimize cropping systems in a manner that protects the important ecosystem services provided by forests while contributing to the development of a sustainable and economically-viable biomass industry in the southeastern United States. Specific objectives are to: Quantify the hydrology of different energy crop production systems in watershed scale experiments on different landscapes in the southeast. Quantify the nutrient dynamics of energy crop production systems in watershed scale experiments to determine the impact of these systems on water quality. Evaluate the impacts of energy crop production on soil structure, fertility, and organic matter. Evaluate the response of flora and fauna populations and habitat quality to energy crop production systems. Develop watershed and regional scale models to evaluate the environmental sustainability and productivity of energy crop and woody biomass operations. Quantify the production systems in terms of bioenergy crop yield versus the energy and economic costs of production. Develop and evaluate best management practice guidelines to ensure the environmental sustainability of energy crop production systems. Watershed and plot scale studies formed the core of this research platform. Matched-watershed studies were established in North Carolina, Mississippi and Alabama. A plot scale study was also established in North Carolina to more intensive examination of the effects of biomass production on hydrology, soil properties, productivity wildlife habitat, and biodiversity on replicate 0.8 ha plots. Studies were also conducted on selected sites to define and quantify the environmental effects of biomass production on wildlife habitat, biodiversity, soil properties and productivity, and carbon storage and flux. Treatments on the sub-watersheds and plots included potential operational systems ranging from monoculture switchgrass to interplanted switchgrass to conventional managed forests as a controls. The hydrology, water quality, soil property, and productivity data collected in the watershed and plot scale experiments were used to develop process based watershed scale models. Existing models (DRAINMOD and APEX) were modified to more effectively simulate the intercropped systems. More regional scale models (DRAINMOD-INTERCROP) with GIS interface and SWAT) were used to simulate the impacts of intercropping switchgrass in pine plantations on the hydrology and water quality of larger scale watersheds. Results from the watershed and plot scale studies, and the modeling studies were used to develop Best Management Practice (BMP) guidelines to ensure environmentally sustainable bioenergy production in the forestry setting. While the results of the environmental sustainability research for this project have become publically available, many of the planning decisions and operational trial results were not public. Personnel in management, planning, operations, and logistics were interviewed to capture the important economic and operational lessons from internal operational research on approximately 30 full-scale operational tracts. This project produced a very large database documenting the impact of interplanting switchgrass with pine trees on hydrology, water quality, soil quality, and biodiversity. Some environmental impacts were observed in response to additional operations required for interplanting, but these impacts were small and short lived. Given that existing forestry BMPs provide a flexible system that can be adapted to protect water quality and biodiversity in forestry settings, interplanting switchgrass with pine trees can be considered environmentally sustainable. The project also developed models that can simulate switchgrass growth when it is in competition with pine trees as well as the hydrology and nutrient dynamics that result from this interplanted system. The models predicted switchgrass production, water use, and the quality of the water leaving the system over a range of climatological and geographic conditions. These models can be used to guide decisions toward sustainability. The project also documented the limitations of switchgrass production in the forestry setting and the challenges and increased costs arising from this practice. These challenges led to the conclusion that intercropping switchgrass with pine trees is not economically feasible in the current economic climate. Despite the barriers obstructing use of this system at this point in time, economic and technological changes may occur that will make this a feasible system for bioenergy production in the future. The data, models, BMPs and experiences documented in this report and in publications resulting from this project will be highly valuable to those implementing this system.« less
Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production
NASA Astrophysics Data System (ADS)
Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.
2014-12-01
The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are associated to derive food production estimates. Based on trends analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. CropWatch bulletin can be downloaded from the CropWatch website at http://www.cropwatch.com.cn.
Numerical and experimental investigation of direct solar crop dryer for farmers
NASA Astrophysics Data System (ADS)
Kareem, M. W.; Habib, Khairul; Sulaiman, S. A.
2015-07-01
This article presents a theoretical and experimental investigation on effects of weather on direct solar crop drying technique. The SIMULINK tool was employed to analyze the energy balance equations of the transient system model. A prototype of the drying system was made and data were collected between the months of June and July in Perak, Malaysia. The contribution of intense sunny days was encouraging despite the wet season, and the wind velocity was dynamic during the period of investigation. However, high percentage of relative humidity was observed. This constitutes a hindrance to efficient drying process. The reported studies were silent on the effect of thick atmospheric moisture content on drying rate of agricultural products in tropic climate. This finding has revealed the mean values of insolation, wind speed, moisturized air, system performance efficiency and chili microscopy image morphology. The predicted and measured results were compared with good agreement.
Leplat, J; Heraud, C; Gautheron, E; Mangin, P; Falchetto, L; Steinberg, C
2016-11-01
To evaluate the effect of the type of crop residues on the colonization dynamic of Fusarium graminearum in soil. The ability of F. graminearum to survive in the presence of various crop residues was assessed on Petri dishes and in microcosms. These microcosms comprised soil that had or had not been previously disinfested with or without amendment with various crop residues. The colonization dynamic of F. graminearum was monitored through real-time PCR. Fusarium graminearum development was higher in disinfested soil than in non-disinfested one. The fungal growth was enhanced to various extents according to the type of crop residues, except for mustard residues which inhibited it. The biochemical and physical properties of the residues were likely to account for the differences in the survival of F. graminearum. Fusarium graminearum is a poor competitor in soil but it can use maize, wheat, and rape residues to ensure its survival. Conversely alfalfa, which is assimilated by micro-organisms very easily, avoids long-lasting survival of the fungus. And finally, mustard producing glucosinolates could be used as an intermediate crop to reduce the inoculum amount. This study is contributing to the knowledge about F. graminearum saprotophic abilities and proposes interesting paths to limit its survival in soil. © 2016 The Society for Applied Microbiology.
Effects of Land Use Change for Crops on Water and Carbon Budgets in the Midwest USA
Sun, Jian; Twine, Tracy; Hill, Jason; ...
2017-02-07
By increasing the demand for food and bioenergy, the global landscape has altered dramatically in recent years. Land use and land cover change affects the environmental system in many ways through biophysical and biogeochemical mechanisms. Here, we evaluate the impacts of land use and land cover change driven by recent crop expansion and conversion on the water budget, carbon exchange, and carbon storage in the Midwest USA. A dynamic global vegetation model was used to simulate and examine the impacts of landscape change in a historical case based on crop distribution data from the United States Department of Agriculture Nationalmore » Agricultural Statistics Services. Furthermore, the simulation results indicate that recent crop expansion not only decreased soil carbon sequestration (60 Tg less of soil organic carbon) and net carbon flux into ecosystems (3.7 Tg • year -1 less of net biome productivity), but also lessened water consumption through evapotranspiration (1.04 x 10 10 m 3 • year -1 less) over 12 states in the Midwest. More water yield at the land surface does not necessarily make more water available for vegetation. Crop residue removal might also exacerbate the soil carbon loss.« less
Effects of Land Use Change for Crops on Water and Carbon Budgets in the Midwest USA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Jian; Twine, Tracy; Hill, Jason
By increasing the demand for food and bioenergy, the global landscape has altered dramatically in recent years. Land use and land cover change affects the environmental system in many ways through biophysical and biogeochemical mechanisms. Here, we evaluate the impacts of land use and land cover change driven by recent crop expansion and conversion on the water budget, carbon exchange, and carbon storage in the Midwest USA. A dynamic global vegetation model was used to simulate and examine the impacts of landscape change in a historical case based on crop distribution data from the United States Department of Agriculture Nationalmore » Agricultural Statistics Services. Furthermore, the simulation results indicate that recent crop expansion not only decreased soil carbon sequestration (60 Tg less of soil organic carbon) and net carbon flux into ecosystems (3.7 Tg • year -1 less of net biome productivity), but also lessened water consumption through evapotranspiration (1.04 x 10 10 m 3 • year -1 less) over 12 states in the Midwest. More water yield at the land surface does not necessarily make more water available for vegetation. Crop residue removal might also exacerbate the soil carbon loss.« less
Kumar, Pankaj; Srivastava, Dinesh Kumar
2016-04-01
Biotechnology holds promise for genetic improvement of important vegetable crops. Broccoli (Brassica oleracea L. var. italica) is an important vegetable crop of the family Brassicaceae. However, various biotic and abiotic stresses cause enormous crop yield losses during commercial cultivation of broccoli. Establishment of a reliable, reproducible and efficient in vitro plant regeneration system with cell and tissue culture is a vital prerequisite for biotechnological application of crop improvement programme. An in vitro plant regeneration technique refers to culturing, cell division, cell multiplication, de-differentiation and differentiation of cells, protoplasts, tissues and organs on defined liquid/solid medium under aseptic and controlled environment. Recent progress in the field of plant tissue culture has made this area one of the most dynamic and promising in experimental biology. There are many published reports on in vitro plant regeneration studies in broccoli including direct organogenesis, indirect organogenesis and somatic embryogenesis. This review summarizes those plant regeneration studies in broccoli that could be helpful in drawing the attention of the researchers and scientists to work on it to produce healthy, biotic and abiotic stress resistant plant material and to carry out genetic transformation studies for the production of transgenic plants.
Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...
2016-11-12
Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA)more » census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi
Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA)more » census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less
USDA-ARS?s Scientific Manuscript database
Improving the water quantity and water quality impacts of corn (Zea mays L.)- and soybean (Glycine max L.)-based cropping systems is a key challenge for agriculture in the US Midwest and similar regions around the world. Long-term field experiments are important for documenting those effects and exp...
USDA-ARS?s Scientific Manuscript database
Bolivia is the poorest country in South America with over 80% of the rural population under the poverty line. Agricultural productivity is closely correlated with poverty levels across rural Bolivia. Potato (Solanum tuberosum L.) is one of the most important crops for food security in Bolivia and th...
NASA Astrophysics Data System (ADS)
Manowitz, D. H.; Schwab, D. E.; Izaurralde, R. C.
2010-12-01
As bioenergy production continues to increase, it is important to be able to predict not only the crop yields that are expected from future production, but also the various environmental impacts that will accompany it. Therefore, models that can be used to make such predictions must be validated against as many of these agricultural outputs as possible. The Environmental Policy Integrated Climate (EPIC) model is a widely used and tested model for simulating many agricultural ecosystem processes including plant growth, crop yield, carbon and nutrient cycling, wind and water erosion, runoff, leaching, as well as changes in soil physical and chemical properties. This model has undergone many improvements, including the addition of a process-based denitrification submodel. Here we evaluate the performance of EPIC in its ability to simulate nitrous oxide (N2O) fluxes and related variables as observed in selected treatments of the Long-Term Ecological Research (LTER) cropping systems study at Kellogg Biological Station (KBS). We will provide a brief description of the EPIC model in the context of bioenergy production, describe the denitrification submodel, and compare simulated and observed values of crop yields, N2O emissions, soil carbon dynamics, and soil moisture.
Saunders, Megan; Glenn, Anthony E; Kohn, Linda M
2010-01-01
All plants, including crop species, harbor a community of fungal endophyte species, yet we know little about the biotic factors that are important in endophyte community assembly. We suggest that the most direct route to understanding the mechanisms underlying community assembly is through the study of functional trait variation in the host and its fungal consortium. We review studies on crop endophytes that investigate plant and fungal traits likely to be important in endophyte community processes. We focus on approaches that could speed detection of general trends in endophyte community assembly: (i) use of the ‘assembly rules’ concept to identify specific mechanisms that influence endophyte community dynamics, (ii) measurement of functional trait variation in plants and fungi to better understand endophyte community processes and plant–fungal interactions, and (iii) investigation of microbe–microbe interactions, and fungal traits that mediate them. This approach is well suited for research in agricultural systems, where pair-wise host–fungus interactions and mechanisms of fungal–fungal competition have frequently been described. Areas for consideration include the possibility that human manipulation of crop phenotype and deployment of fungal biocontrol species can significantly influence endophyte community assembly. Evaluation of endophyte assembly rules may help to fine-tune crop management strategies. PMID:25567944
NASA Astrophysics Data System (ADS)
Piovesan, Mônica; Specht, Alexandre; Carneiro, Eduardo; Paula-Moraes, Silvana Vieira; Casagrande, Mirna Martins
2018-03-01
The identification of factors responsible for the population dynamics is fundamental for pest management, since losses can reach 18% of annual production. Besides regular seasonal environmental factors and crop managements, additional supra-annual meteorological phenomena can also affect population dynamics, although its relevance has been rarely investigated. Among crop pests, Spodoptera stands out due to its worldwide distribution, high degree of polyphagy, thus causing damages in several crops in the world. Aiming to distinguish the relevance of different factors shaping population dynamics of Spodoptera in an ecosystem constituted of dry and rainy seasons, the current study used circular statistics to identify phenological patterns and test if its population fluctuation is driven by El Niño-Southern Oscillation (ENSO) effect, seasonal meteorological parameters, and/or host plant availability. Samplings were done in an intercropping system, in the Brazilian Savanna, during the new moon cycles between July/2013 and June/2016. Species were recorded all year round, but demonstrated differently non-uniform distribution, being concentrated in different seasons of the year. Population fluctuations were mostly affected by the ENSO intensity, despite the contrasting seasonal meteorological variation or host plant availability in a 400-m radius. Studies involving the observation of supra-annual phenomena, although rare, reach similar conclusions in relation to Neotropical insect fauna. Therefore, it is paramount to have long-term sampling studies to obtain a more precise response of the pest populations towards the agroecosystem conditions.
To BECCS or Not To BECCS: A Question of Method
NASA Astrophysics Data System (ADS)
DeCicco, J. M.
2017-12-01
Bioenergy with carbon capture and storage (BECCS) is seen as an important option in many climate stabilization scenarios. Limited demonstrations are underway, including a system that captures and sequesters the fermentation CO2 from ethanol production. However, its net CO2 emissions are uncertain for reasons related to both system characteristics and methodological issues. As for bioenergy in general, evaluations draw on both ecological and engineering methods. It is informative to apply different methods using available data for demonstration systems in comparison to related bioenergy systems. To do so, this paper examines a case study BECCS system and addresses questions regarding the utilization of terrestrial carbon, biomass sustainability and the implications for scalability. The analysis examines four systems, all utilizing the same land area, using two methods. The cases are: A) a crop system without either biofuel production or CCS; B) a biofuel production system without CCS; C) biofuel system with CCS, i.e., the BECCS case, and D) a crop system without biofuel production or CCS but with crop residue removal and conversion to a stable char. In cases A and D, the delivered fuel is fossil-based; in cases B and C the fuel is biomass-based. The first method is LCA, involving steady-flow modeling of systems over a defined lifecycle, following current practice as seen in the attributional LCA component of California's Low-Carbon Fuel Standard (LCFS). The second method involves spatially and temporally explicit analysis, reflecting the dynamics of carbon exchanges with the atmosphere. Although parameters are calibrated to the California LCFS LCA model, simplified spreadsheet modeling is used to maximize transparency while highlighting assumptions that most influence the results. The analysis reveals distinctly different pictures of net CO2 emissions for the cases examined, with the dynamic method painting a less optimistic picture of the BECCS system than the LCA method. Differences in results are traced to differing representations of terrestrial carbon exchanges and associated modeling assumptions. We conclude with suggestions for future work on project- and program-scale carbon accounting methods and the need for caution in advancing BECCS before such methods are better validated.
NASA Astrophysics Data System (ADS)
Löw, Fabian; Biradar, Chandrashekhar; Fliemann, Elisabeth; Lamers, John P. A.; Conrad, Christopher
2017-07-01
Improving crop area and/or crop yields in agricultural regions is one of the foremost scientific challenges for the next decades. This is especially true in irrigated areas because sustainable intensification of irrigated crop production is virtually the sole means to enhance food supply and contribute to meeting food demands of a growing population. Yet, irrigated crop production worldwide is suffering from soil degradation and salinity, reduced soil fertility, and water scarcity rendering the performance of irrigation schemes often below potential. On the other hand, the scope for improving irrigated agricultural productivity remains obscure also due to the lack of spatial data on agricultural production (e.g. crop acreage and yield). To fill this gap, satellite earth observations and a replicable methodology were used to estimate crop yields at the field level for the period 2010/2014 in the Fergana Valley, Central Asia, to understand the response of agricultural productivity to factors related to the irrigation and drainage infrastructure and environment. The results showed that cropping pattern, i.e. the presence or absence of multi-annual crop rotations, and spatial diversity of crops had the most persistent effects on crop yields across observation years suggesting the need for introducing sustainable cropping systems. On the other hand, areas with a lower crop diversity or abundance of crop rotation tended to have lower crop yields, with differences of partly more than one t/ha yield. It is argued that factors related to the infrastructure, for example, the distance of farms to the next settlement or the density of roads, had a persistent effect on crop yield dynamics over time. The improvement potential of cotton and wheat yields were estimated at 5%, compared to crop yields of farms in the direct vicinity of settlements or roads. In this study it is highlighted how remotely sensed estimates of crop production in combination with geospatial technologies provide a unique perspective that, when combined with field surveys, can support planners to identify management priorities for improving regional production and/or reducing environmental impacts.
Maximizing the potential of cropping systems for nematode management.
Noe, J P; Sasser, J N; Imbriani, J L
1991-07-01
Quantitative techniques were used to analyze and determine optimal potential profitability of 3-year rotations of cotton, Gossypium hirsutum cv. Coker 315, and soybean, Glycine max cv. Centennial, with increasing population densities of Hoplolaimus columbus. Data collected from naturally infested on-farm research plots were combined with economic information to construct a microcomputer spreadsheet analysis of the cropping system. Nonlinear mathematical functions were fitted to field data to represent damage functions and population dynamic curves. Maximum yield losses due to H. columbus were estimated to be 20% on cotton and 42% on soybean. Maximum at-harvest population densities were calculated to be 182/100 cm(3) soil for cotton and 149/100 cm(3) soil for soybean. Projected net incomes ranged from a $17.74/ha net loss for the soybean-cotton-soybean sequence to a net profit of $46.80/ha for the cotton-soybean-cotton sequence. The relative profitability of various rotations changed as nematode densities increased, indicating economic thresholds for recommending alternative crop sequences. The utility and power of quantitative optimization was demonstrated for comparisons of rotations under different economic assumptions and with other management alternatives.
Diversified cropping systems support greater microbial cycling and retention of carbon and nitrogen
DOE Office of Scientific and Technical Information (OSTI.GOV)
King, Alison E.; Hofmockel, Kirsten S.
2017-03-01
Diversifying biologically simple cropping systems often entails altering other management practices, such as tillage regime or nitrogen (N) source. We hypothesized that the interaction of crop rotation, N source, and tillage in diversified cropping systems would promote microbially-mediated soil C and N cycling while attenuating inorganic N pools. We studied a cropping systems trial in its 10th year in Iowa, USA, which tested a 2-yr cropping system of corn (Zea mays L.)/soybean [Glycine max (L.) Merr.] managed with conventional fertilizer N inputs and conservation tillage, a 3-yr cropping system of corn/soybean/small grain + red clover (Trifolium pratense L.), and amore » 4-yr cropping system of corn/soybean/small grain + alfalfa (Medicago sativa L.)/alfalfa. Three year and 4-yr cropping systems were managed with composted manure, reduced N fertilizer inputs, and periodic moldboard ploughing. We assayed soil microbial biomass carbon (MBC) and N (MBN), soil extractable NH4 and NO3, gross proteolytic activity of native soil, and potential activity of six hydrolytic enzymes eight times during the growing season. At the 0-20cm depth, native protease activity in the 4-yr cropping system was greater than in the 2-yr cropping system by a factor of 7.9, whereas dissolved inorganic N pools did not differ between cropping systems (P = 0.292). At the 0-20cm depth, MBC and MBN the 4-yr cropping system exceeded those in the 2-yr cropping system by factors of 1.51 and 1.57. Our findings suggest that diversified crop cropping systems, even when periodically moldboard ploughed, support higher levels of microbial biomass, greater production of bioavailable N from SOM, and a deeper microbially active layer than less diverse cropping systems.« less
Lima, Carlos H O; Sarmento, Renato A; Galdino, Tarcísio V S; Pereira, Poliana S; Silva, Joedna; Souza, Danival J; Dos Santos, Gil R; Costa, Thiago L; Picanço, Marcelo C
2018-04-16
Spatiotemporal dynamics studies of crop pests enable the determination of the colonization pattern and dispersion of these insects in the landscape. Geostatistics is an efficient tool for these studies: to determine the spatial distribution pattern of the pest in the crops and to make maps that represent this situation. Analysis of these maps across the development of plants can be used as a tool in precision agriculture programs. Watermelon, Citrullus lanatus (Thunb.) Matsum. and Nakai (Cucurbitales: Cucurbitaceae), is the second most consumed fruit in the world, and the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is one of the most important pests of this crop. Thus, the objective of this work was to determine the spatiotemporal distribution of B. tabaci in commercial watermelon crops using geostatistics. For 2 yr, we monitored adult whitefly densities in eight watermelon crops in a tropical climate region. The location of the samples and other crops in the landscape was georeferenced. Experimental data were submitted to geostatistical analysis. The colonization of B. tabaci had two patterns. In the first, the colonization started at the outermost parts of the crop. In the second, the insects occupied the whole area of the crop since the beginning of cultivation. The maximum distance between sites of watermelon crops in which spatial dependence of B. tabaci densities was observed was 19.69 m. The adult B. tabaci densities in the eight watermelon fields were positively correlated with rainfall and relative humidity, whereas wind speed negatively affected whiteflies population.
USDA-ARS?s Scientific Manuscript database
Alfalfa (Medicago sativa L.) can be strategically planted as a trap crop for Lygus spp. in California’s organic strawberry fields. Alfalfa has been shown to attract both Lygus spp. and, in turn, a Lygus-specific parasitoid, Peristenus relictus (Ruthe). However, the impact of alfalfa trap-cropped st...
Large scale maps of cropping intensity in Asia from MODIS
NASA Astrophysics Data System (ADS)
Gray, J. M.; Friedl, M. A.; Frolking, S. E.; Ramankutty, N.; Nelson, A.
2013-12-01
Agricultural systems are geographically extensive, have profound significance to society, and also affect regional energy, carbon, and water cycles. Since most suitable lands worldwide have been cultivated, there is growing pressure to increase yields on existing agricultural lands. In tropical and sub-tropical regions, multi-cropping is widely used to increase food production, but regional-to-global information related to multi-cropping practices is poor. Such information is of critical importance to ensure sustainable food production while mitigating against negative environmental impacts associated with agriculture such as contamination and depletion of freshwater resources. Unfortunately, currently available large-area inventory statistics are inadequate because they do not capture important spatial patterns in multi-cropping, and are generally not available in a timeframe that can be used to help manage cropping systems. High temporal resolution sensors such as MODIS provide an excellent source of information for addressing this need. However, relative to studies that document agricultural extensification, systematic assessment of agricultural intensification via multi-cropping has received relatively little attention. The goal of this work is to help close this methodological and information gap by developing methods that use multi-temporal remote sensing to map multi-cropping systems in Asia. Image time series analysis is especially challenging in Asia because atmospheric conditions including clouds and aerosols lead to high frequencies of missing or low quality remote sensing observations, especially during the Asian Monsoon. The methodology that we use for this work builds upon the algorithm used to produce the MODIS Land Cover Dynamics product (MCD12Q2), but employs refined methods to segment, smooth, and gap-fill 8-day EVI time series calculated from MODIS BRDF corrected surface reflectances. Crop cycle segments are identified based on changes in slope for linear regressions estimated for local windows, and constrained by the EVI amplitude and length of crop cycles that are identified. The procedure can be used to map seasonal or long-term average cropping strategies, and to characterize changes in cropping intensity over longer time periods. The datasets produced using this method therefore provide information related to global cropping systems, and more broadly, provide important information that is required to ensure sustainable management of Earth's resources and ensure food security. To test our algorithm, we applied it to time series of MODIS EVI images over Asia from 2000-2012. Our results demonstrate the utility of multi-temporal remote sensing for characterizing multi-cropping practices in some of the most important and intensely agricultural regions in the world. To evaluate our approach, we compared results from MODIS to field-scale survey data at the pixel scale, and agricultural inventory statistics at sub-national scales. We then mapped changes in multi-cropped area in Asia from the early MODIS period (2001-2004) to present (2009-2012), and characterizes the magnitude and location of changes in cropping intensity over the last 12 years. We conclude with a discussion of the challenges, future improvements, and broader impacts of this work.
Yun, Lei; Bi, Hua-Xing; Tian, Xiao-Ling; Cui, Zhe-Wei; Zhou, Hui-Zi; Gao, Lu-Bo; Liu, Li-Xia
2011-05-01
Taking the four typical fruit-crop intercropping models, i.e., walnut-peanut, walnut-soybean, apple-peanut, and apple-soybean, in the Loess Region of western Shanxi Province as the objects, this paper analyzed the crop (peanut and soybean) photosynthetic active radiation (PAR), net photosynthetic rate (P(n)), yield, and soil moisture content. Comparing with crop monoculture, fruit-crop intercropping decreased the crop PAR and P(n). The smaller the distance from tree rows, the smaller the crop PAR and P(n). There was a significantly positive correlation between the P(n) and crop yield, suggesting that illumination was one of the key factors affecting crop yield. From the whole trend, the 0-100 cm soil moisture content had no significant differences between walnut-crop intercropping systems and corresponding monoculture cropping systems, but had significant differences between apple-crop intercropping systems and corresponding monoculture cropping systems, indicating that the competition for soil moisture was more intense in apple-crop intercropping systems than in walnut-crop intercropping systems. Comparing with monoculture, fruit-crop intercropping increased the land use efficiency and economic benefit averagely by 70% and 14%, respectively, and walnut-crop intercropping was much better than apple-crop intercropping. To increase the crop yield in fruit-crop intercropping systems, the following strategies should be taken: strengthening the management of irrigation and fertilization, increasing the distances or setting root barriers between crop and tree rows, regularly and properly pruning, and planting shade-tolerant crops in intercropping.
Cover crops support ecological intensification of arable cropping systems
NASA Astrophysics Data System (ADS)
Wittwer, Raphaël A.; Dorn, Brigitte; Jossi, Werner; van der Heijden, Marcel G. A.
2017-02-01
A major challenge for agriculture is to enhance productivity with minimum impact on the environment. Several studies indicate that cover crops could replace anthropogenic inputs and enhance crop productivity. However, so far, it is unclear if cover crop effects vary between different cropping systems, and direct comparisons among major arable production systems are rare. Here we compared the short-term effects of various cover crops on crop yield, nitrogen uptake, and weed infestation in four arable production systems (conventional cropping with intensive tillage and no-tillage; organic cropping with intensive tillage and reduced tillage). We hypothesized that cover cropping effects increase with decreasing management intensity. Our study demonstrated that cover crop effects on crop yield were highest in the organic system with reduced tillage (+24%), intermediate in the organic system with tillage (+13%) and in the conventional system with no tillage (+8%) and lowest in the conventional system with tillage (+2%). Our results indicate that cover crops are essential to maintaining a certain yield level when soil tillage intensity is reduced (e.g. under conservation agriculture), or when production is converted to organic agriculture. Thus, the inclusion of cover crops provides additional opportunities to increase the yield of lower intensity production systems and contribute to ecological intensification.
The GP problem: quantifying gene-to-phenotype relationships.
Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L
2002-01-01
In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.
Modelling impacts of climate change on arable crop diseases: progress, challenges and applications.
Newbery, Fay; Qi, Aiming; Fitt, Bruce Dl
2016-08-01
Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored. Impact assessments are still concentrated on few crops and few diseases but are beginning to investigate arable crop disease dynamics at the landscape level. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
NASA Astrophysics Data System (ADS)
Berardy, Andrew; Chester, Mikhail V.
2017-03-01
Interdependent systems providing water and energy services are necessary for agriculture. Climate change and increased resource demands are expected to cause frequent and severe strains on these systems. Arizona is especially vulnerable to such strains due to its hot and arid climate. However, its climate enables year-round agricultural production, allowing Arizona to supply most of the country’s winter lettuce and vegetables. In addition to Phoenix and Tucson, cities including El Paso, Las Vegas, Los Angeles, and San Diego rely on Arizona for several types of agricultural products such as animal feed and livestock, meaning that disruptions to Arizona’s agriculture also disrupt food supply chains to at least six major cities. Arizona’s predominately irrigated agriculture relies on water imported through an energy intensive process from water-stressed regions. Most irrigation in Arizona is electricity powered, so failures in energy or water systems can cascade to the food system, creating a food-energy-water (FEW) nexus of vulnerability. We construct a dynamic simulation model of the FEW nexus in Arizona to assess the potential impacts of increasing temperatures and disruptions to energy and water supplies on crop irrigation requirements, on-farm energy use, and yield. We use this model to identify critical points of intersection between energy, water, and agricultural systems and quantify expected increases in resource use and yield loss. Our model is based on threshold temperatures of crops, USDA and US Geological Survey data, Arizona crop budgets, and region-specific literature. We predict that temperature increase above the baseline could decrease yields by up to 12.2% per 1 °C for major Arizona crops and require increased irrigation of about 2.6% per 1 °C. Response to drought varies widely based on crop and phenophase, so we estimate irrigation interruption effects through scenario analysis. We provide an overview of potential adaptation measures farmers can take, and barriers to implementation.
Weed Dynamics during Transition to Conservation Agriculture in Western Kenya Maize Production
Odhiambo, Judith A.; Norton, Urszula; Ashilenje, Dennis; Omondi, Emmanuel C.; Norton, Jay B.
2015-01-01
Weed competition is a significant problem in maize (Zea mays, L.) production in Sub-Saharan Africa. Better understanding of weed management and costs in maize intercropped with beans (Phaseolus vulgaris, L.) during transition to conservation agricultural systems is needed. Changes in weed population and maize growth were assessed for a period of three years at Bungoma where crops are grown twice per year and at Trans-Nzoia where crops are grown once per year. Treatments included three tillage practices: minimum (MT), no-till (NT) and conventional (CT) applied to three cropping systems: continuous maize/bean intercropping (TYPICAL), maize/bean intercropping with relayed mucuna after bean harvest (RELAY) and maize, bean and mucuna planted in a strip intercropping arrangement (STRIP). Herbicides were used in NT, shallow hand hoeing and herbicides were used in MT and deep hoeing with no herbicides were used in CT. Weed and maize performance in the maize phase of each cropping system were assessed at both locations and costs of weed control were estimated at Manor House only. Weed density of grass and forb species declined significantly under MT and NT at Manor House and of grass species only at Mabanga. The greatest declines of more than 50% were observed as early as within one year of the transition to MT and NT in STRIP and TYPICAL cropping systems at Manor House. Transitioning to conservation based systems resulted in a decline of four out of five most dominant weed species. At the same time, no negative impact of MT or NT on maize growth was observed. Corresponding costs of weed management were reduced by $148.40 ha-1 in MT and $149.60 ha-1 in NT compared with CT. In conclusion, farmers can benefit from effective and less expensive weed management alternatives early in the process of transitioning to reduced tillage operations. PMID:26237404
Weed Dynamics during Transition to Conservation Agriculture in Western Kenya Maize Production.
Odhiambo, Judith A; Norton, Urszula; Ashilenje, Dennis; Omondi, Emmanuel C; Norton, Jay B
2015-01-01
Weed competition is a significant problem in maize (Zea mays, L.) production in Sub-Saharan Africa. Better understanding of weed management and costs in maize intercropped with beans (Phaseolus vulgaris, L.) during transition to conservation agricultural systems is needed. Changes in weed population and maize growth were assessed for a period of three years at Bungoma where crops are grown twice per year and at Trans-Nzoia where crops are grown once per year. Treatments included three tillage practices: minimum (MT), no-till (NT) and conventional (CT) applied to three cropping systems: continuous maize/bean intercropping (TYPICAL), maize/bean intercropping with relayed mucuna after bean harvest (RELAY) and maize, bean and mucuna planted in a strip intercropping arrangement (STRIP). Herbicides were used in NT, shallow hand hoeing and herbicides were used in MT and deep hoeing with no herbicides were used in CT. Weed and maize performance in the maize phase of each cropping system were assessed at both locations and costs of weed control were estimated at Manor House only. Weed density of grass and forb species declined significantly under MT and NT at Manor House and of grass species only at Mabanga. The greatest declines of more than 50% were observed as early as within one year of the transition to MT and NT in STRIP and TYPICAL cropping systems at Manor House. Transitioning to conservation based systems resulted in a decline of four out of five most dominant weed species. At the same time, no negative impact of MT or NT on maize growth was observed. Corresponding costs of weed management were reduced by $148.40 ha(-1) in MT and $149.60 ha(-1) in NT compared with CT. In conclusion, farmers can benefit from effective and less expensive weed management alternatives early in the process of transitioning to reduced tillage operations.
Climate change and world food supply, demand, and trade
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fischer, G.; Frohberg, K.; Parry, M.L.
This chapter summarizes the findings of a major interdisciplinary research effort by scientists in 25 countries. The study examined the potential biophysical responses of major food crops to changing atmospheric composition and climate, and projected potential socio-economic consequences. In a first step, crop models were used to estimate how changing climatic conditions may alter yields of major crops at a number of sites representing both major production areas and vulnerable regions at low, mid, and high latitudes. Then socio-economic impacts were assessed for the period 1990 up to the Year 2060 with a dynamic recursive model of the world foodmore » system. The results of the assessment suggest that a doubling of the atmospheric CO{sub 2} concentration will have little effect on global food production levels. Globally, impacts on crop production will be small compared to the required production increases between now and the middle of the next century. But, under all simulated scenarios possible negative impacts were mostly observed in low latitudes thus tending to increase the disparity between developed and developing countries.« less
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.
NASA Astrophysics Data System (ADS)
Bartholomeus, Ruud; van den Eertwegh, Gé; Simons, Gijs
2015-04-01
Agricultural crop yields depend largely on the soil moisture conditions in the root zone. Drought but especially an excess of water in the root zone and herewith limited availability of soil oxygen reduces crop yield. With ongoing climate change, more prolonged dry periods alternate with more intensive rainfall events, which changes soil moisture dynamics. With unaltered water management practices, reduced crop yield due to both drought stress and waterlogging will increase. Therefore, both farmers and water management authorities need to be provided with opportunities to reduce risks of decreasing crop yields. In The Netherlands, agricultural production of crops represents a market exceeding 2 billion euros annually. Given the increased variability in meteorological conditions and the resulting larger variations in soil moisture contents, it is of large economic importance to provide farmers and water management authorities with tools to mitigate risks of reduced crop yield by anticipatory water management, both at field and at regional scale. We provide the development and the field application of a decision support system (DSS), which allows to optimize crop yield by timely anticipation on drought and waterlogging situations. By using this DSS, we will minimize plant water stress through automated drainage and irrigation management. In order to optimize soil moisture conditions for crop growth, the interacting processes in the soil-plant-atmosphere system need to be considered explicitly. Our study comprises both the set-up and application of the DSS on a pilot plot in The Netherlands, in order to evaluate its implementation into daily agricultural practice. The DSS focusses on anticipatory water management at the field scale, i.e. the unit scale of interest to a farmer. We combine parallel field measurements ('observe'), process-based model simulations ('predict'), and the novel Climate Adaptive Drainage (CAD) system ('adjust') to optimize soil moisture conditions. CAD is used both for controlled drainage practices and for sub-irrigation. The DSS has a core of the plot-scale SWAP model (soil-water-atmosphere-plant), extended with a process-based module for the simulation of oxygen stress for plant roots. This module involves macro-scale and micro-scale gas diffusion, as well as the plant physiological demand of oxygen, to simulate transpiration reduction due to limited oxygen availability. Continuous measurements of soil moisture content, groundwater level, and drainage level are used to calibrate the SWAP model each day. This leads to an optimal reproduction of the actual soil moisture conditions by data assimilation in the first step in the DSS process. During the next step, near-future (+10 days) soil moisture conditions and drought and oxygen stress are predicted using weather forecasts. Finally, optimal drainage levels to minimize stress are simulated, which can be established by CAD. Linkage to a grid-based hydrological simulation model (SPHY) facilitates studying the spatial dynamics of soil moisture and associated implications for management at the regional scale. Thus, by using local-scale measurements, process-based models and weather forecasts to anticipate on near-future conditions, not only field-scale water management but also regional surface water management can be optimized both in space and time.
NASA Astrophysics Data System (ADS)
Grandy, S.
2013-12-01
Plant diversity is known to strongly influence aboveground ecosystem functions, but our understanding of its effects on belowground carbon (C) cycling has not kept pace. We know in broad terms that the belowground implications of reducing plant diversity include changes in soil nutrient cycling and biological communities, but remain uncertain about the specific links between plant diversity, soil microbial communities, and soil C cycling. Our knowledge gap is especially wide in agricultural systems, which comprise ~50% of the contiguous U.S. and differ from non-managed systems because diversity: (1) occurs primarily over time (i.e. crop rotations) rather than in space (i.e. inter-cropping); (2) exists as one of multiple management factors that potentially regulates soil C dynamics; and (3) is almost always low, with the addition or subtraction of a single plant species often representing a substantial change in diversity. I have been addressing the uncertain relationships between agricultural plant diversity and soil C cycling with a multi-tiered approach that includes a global meta-analysis, site-specific field manipulations, and intensive laboratory analyses. The meta-analysis using 122 studies shows that compared to single-crop monocultures, rotations increased soil microbial biomass C by 20.7% and microbial biomass N by 26.1% as well as total soil C and N. In a complimentary field study at the W.K. Kellogg Biological Station LTER Cropping Biodiversity Gradient Experiment we examined microbial communities, C cycling processes, and trace gas emissions in five rotation sequences varying in complexity from continuous corn monoculture to a five crop three-year rotation. Finding striking differences between monocultures and systems with more complex plant communities, these results confirm our meta-analysis, and highlight the strong effects of diversifying plant communities in agricultural systems. A complimentary lab study examining decomposition processes in monocultures and more diverse rotations shows that rotation soils process chemically complex C more rapidly. My studies point to complex relationships between the chemistry of substrate inputs and their fate in soils, while also emphasizing an important management consideration: maintaining soil biological functions and ecosystem services in managed agricultural systems requires the rotation of different crops, rather than the production of single crop monocultures.
NASA Astrophysics Data System (ADS)
Melati, Dian N.; Nengah Surati Jaya, I.; Pérez-Cruzado, César; Zuhdi, Muhammad; Fehrmann, Lutz; Magdon, Paul; Kleinn, Christoph
2015-04-01
Land use/land cover (LULC) in forested tropical landscapes is very dynamically developing. In particular, the pace of forest conversion in the tropics is a global concern as it directly impacts the global carbon cycle and biodiversity conservation. Expansion of agriculture is known to be among the major drivers of forest loss especially in the tropics. This is also the case in Jambi Province, Sumatra, Indonesia where it is the mainly expansion of tree crops that triggers deforestation: oil palm and rubber trees. Another transformation system in Jambi is the one from natural forest into jungle rubber, which is an agroforestry system where a certain density of forest trees accompanies the rubber tree crop, also for production of wood and non-wood forest products. The spatial distribution and the dynamics of these transformation systems and of the remaining forests are essential information for example for further research on ecosystem services and on the drivers of land transformation. In order to study land transformation, maps from the years 1990, 2000, 2011, and 2013 were utilized, derived from visual interpretation of Landsat images. From these maps, we analyze the land use/land cover change (LULCC) in the study region. It is found that secondary dryland forest (on mineral soils) and secondary swamp forest have been transformed largely into (temporary) shrub land, plantation forests, mixed dryland agriculture, bare lands and estate crops where the latter include the oil palm and rubber plantations. In addition, we present some analyses of the spatial pattern of land transformation to better understand the process of LULC fragmentation within the studied periods. Furthermore, the driving forces are analyzed.
Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images
NASA Astrophysics Data System (ADS)
Shang, Jiali; Liu, Jiangui; Huffman, Ted; Qian, Budong; Pattey, Elizabeth; Wang, Jinfei; Zhao, Ting; Geng, Xiaoyuan; Kroetsch, David; Dong, Taifeng; Lantz, Nicholas
2014-01-01
This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping within-field variability of crop growth conditions and tracking the seasonal growth dynamics. The study was carried out in southern Ontario, Canada, during the 2013 growing season for three annual crops, corn, soybeans, and winter wheat. Plant area index (PAI) was measured at different growth stages using digital hemispherical photography at two corn fields, two winter wheat fields, and two soybean fields. Comparison between several conventional vegetation indices derived from concurrently acquired image data by the two sensors showed a good agreement. The two-band enhanced vegetation index (EVI2) and the normalized difference vegetation index (NDVI) were derived from the surface reflectance of the two sensors. The study showed that EVI2 was more resistant to saturation at high biomass range than NDVI. A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R2) of 0.85 and root-mean-square error of 0.53. The estimated multitemporal product of green PAI was found to be able to capture the seasonal dynamics of the three crops.
Applying a particle filtering technique for canola crop growth stage estimation in Canada
NASA Astrophysics Data System (ADS)
Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi
2017-10-01
Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.
NASA Astrophysics Data System (ADS)
Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.
2014-04-01
The complex interactions and feedbacks between humans and water are very essential issues but are poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable to improve our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed for the Tarim River Basin in Western China, and is used to illustrate the explanatory power of such a model. The study area is the mainstream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four parts, i.e. social sub-system, economic sub-system, ecological sub-system, and hydrological sub-system. In each modeling unit, four coupled ordinary differential equations are used to simulate the dynamics of the social sub-system represented by human population, the economic sub-system represented by irrigated crop area, the ecological sub-system represented by natural vegetation cover and the hydrological sub-system represented by stream discharge. The coupling and feedback processes of the four dominant sub-systems (and correspondingly four state variables) are integrated into several internal system characteristics interactively and jointly determined by themselves and by other coupled systems. For example, the stream discharge is coupled to the irrigated crop area by the colonization rate and mortality rate of the irrigated crop area in the upper reach and the irrigated area is coupled to stream discharge through irrigation water consumption. In a similar way, the stream discharge and natural vegetation cover are coupled together. The irrigated crop area is coupled to human population by the colonization rate and mortality rate of the population. The inflow of the lower reach is determined by the outflow from the upper reach. The natural vegetation cover in the lower reach is coupled to the outflow from the upper reach and governed by regional water resources management policy. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. In the modeling framework, the state of each subsystem is holistically described by one state variable and the framework is flexible enough to comprise more processes and constitutive relationships if they are needed to illustrate the interaction and feedback mechanisms of the human-water system.
Effects of elevated CO2 on fine root dynamics in a Mojave Desert community: A FACE study
Phillips, D.L.; Johnson, M.G.; Tingey, D.T.; Catricala, C.E.; Hoyman, T.L.; Nowak, R.S.
2006-01-01
Fine roots (??? 1mm diameter) are critical in plant water and nutrient absorption, and it is important to understand how rising atmospheric CO2 will affect them as part of terrestrial ecosystem responses to global change. This study's objective was to determine effects of elevated CO2 on production, mortality, and standing crops of fine root length over 2 years in a free-air CO2 enrichment (FACE) facility in the Mojave Desert of southern Nevada, USA. Three replicate 25m diameter FACE rings were maintained at ambient (??? 370 ??mol mol-1) and elevated CO2 (??? 550 ??mol mol-1) atmospheric concentrations. Twenty-eight minirhizotron tubes were placed in each ring to sample three microsite locations: evergreen Larrea shrubs, drought-deciduous Ambrosia shrubs, and along systematic community transects (primarily in shrub interspaces which account for ??? 85% of the area). Seasonal dynamics were similar for ambient and elevated CO2: fine root production peaked in April-June, with peak standing crop occurring about 1 month later, and peak mortality occurring during the hot summer months, with higher values for all three measures in a wet year compared with a dry year. Fine root standing crop, production, and mortality were not significantly different between treatments except standing crop along community transects, where fine root length was significantly lower in elevated CO2. Fine root turnover (annual cumulative mortality/mean standing crop) ranged from 2.33 to 3.17 year-1, and was not significantly different among CO2 treatments, except for community transect tubes where it was significantly lower for elevated CO2. There were no differences in fine root responses to CO2 between evergreen (Larrea) and drought-deciduous (Ambrosia) shrubs. Combined with observations of increased leaf-level water-use efficiency and lack of soil moisture differences, these results suggest that under elevated CO2 conditions, reduced root systems (compared with ambient CO2) appear sufficient to provide resources for modest aboveground production increases across the community, but in more fertile shrub microsites, fine root systems of comparable size with those in ambient CO2 were required to support the greater aboveground production increases. For community transects, development of the difference in fine root standing crops occurred primarily through lower stimulation of fine root production in the elevated CO2 treatment during periods of high water availability. ?? 2005 Blackwell Publishing Ltd.
Atmospheric dynamics in Laboratory Biosphere with wheat and sweet potato crops
NASA Astrophysics Data System (ADS)
Dempster, W. F.; Allen, J. P.; Alling, A.; Nelson, M.; Silvertone, S.; van Thillo, M.
Laboratory Biosphere is a 40 m3 closed life system equipped with 12000 watts of high pressure sodium lamps over planting beds with 5.37 m2 of soil. Atmospheric composition changes due to photosynthetic fixation of carbon dioxide and corresponding production of oxygen or the reverse, respiration, are observed in short timeframes, eg. hourly. To focus on inherent characteristics of the crop as distinct from its area or the volume of the chamber, we report fixation and respiration rates in millimoles per hour per square meter of planted area. An 85 day crop of USU Apogee wheat under a 16 hour lighted / 8 hour dark regime peaked in fixation rate at about 100 mmol h-1 m-2 approximately 24 days after planting. Light intensity was about 840 mol m-2 s-1. Dark respiration peaked at about 31 mmol h-1 m-2 at the same time. Thereafter, both fixation and respiration declined toward zero as harvest time approached. A residual soil respiration rate of about 1.9 mmol h-1 m-2 was observed in the dark closed chamber for 100 days after the harvest. A 126 day crop of Tuskegee TU-82-155 sweet potato behaved quite differently. Under a 680 mol m-2 s-1, 18 hour lighted / 6 hour dark regime, fixation during lighted hours rose to a plateau ranging from about 27 to 48 mmol h-1 m-2 after 42 days and respiration settled into a range of 12 to 23 mmol h-1 m-2. These rates continued unabated until the harvest at 126 days, suggesting that tuber biomass production might have continued at about the same rate for some time beyond the harvest time that was exercised in this experiment. In both experiments CO2 levels were allowed to range widely from a few hundred ppm to about 3000 ppm, which permitted observation of fixation rates both at varying CO2 concentrations and at each number of days after planting. This enables plotting the fixation rate as a function of both variables. Understanding the atmospheric dynamics of individual crops will be essential for design and atmospheric management of more complex CES which integrate the simultaneous growth of several crops as in a sustainable remote life support system.
Atmospheric dynamics in the “Laboratory Biosphere” with wheat and sweet potato crops
NASA Astrophysics Data System (ADS)
Dempster, William F.; Allen, J. P.; Alling, A.; Silverstone, S.; Van Thillo, M.
Laboratory Biosphere is a 40-m 3 closed life system equipped with 12,000 W of high pressure sodium lamps over planting beds with 5.37 m 2 of soil. Atmospheric composition changes due to photosynthetic fixation of carbon dioxide and corresponding production of oxygen or the reverse, respiration, are observed in short timeframes, e.g., hourly. To focus on inherent characteristics of the crop as distinct from its area or the volume of the chamber, we report fixation and respiration rates in mmol h -1 m -2 of planted area. An 85-day crop of USU Apogee wheat under a 16-h lighted/8-h dark regime peaked in fixation rate at about 100 mmol h -1 m -2 approximately 24 days after planting. Light intensity was about 840 μmol m -2 s -1. Dark respiration peaked at about 31 mmol h -1 m -2 at the same time. Thereafter, both fixation and respiration declined toward zero as harvest time approached. A residual soil respiration rate of about 1.9 mmol h -1 m -2 was observed in the dark closed chamber for 100 days after the harvest. A 126-day crop of Tuskegee TU-82-155 sweet potato behaved quite differently. Under a 680 μmol m -2 s -1, 18-h lighted/6-h dark regime, fixation during lighted hours rose to a plateau ranging from about 27 to 48 mmol h -1 m -2 after 42 days and dark respiration settled into a range of 12-23 mmol h -1 m -2. These rates continued unabated until the harvest at 126 days, suggesting that tuber biomass production might have continued at about the same rate for some time beyond the harvest time that was exercised in this experiment. In both experiments CO 2 levels were allowed to range widely from a few hundred to about 3000 ppm, which permitted observation of fixation rates both at varying CO 2 concentrations and at each number of days after planting. This enables plotting the fixation rate as a function of both variables. Understanding the atmospheric dynamics of individual crops will be essential for design and atmospheric management of more complex CELSS which integrate the simultaneous growth of several crops as in a sustainable remote life support system.
Sun, Jing; Wu, Wenbin; Tang, Huajun; Liu, Jianguo
2015-01-01
Despite heated debates over the safety of genetically modified (GM) food, GM crops have been expanding rapidly. Much research has focused on the expansion of GM crops. However, the spatiotemporal dynamics of non-genetically modified (non-GM) crops are not clear, although they may have significant environmental and agronomic impacts and important policy implications. To understand the dynamics of non-GM crops and to inform the debates among relevant stakeholders, we conducted spatiotemporal analyses of China’s major non-GM soybean production region, the Heilongjiang Province. Even though the total soybean planting area decreased from 2005 to 2010, surprisingly, there were hotspots of increase. The results also showed hotspots of loss as well as a large decline in the number and continuity of soybean plots. Since China is the largest non-GM soybean producer in the world, the decline of its major production region may signal the continual decline of global non-GM soybeans. PMID:26380899
Sun, Jing; Wu, Wenbin; Tang, Huajun; Liu, Jianguo
2015-09-18
Despite heated debates over the safety of genetically modified (GM) food, GM crops have been expanding rapidly. Much research has focused on the expansion of GM crops. However, the spatiotemporal dynamics of non-genetically modified (non-GM) crops are not clear, although they may have significant environmental and agronomic impacts and important policy implications. To understand the dynamics of non-GM crops and to inform the debates among relevant stakeholders, we conducted spatiotemporal analyses of China's major non-GM soybean production region, the Heilongjiang Province. Even though the total soybean planting area decreased from 2005 to 2010, surprisingly, there were hotspots of increase. The results also showed hotspots of loss as well as a large decline in the number and continuity of soybean plots. Since China is the largest non-GM soybean producer in the world, the decline of its major production region may signal the continual decline of global non-GM soybeans.
NASA Astrophysics Data System (ADS)
Battisti, R.; Sentelhas, P. C.; Boote, K. J.
2017-12-01
Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.
NASA Astrophysics Data System (ADS)
Battisti, R.; Sentelhas, P. C.; Boote, K. J.
2018-05-01
Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.
A management information system to study space diets
NASA Technical Reports Server (NTRS)
Kang, Sukwon; Both, A. J.; Janes, H. W. (Principal Investigator)
2002-01-01
A management information system (MIS), including a database management system (DBMS) and a decision support system (DSS), was developed to dynamically analyze the variable nutritional content of foods grown and prepared in an Advanced Life Support System (ALSS) such as required for long-duration space missions. The DBMS was designed around the known nutritional content of a list of candidate crops and their prepared foods. The DSS was designed to determine the composition of the daily crew diet based on crop and nutritional information stored in the DBMS. Each of the selected food items was assumed to be harvested from a yet-to-be designed ALSS biomass production subsystem and further prepared in accompanying food preparation subsystems. The developed DBMS allows for the analysis of the nutrient composition of a sample 20-day diet for future Advanced Life Support missions and is able to determine the required quantities of food needed to satisfy the crew's daily consumption. In addition, based on published crop growth rates, the DBMS was able to calculate the required size of the biomass production area needed to satisfy the daily food requirements for the crew. Results from this study can be used to help design future ALSS for which the integration of various subsystems (e.g., biomass production, food preparation and consumption, and waste processing) is paramount for the success of the mission.
A management information system to study space diets.
Kang, Sukwon; Both, A J
2002-01-01
A management information system (MIS), including a database management system (DBMS) and a decision support system (DSS), was developed to dynamically analyze the variable nutritional content of foods grown and prepared in an Advanced Life Support System (ALSS) such as required for long-duration space missions. The DBMS was designed around the known nutritional content of a list of candidate crops and their prepared foods. The DSS was designed to determine the composition of the daily crew diet based on crop and nutritional information stored in the DBMS. Each of the selected food items was assumed to be harvested from a yet-to-be designed ALSS biomass production subsystem and further prepared in accompanying food preparation subsystems. The developed DBMS allows for the analysis of the nutrient composition of a sample 20-day diet for future Advanced Life Support missions and is able to determine the required quantities of food needed to satisfy the crew's daily consumption. In addition, based on published crop growth rates, the DBMS was able to calculate the required size of the biomass production area needed to satisfy the daily food requirements for the crew. Results from this study can be used to help design future ALSS for which the integration of various subsystems (e.g., biomass production, food preparation and consumption, and waste processing) is paramount for the success of the mission.
Embedding an evolving agricultural system within a water resources planning model
NASA Astrophysics Data System (ADS)
Young, C.; Joyce, B.; Purkey, D.; Dale, L.; Mehta, V.
2008-12-01
The Water Evaluation and Planning (WEAP) system is a comprehensive, fully integrated water basin analysis tool. It is a simulation model that includes a robust and flexible representation of water demands from all sectors and flexible, programmable operating rules for infrastructure elements such as reservoirs, canals, and hydropower projects. Additionally, it has watershed rainfall-runoff modeling capabilities that allow all portions of the water infrastructure and demand to be dynamically nested within the underlying hydrological processes. WEAP also allows for linking with other models to provide feedback mechanisms whereby the management regime can be altered to respond to changing water supply conditions. This study presents an application wherein the year-to-year cropping decisions of farmers in California's Central Valley are reactive to changes in water supply conditions. To capture this dynamic, we have included in WEAP a link to an agricultural economics model (the Central Valley Production Model) that relates cropping decisions to water supply conditions (surface water allocations and depth to groundwater) and economic considerations (cost of electricity) at the time of planting. This linked model was used to evaluate changes in water supply and demand in the context of projected climate change over the next century.
NASA Astrophysics Data System (ADS)
Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang
2017-10-01
The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.
Chouchane, Hatem; Krol, Maarten S; Hoekstra, Arjen Y
2018-02-01
Growing water demands put increasing pressure on local water resources, especially in water-short countries. Virtual water trade can play a key role in filling the gap between local demand and supply of water-intensive commodities. This study aims to analyse the dynamics in virtual water trade of Tunisia in relation to environmental and socio-economic factors such as GDP, irrigated land, precipitation, population and water scarcity. The water footprint of crop production is estimated using AquaCrop for six crops over the period 1981-2010. Net virtual water import (NVWI) is quantified at yearly basis. Regression models are used to investigate dynamics in NVWI in relation to the selected factors. The results show that NVWI during the study period for the selected crops is not influenced by blue water scarcity. NVWI correlates in two alternative models to either population and precipitation (model I) or to GDP and irrigated area (model II). The models are better in explaining NVWI of staple crops (wheat, barley, potatoes) than NVWI of cash crops (dates, olives, tomatoes). Using model I, we are able to explain both trends and inter-annual variability for rain-fed crops. Model II performs better for irrigated crops and is able to explain trends significantly; no significant relation is found, however, with variables hypothesized to represent inter-annual variability. Copyright © 2017 Elsevier B.V. All rights reserved.
Zhou, Xingang; Wang, Zhilin; Jia, Huiting; Li, Li; Wu, Fengzhi
2018-01-01
Soil microbial communities have profound effects on the growth, nutrition and health of plants in agroecosystems. Understanding soil microbial dynamics in cropping systems can assist in determining how agricultural practices influence soil processes mediated by microorganisms. In this study, soil bacterial communities were monitored in a continuously monocropped Jerusalem artichoke (JA) system, in which JA was successively monocropped for 3 years in a wheat field. Soil bacterial community compositions were estimated by amplicon sequencing of the 16S rRNA gene. Abundances of ammonia-oxidizing and denitrifying bacteria were estimated by quantitative PCR analysis of the amoA , nirS , and nirK genes. Results showed that 1-2 years of monocropping of JA did not significantly impact the microbial alpha diversity, and the third cropping of JA decreased the microbial alpha diversity ( P < 0.05). Principal coordinates analysis and permutational multivariate analysis of variance analyses revealed that continuous monocropping of JA changed soil bacterial community structure and function profile ( P < 0.001). At the phylum level, the wheat field was characterized with higher relative abundances of Latescibacteria , Planctomycetes , and Cyanobacteria , the first cropping of JA with Actinobacteria , the second cropping of JA with Acidobacteria , Armatimonadetes , Gemmatimonadetes , and Proteobacteria . At the genus level, the first cropping of JA was enriched with bacterial species with pathogen-antagonistic and/or plant growth promoting potentials, while members of genera that included potential denitrifiers increased in the second and third cropping of JA. The first cropping of JA had higher relative abundances of KO terms related to lignocellulose degradation and phosphorus cycling, the second cropping of JA had higher relative abundances of KO terms nitrous-oxide reductase and nitric-oxide reductase, and the third cropping of JA had higher relative abundances of KO terms nitrate reductase and nitrite reductase. The abundances of amoA genes decreased while nirK increased in the third cropping of JA, nirS continuously increased in the second and third cropping of JA ( P < 0.05). Redundancy analysis and Mantel test found that soil organic carbon and Olsen phosphorus contents played important roles in shaping soil bacterial communities. Overall, our results revealed that continuous monocropping of JA changed soil bacterial community composition and its functional potentials.
NASA Technical Reports Server (NTRS)
Blackwell, C. C.; Blackwell, A. L.
1992-01-01
The details of our initial study of the control problem of the crop shoot environment of a hypothetical closed crop growth research chamber (CGRC) are presented in this report. The configuration of the CGRC is hypothetical because neither a physical subject nor a design existed at the time the study began, a circumstance which is typical of large scale systems control studies. The basis of the control study is a mathematical model which was judged to adequately mimic the relevant dynamics of the system components considered necessary to provide acceptable realism in the representation. Control of pressure, temperature, and flow rate of the crop shoot environment, along with its oxygen, carbon dioxide, and water concentration is addressed. To account for mass exchange, the group of plants is represented in the model by a source of oxygen, a source of water vapor, and a sink for carbon dioxide. In terms of the thermal energy exchange, the group of plants is represented by a surface with an appropriate temperature. Most of the primitive equations about an experimental operating condition and a state variable representation which was extracted from the linearized equations are presented. Next, we present the results of a real Jordan decomposition and the repositioning of an undesirable eigenvalue via full state feedback. The state variable representation of the modeling system is of the nineteenth order and reflects the eleven control variables and eight system disturbances. Five real eigenvalues are very near zero, with one at zero, three having small magnitude positive values, and one having a small magnitude negative value. A Singular Value Decomposition analysis indicates that these non-zero eigenvalues are not results of numerical error.
NASA Astrophysics Data System (ADS)
Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.
2014-12-01
China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.
Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale1[W][OPEN
Grafahrend-Belau, Eva; Junker, Astrid; Eschenröder, André; Müller, Johannes; Schreiber, Falk; Junker, Björn H.
2013-01-01
Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement. PMID:23926077
Chen, Mingna; Li, Xiao; Yang, Qingli; Chi, Xiaoyuan; Pan, Lijuan; Chen, Na; Yang, Zhen; Wang, Tong; Wang, Mian; Yu, Shanlin
2014-01-01
Plant health and soil fertility are affected by plant–microbial interactions in soils. Peanut is an important oil crop worldwide and shows considerable adaptability, but growth and yield are negatively affected by continuous cropping. In this study, 16S rRNA gene clone library analyses were used to study the succession of soil bacterial communities under continuous peanut cultivation. Six libraries were constructed for peanut over three continuous cropping cycles and during its seedling and pod-maturing growth stages. Cluster analyses indicated that soil bacterial assemblages obtained from the same peanut cropping cycle were similar, regardless of growth period. The diversity of bacterial sequences identified in each growth stage library of the three peanut cropping cycles was high and these sequences were affiliated with 21 bacterial groups. Eight phyla: Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Gemmatimonadetes, Planctomycetes, Proteobacteria and Verrucomicrobia were dominant. The related bacterial phylotypes dynamic changed during continuous cropping progress of peanut. This study demonstrated that the bacterial populations especially the beneficial populations were positively selected. The simplification of the beneficial microbial communities such as the phylotypes of Alteromonadales, Burkholderiales, Flavobacteriales, Pseudomonadales, Rhizobiales and Rhodospirillales could be important factors contributing to the decline in peanut yield under continuous cropping. The microbial phylotypes that did not successively changed with continuous cropping, such as populations related to Rhizobiales and Rhodospirillales, could potentially resist stress due to continuous cropping and deserve attention. In addition, some phylotypes, such as Acidobacteriales, Chromatiales and Gemmatimonadales, showed a contrary tendency, their abundance or diversity increased with continuous peanut cropping progress. Some bacterial phylotypes including Acidobacteriales, Burkholderiales, Bdellovibrionales, and so on, also were affected by plant age. PMID:25010658
NASA Astrophysics Data System (ADS)
Rojas, Marcela; Malard, Julien; Adamowski, Jan; Carrera, Jaime Luis; Maas, Raúl
2017-04-01
While it is known that climate change will impact future plant-pest population dynamics, potentially affecting crop damage, agroforestry with its enhanced biodiversity is said to reduce the outbreaks of pest insects by providing natural enemies for the control of pest populations. This premise is known in the literature as the natural enemy hypothesis and has been widely studied qualitatively. However, disagreement still exists on whether biodiversity enhancement reduces pest outbreaks, showing the need of quantitatively understanding the mechanisms behind the interactions between pests and natural enemies, also known as trophic interactions. Crop pest models that study insect population dynamics in agroforestry contexts are very rare, and pest models that take trophic interactions into account are even rarer. This may be due to the difficulty of representing complex food webs in a quantifiable model. There is therefore a need for validated food web models that allow users to predict the response of these webs to changes in climate in agroforestry systems. In this study we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web models; the program uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. Tiko'n was run using coffee leaf miner (Leucoptera coffeella) and associated parasitoid data from a shaded coffee plantation, showing the mechanisms of insect population dynamics within a tri-trophic food web in an agroforestry system.
Unveiled Risks in a Telecoupled Arena Dependent on Agricultural Commodity Trade
NASA Astrophysics Data System (ADS)
Batistella, M.; Silva, R. F. B. D.; Liu, J.; Moran, E. F.; Torres, S.; Dou, Y.
2017-12-01
In less than five years, a new field of interdisciplinary research has been widely developed within the coupled human-natural systems (CHANS) community. Based on well-known concepts acting over long distances, such as teleconnections for biophysical sciences and globalization for human sciences, the telecoupling framework states that long distant CHANS may be integrated through flows of capital, information, and matter, shaping environmental and socioeconomic changes within local systems. An international project including researchers from Brazil, China, United Kingdom (UK), and United States of America (USA) is using such a framework to study the flows of agricultural commodities between sending systems such as Brazil and the USA, and receiving systems such as China with soybean trade as a case in point. Many findings have already shown that these dynamics are intrinsically connected and changes in environmental conditions in one system may affect economic conditions in other systems. In the case of the double-crop practice (i.e., soybean followed by maize, two crops year round) used in some regions of Brazil, maize production is strongly connected with soybean production through the supply chain, logistics, producer regions, and farmers. Consequently, maize has been displaced to second-crop status, making it more vulnerable to rain shortfalls. The use of the telecoupling framework has also unveiled a possible threat for soybean production in the long run if it only relies on international demand and inputs. The telecoupled soybean production system has put some Brazilian farmers at economic risk, and is pushing them towards diversification and alternative production practices (e.g., non-GMO crops, biological control, in-farm seed production) to reduce their risk. This, in turn, may affect the demand-consumption relationship among traditional trading partners. With this paper, we also highlight the role of cascading effects and spillover systems of telecoupling in shaping system interconnections and sustainability.
Ranking agricultural practices on soil water improvements: a meta-analysis
NASA Astrophysics Data System (ADS)
Basche, A.; DeLonge, M. S.; Gonzalez, J.
2016-12-01
Increased rainfall variability is well documented in the historic record and predicted to intensify with future climate change. Managing excess water in periods of heavy rain and a lack of water in periods of inadequate precipitation will continue to be a challenge. Improving soil resiliency through increased water storage is a promising strategy to combat effects of both rainfall extremes. The goal of this research is to quantify to what extent various conservation and ecological practices can improve soil hydrology. We are conducting a global meta-analysis focused on studies where conservation and ecological practices are compared to more conventional management. To date we have analyzed 100 studies with more than 450 paired comparisons to understand the effect of management on water infiltration rates, a critical process that ensures water enters the soil profile for crop use, water storage and runoff prevention. The database will be expanded to include studies measuring soil porosity and the water retained at field capacity. Statistical analysis has been done both with both a bootstrap method and a mixed model that weights studies based on precision while accounting for between-study variation. We find that conservation and ecological practices, ranging from no-till, cover crops, crop rotation, perennial crops and agroforestry, on average significantly increased water infiltration rates relative to more conventional practice controls (mean of 75%, standard error 25%). There were significant differences between practices, where perennial and agroforestry systems show the greatest potential for improving water infiltration rates (> 100% increase). Cover crops also lead to a significant increase in water infiltration rates (> 60%) while crop rotations and no-till systems did not consistently demonstrate increases. We also found that studies needed to include alternative management for more than two years to detect a significant increase. Overall this global meta-analysis improves understanding of how alternative management, notably the use of continuous cover in agricultural systems, improves water dynamics. Policies should be designed in a way that allows agricultural producers to prioritize and implement practices that offer greater water conservation while maintaining crop productivity.
Predictive spatial modeling of narcotic crop growth patterns
Waltz, Frederick A.; Moore, D.G.
1986-01-01
Spatial models for predicting the geographic distribution of marijuana crops have been developed and are being evaluated for use in law enforcement programs. The models are based on growing condition preferences and on psychological inferences regarding grower behavior. Experiences of local law officials were used to derive the initial model, which was updated and improved as data from crop finds were archived and statistically analyzed. The predictive models are changed as crop locations are moved in response to the pressures of law enforcement. The models use spatial data in a raster geographic information system. The spatial data are derived from the U.S. Geological Survey's US GeoData, standard 7.5-minute topographic quadrangle maps, interpretations of aerial photographs, and thematic maps. Updating of cultural patterns, canopy closure, and other dynamic features is conducted through interpretation of aerial photographs registered to the 7.5-minute quadrangle base. The model is used to numerically weight various data layers that have been processed using spread functions, edge definition, and categorization. The building of the spatial data base, model development, model application, product generation, and use are collectively referred to as the Area Reduction Program (ARP). The goal of ARP is to provide law enforcement officials with tactical maps that show the most likely locations for narcotic crops.
NASA Astrophysics Data System (ADS)
Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.
2015-11-01
Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us to investigate trade-offs between these ecosystem services that can be provided from agricultural fields. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP (Representative Concentration Pathway) 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles.
NASA Astrophysics Data System (ADS)
Boulain, N.; Cappelaere, B.; Ramier, D.; Issoufou, H. B. A.; Halilou, O.; Seghieri, J.; Guillemin, F.; Oï, M.; Gignoux, J.; Timouk, F.
2009-08-01
SummaryThis paper analyses the dynamics of vegetation and carbon during the West African monsoon season, for millet crop and fallow vegetation covers in the cultivated area of the Sahel. Comparing these two dominant land cover types informs on the impact of cultivation on productivity and carbon fluxes. Biomass, leaf area index (LAI) and carbon fluxes were monitored over a 2-year period for these two vegetation systems in the Wankama catchment of the AMMA (African monsoon multidisciplinary analyses) experimental super-site in West Niger. Carbon fluxes and water use efficiency observed at the field scale are confronted with ecophysiological measurements (photosynthetic response to light, and relation of water use efficiency to air humidity) made at the leaf scale for the dominant plant species in the two vegetation systems. The two rainy seasons monitored were dissimilar with respect to rain patterns, reflecting some of the interannual variability. Distinct responses in vegetation development and in carbon dynamics were observed between the two vegetation systems. Vegetation development in the fallow was found to depend more on rainfall distribution along the season than on its starting date. A quite opposite behaviour was observed for the crop vegetation: the date of first rain appears as a principal factor of millet growth. Carbon flux exchanges were well correlated to vegetation development. High responses of photosynthesis to light were observed for the dominant herbaceous and shrub species of the fallow at the leaf and field scales. Millet showed high response at the leaf scale, but a much lesser response at the field scale. This pattern, also observed for water use efficiency, is to be related to the low density of the millet cover. A simple LAI-based model for scaling up the photosynthetic response from leaf to field scale was found quite successful for the fallow, but was less conclusive for the crop, due to spatial variability of LAI. Time/space variations in leaf distribution for the dominant species are key to scale transition of carbon dynamics. Results obtained for the two vegetation covers are important in light of the major land use/cover change experienced in the Sahel region due to extensive savanna clearing for food production.
The development and status of Bt rice in China.
Li, Yunhe; Hallerman, Eric M; Liu, Qingsong; Wu, Kongming; Peng, Yufa
2016-03-01
Multiple lines of transgenic rice expressing insecticidal genes from the bacterium Bacillus thuringiensis (Bt) have been developed in China, posing the prospect of increases in production with decreased application of pesticides. We explore the issues facing adoption of Bt rice for commercial production in China. A body of safety assessment work on Bt rice has shown that Bt rice poses a negligible risk to the environment and that Bt rice products are as safe as non-Bt control rice products as food. China has a relatively well-developed regulatory system for risk assessment and management of genetically modified (GM) plants; however, decision-making regarding approval of commercial production has become politicized, and two Bt rice lines that otherwise were ready have not been allowed to enter the Chinese agricultural system. We predict that Chinese farmers would value the prospect of increased yield with decreased use of pesticide and would readily adopt production of Bt rice. That Bt rice lines may not be commercialized in the near future we attribute to social pressures, largely due to the low level of understanding and acceptance of GM crops by Chinese consumers. Hence, enhancing communication of GM crop science-related issues to the public is an important, unmet need. While the dynamics of each issue are particular to China, they typify those in many countries where adoption of GM crops has been not been rapid; hence, the assessment of these dynamics might inform resolution of these issues in other countries. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.
Hand-held radiometer red and photographic infrared spectral measurements of agricultural crops
NASA Technical Reports Server (NTRS)
Tucker, C. J.; Fan, C. J.; Elgin, J. H., Jr.; Mcmurtrey, J. E., III
1978-01-01
Red and photographic infrared radiance data, collected under a variety of conditions at weekly intervals throughout the growing season using a hand-held radiometer, were used to monitor crop growth and development. The vegetation index transformation was used to effectively compensate for the different irradiational conditions encountered during the study period. These data, plotted against time, compared the different crops measured by comparing their green leaf biomass dynamics. This approach, based entirely upon spectral inputs, closely monitors crop growth and development and indicates the promise of ground-based hand-held radiometer measurements of crops.
Stagnari, Fabio; Perpetuini, Giorgia; Tofalo, Rosanna; Campanelli, Gabriele; Leteo, Fabrizio; Della Vella, Umberto; Schirone, Maria; Suzzi, Giovanna; Pisante, Michele
2014-01-01
In the present study, long-term organic and conventional managements were compared at the experimental field of Monsampolo del Tronto (Marche region, Italy) with the aim of investigating soil chemical fertility and microbial community structure. A polyphasic approach, combining soil fertility indicators with microbiological analyses (plate counts, PCR-denaturing gradient gel electrophoresis [DGGE] and phospholipid fatty acid analysis [PLFA]) was applied. Organic matter, N as well as some important macro and micronutrients (K, P, Mg, Mn, Cu, and Zn) for crop growth, were more available under organic management. Bacterial counts were higher in organic management. A significant influence of management system and management x crop interaction was observed for total mesophilic bacteria, nitrogen fixing bacteria and actinobacteria. Interestingly, cultivable fungi were not detected in all analyzed samples. PLFA biomass was higher in the organic and Gram positive bacteria dominated the microbial community in both systems. Even if fungal biomass was higher in organic management, fungal PCR-DGGE fingerprinting revealed that the two systems were very similar in terms of fungal species suggesting that 10 years were not enough to establish a new dynamic equilibrium among ecosystem components. A better knowledge of soil biota and in particular of fungal community structure will be useful for the development of sustainable management strategies. PMID:25540640
Microbial Ecology of Soil Aggregation in Agroecosystems
NASA Astrophysics Data System (ADS)
Hofmockel, K. S.; Bell, S.; Tfailly, M.; Thompson, A.; Callister, S.
2017-12-01
Crop selection and soil texture influence the physicochemical attributes of the soil, which structures microbial communities and influences soil C cycling storage. At the molecular scale, microbial metabolites and necromass alter the soil environment, which creates feedbacks that influence ecosystem functions, including soil C accumulation. By integrating lab to field studies we aim to identify the molecules, organisms and metabolic pathways that control carbon cycling and stabilization in bioenergy soils. We investigated the relative influence of plants, microbes, and minerals on soil aggregate ecology at the Great Lakes Bioenergy Research experiment. Sites in WI and MI, USA have been in corn and switchgrass cropping systems for a decade. By comparing soil aggregate ecology across sites and cropping systems we are able to test the relative importance of plant, microbe, mineral influences on soil aggregate dynamics. Soil microbial communities (16S) differ in diversity and phylogeny among sites and cropping systems. FT-ICR MS revealed differences in the molecular composition of water-soluble fraction of soil organic matter for cropping systems and soil origin for both relative abundance of assigned formulas and biogeochemical classes of compounds. We found the degree of aggregation, measured by mean weighted diameter of aggregate fractions, is influenced by plant-soil interactions. Similarly, the proportion of soil aggregate fractions varied by both soil and plant factors. Differences in aggregation were reflected in differences in bacterial, but not fungal community composition across aggregate fractions, within each soil. Scanning electron microscopy revealed stark differences in mineral-organic interactions that influence the microbial niche and the accessibility of substrates within the soil. The clay soils show greater surface heterogeneity, enabling interactions with organic fraction of the soil. This is consistent with molecular data that reveal differences in the abundance of chemical classes in clay loams compared to sandy loams. Together our data demonstrate that the potential for aggregation and C storage is strongly influenced by soil mineralogy with important implications for plant-microbe interactions that mediate C biogeochemistry.
Piriformospora indica: Potential and Significance in Plant Stress Tolerance
Gill, Sarvajeet S.; Gill, Ritu; Trivedi, Dipesh K.; Anjum, Naser A.; Sharma, Krishna K.; Ansari, Mohammed W.; Ansari, Abid A.; Johri, Atul K.; Prasad, Ram; Pereira, Eduarda; Varma, Ajit; Tuteja, Narendra
2016-01-01
Owing to its exceptional ability to efficiently promote plant growth, protection and stress tolerance, a mycorrhiza like endophytic Agaricomycetes fungus Piriformospora indica has received a great attention over the last few decades. P. indica is an axenically cultiviable fungus which exhibits its versatility for colonizing/hosting a broad range of plant species through directly manipulating plant hormone-signaling pathway during the course of mutualism. P. indica-root colonization leads to a better plant performance in all respect, including enhanced root proliferation by indole-3-acetic acid production which in turn results into better nutrient-acquisition and subsequently to improved crop growth and productivity. Additionally, P. indica can induce both local and systemic resistance to fungal and viral plant diseases through signal transduction. P. indica-mediated stimulation in antioxidant defense system components and expressing stress-related genes can confer crop/plant stress tolerance. Therefore, P. indica can biotize micropropagated plantlets and also help these plants to overcome transplantation shock. Nevertheless, it can also be involved in a more complex symbiotic relationship, such as tripartite symbiosis and can enhance population dynamic of plant growth promoting rhizobacteria. In brief, P. indica can be utilized as a plant promoter, bio-fertilizer, bioprotector, bioregulator, and biotization agent. The outcome of the recent literature appraised herein will help us to understand the physiological and molecular bases of mechanisms underlying P. indica-crop plant mutual relationship. Together, the discussion will be functional to comprehend the usefulness of crop plant-P. indica association in both achieving new insights into crop protection/improvement as well as in sustainable agriculture production. PMID:27047458
A framework for standardized calculation of weather indices in Germany
NASA Astrophysics Data System (ADS)
Möller, Markus; Doms, Juliane; Gerstmann, Henning; Feike, Til
2018-05-01
Climate change has been recognized as a main driver in the increasing occurrence of extreme weather. Weather indices (WIs) are used to assess extreme weather conditions regarding its impact on crop yields. Designing WIs is challenging, since complex and dynamic crop-climate relationships have to be considered. As a consequence, geodata for WI calculations have to represent both the spatio-temporal dynamic of crop development and corresponding weather conditions. In this study, we introduce a WI design framework for Germany, which is based on public and open raster data of long-term spatio-temporal availability. The operational process chain enables the dynamic and automatic definition of relevant phenological phases for the main cultivated crops in Germany. Within the temporal bounds, WIs can be calculated for any year and test site in Germany in a reproducible and transparent manner. The workflow is demonstrated on the example of a simple cumulative rainfall index for the phenological phase shooting of winter wheat using 16 test sites and the period between 1994 and 2014. Compared to station-based approaches, the major advantage of our approach is the possibility to design spatial WIs based on raster data characterized by accuracy metrics. Raster data and WIs, which fulfill data quality standards, can contribute to an increased acceptance and farmers' trust in WI products for crop yield modeling or weather index-based insurances (WIIs).
NASA Technical Reports Server (NTRS)
1986-01-01
AGDISP, a computer code written for Langley by Continuum Dynamics, Inc., aids crop dusting airplanes in targeting pesticides. The code is commercially available and can be run on a personal computer by an inexperienced operator. Called SWA+H, it is used by the Forest Service, FAA, DuPont, etc. DuPont uses the code to "test" equipment on the computer using a laser system to measure particle characteristics of various spray compounds.
Model Optimization Planting Pattern Agroforestry Forest Land Based on Pine Tree
ERIC Educational Resources Information Center
Rajati, Tati
2015-01-01
This study aims to determine cropping patterns in class slopes 0 - <15% and the grade slope slopes 15% - <30% and the slopes> 30%. The method used in this study is a description of the dynamic system approach using a software power sim. Forest areas where the research, which is a type of plant that is cultivated by the people in the study…
Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa
NASA Astrophysics Data System (ADS)
Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.
2013-12-01
Agriculture in Sub-Saharan Africa (SSA) drives the economy of many African countries and it is mainly rain-fed agriculture used for subsistence. Increasing temperatures, changed precipitation patterns and more frequent droughts may lead to a substantial decrease of crop yields. The projected impacts of future climate change on agriculture are expected to be significant and extensive in the SSA due to the shortening of the growing seasons and the increasing of water-stress risk. Differences in Agro-Ecological Zones and geographical characteristics of SSA influence the diverse impacts of climate change, which can greatly differ across the continent and within countries. The vulnerability of African Countries to climate change is aggravated by the low adaptive capacity of the continent, due to the increasing of its population, the widespread poverty, and other social factors. In this contest, the assessment of climate change impact on agricultural sector has a particular interest to stakeholder and policy makers, in order to identify specific agricultural sectors and Agro-Ecological Zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in SSA was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management analysis. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT-CSM are tools that allow to simulate physiological process of crop growth, development and production, by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were used, after a parameterization phase, to evaluate climate change impacts on crop phenology and production. Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.
Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes
NASA Astrophysics Data System (ADS)
Chen, Ming; Griffis, Tim J.; Baker, John; Wood, Jeffrey D.; Xiao, Ke
2015-02-01
A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water, and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to Earth system models is relatively rare. Here we evaluated two such models (CLM4-Crop and CLM3.5-CornSoy), both implemented within the Community Land Model (CLM) framework, at two AmeriFlux corn-soybean sites to assess their ability to simulate phenology, energy, and carbon fluxes. Our results indicated that the accuracy of net ecosystem exchange and gross primary production simulations was intimately connected to the phenology simulations. The CLM4-Crop model consistently overestimated early growing season leaf area index, causing an overestimation of gross primary production, to such an extent that the model simulated a carbon sink instead of the measured carbon source for corn. The CLM3.5-CornSoy-simulated leaf area index (LAI), energy, and carbon fluxes showed stronger correlations with observations compared to CLM4-Crop. Net radiation was biased high in both models and was especially pronounced for soybeans. This was primarily caused by the positive LAI bias, which led to a positive net long-wave radiation bias. CLM4-Crop underestimated soil water content during midgrowing season in all soil layers at the two sites, which caused unrealistic water stress, especially for soybean. Future work regarding the mechanisms that drive early growing season phenology and soil water dynamics is needed to better represent crops including their net radiation balance, energy partitioning, and carbon cycle processes.
Battisti, R; Sentelhas, P C; Boote, K J
2018-05-01
Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .
Goswami, Varun R; Medhi, Kamal; Nichols, James D; Oli, Madan K
2015-08-01
Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08-0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human-wildlife interactions. © 2015 Society for Conservation Biology.
Dispersal of Transgenes through Maize Seed Systems in Mexico
Dyer, George A.; Serratos-Hernández, J. Antonio; Perales, Hugo R.; Gepts, Paul; Piñeyro-Nelson, Alma; Chávez, Angeles; Salinas-Arreortua, Noé; Yúnez-Naude, Antonio; Taylor, J. Edward; Alvarez-Buylla, Elena R.
2009-01-01
Objectives Current models of transgene dispersal focus on gene flow via pollen while neglecting seed, a vital vehicle for gene flow in centers of crop origin and diversity. We analyze the dispersal of maize transgenes via seeds in Mexico, the crop's cradle. Methods We use immunoassays (ELISA) to screen for the activity of recombinant proteins in a nationwide sample of farmer seed stocks. We estimate critical parameters of seed population dynamics using household survey data and combine these estimates with analytical results to examine presumed sources and mechanisms of dispersal. Results Recombinant proteins Cry1Ab/Ac and CP4/EPSPS were found in 3.1% and 1.8% of samples, respectively. They are most abundant in southeast Mexico but also present in the west-central region. Diffusion of seed and grain imported from the United States might explain the frequency and distribution of transgenes in west-central Mexico but not in the southeast. Conclusions Understanding the potential for transgene survival and dispersal should help design methods to regulate the diffusion of germplasm into local seed stocks. Further research is needed on the interactions between formal and informal seed systems and grain markets in centers of crop origin and diversification. PMID:19503610
NASA Astrophysics Data System (ADS)
Zaki, M. K.; Furi, N. T.; Syamsiyah, Jauhari; Sumani
2018-03-01
Weather dynamics such as the fifth time of the rainy season and drought are becoming more frequent. These conditions pose a significant impact on the strategies of cultivation such as cropping pattern and crop yields, especially in rainfed areas. One of the steps that can be taken is to return to local wisdom, such as pranata mangsa. This study aimed at analyzing the relationship of the variability of precipitation in rainfed areas with pranata mangsa and then to evaluate cropping patterns based on the result of the analysis. The study was conducted in rainfed areas of the District of Jumantono, Karanganyar Regency; and District of Teras and District of Ampel, Boyolali Regency in June until December 2014. The research method is a descriptive exploratory survey with purposive sampling based on moderate altitude (200-700 masl). The types of data that are used are primary and secondary. Data analysis was used correlation test. The results showed that precipitation in rainfed areas has a close relationship with paranata mangsa. These results explain that pranata mangsa still relevant to be used even though it has happened weather dynamics.
Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data
NASA Astrophysics Data System (ADS)
Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin
2013-04-01
The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the assimilation of the remotely sensed GAI time series. The calibration process led to accurate spatial estimates of GAI, ETR as well as of biomass and yield over the study area (24 km x 24 km window). The results highlight the interest of using a combined approach (crop model coupled with high spatial and temporal resolution remote sensing data) for the estimation of agronomical variables. At local scale, the model reproduced correctly the biomass production and ETR for summer crops (with relative RMSE of 29% and 35%, respectively). At regional scale, estimated yield and water requirement for irrigation were compared to regional statistics of yield and irrigation inventories provided by the local water agency. Results showed good agreements for inter-annual dynamics of yield estimates. Differences between water requirement for irrigation and actual supply were lower than 10% and inter-annual variability was well represented as well. The work, initially focused on summer crops, is being adapted to winter crops.
Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Møller, B. Lindberg; Gleadow, R. M.
2015-01-01
The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator® at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf ‘greenness’ correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants. PMID:25697789
NASA Astrophysics Data System (ADS)
Jha, Prakash K.; Athanasiadis, Panos; Gualdi, Silvio; Trabucco, Antonio; Mereu, Valentina; Shelia, Vakhtang; Hoogenboom, Gerrit
2018-03-01
Ensemble forecasts from dynamic seasonal prediction systems (SPSs) have the potential to improve decision-making for crop management to help cope with interannual weather variability. Because the reliability of crop yield predictions based on seasonal weather forecasts depends on the quality of the forecasts, it is essential to evaluate forecasts prior to agricultural applications. This study analyses the potential of Climate Forecast System version 2 (CFSv2) in predicting the Indian summer monsoon (ISM) for producing meteorological variables relevant to crop modeling. The focus area was Nepal's Terai region, and the local hindcasts were compared with weather station and reanalysis data. The results showed that the CFSv2 model accurately predicts monthly anomalies of daily maximum and minimum air temperature (Tmax and Tmin) as well as incoming total surface solar radiation (Srad). However, the daily climatologies of the respective CFSv2 hindcasts exhibit significant systematic biases compared to weather station data. The CFSv2 is less capable of predicting monthly precipitation anomalies and simulating the respective intra-seasonal variability over the growing season. Nevertheless, the observed daily climatologies of precipitation fall within the ensemble spread of the respective daily climatologies of CFSv2 hindcasts. These limitations in the CFSv2 seasonal forecasts, primarily in precipitation, restrict the potential application for predicting the interannual variability of crop yield associated with weather variability. Despite these limitations, ensemble averaging of the simulated yield using all CFSv2 members after applying bias correction may lead to satisfactory yield predictions.
NASA Astrophysics Data System (ADS)
Monteiro, Filipa; Vidigal, Patricia; Romeiras, Maria Manuel; Ribeiro, Ana; Abreu, Maria Manuela; Viegas, Wanda; Catarino, Luís
2017-04-01
During the last decades, agriculture in West Africa has been marked by dramatic shifts with the coverage of single crops, increasing pressure over the available arable land. Yet, West African countries are still striving to achieve sustainable production at an increased scale for global market needs. Market-driven rapid intensification is often a major cause for cropland area expansion at the expense of deforestation and soil degradation, especially to export commodities in times of high prices. Cashew (Anacardium occidentale L.) is nowadays an important export-oriented crop, being produced under intensive cultivation regimes in several tropical regions. Particularly, among the main cashew production areas, West Africa is the most recent and dynamic in the world, accounting for 45% of the world cashew nuts production in 2015. Considering its global market values, several developing countries rely on cashew nuts as national economy revenues, namely in Guinea-Bissau. Considering the intensive regime of cashew production in Guinea-Bissau, and as widely recognized, intensive agriculture linked with extensification can negatively impact ecosystems, affecting natural resources availability, soil erosion and arability compromised by excessive salinity. Ultimately this will result in the disruption of carbon - nitrogen cycle, important to the agricultural ecosystem sustainability. As such, tree intercropped with legumes as cover crops, offers a sustainable management of the land area, thus creating substantial benefits both economically and environmentally, as it enhances diversification of products outputs and proving to be more sustainable than forestry and/or agricultural monocultures. Soil fertility improvement is a key entry point for achieving food security, and also increment agriculture commodities of the agro-system. Without using inorganic fertilizers, the green solution for improving soil management is to incorporate adapted multi-purpose legumes as cover crops, reducing soil erosion as well as insect pests and associated diseases, while improves the yield of the main crop. The integration of legume in agroforestry systems offers an alternative and resilient strategy to increase N availability without increasing mineral N additions. As such, we present a case study of a forest-based system under intensive agriculture regime and propose an alternative sustainable system - the agroforestry system - by intercropping legumes, thus ensuring the sustainability of a cash crop sector both in terms of food security and soil resources. Results obtained from this case-study will therefore be important to demonstrate the global importance of agroforestry systems as key strategy for land use planning, sustainability of the agricultural systems as well as the preserving the environment of smallholder farms in the sub-Saharan Africa.
NASA Astrophysics Data System (ADS)
Huang, C.; Zhang, L.; Wang, S.; Qiao, N.
2016-12-01
Remotely sensed solar-induced chlorophyll fluorescence (SIF) has been considered an ideal probe in monitoring vegetation photosynthesis. However, numerous challenges have greatly limited its wide applications, including accurate estimate of faint SIF from the observed apparent reflected radiation, uncertainties in inferring the vegetation photosynthesis as well as lack of validation. These difficulties should be resolved at ground-based controlled scales before the launch of SIF satellite platforms such as ESA's FLEX (to be launched 2021). Currently, increasing continuous and long-term automated SIF measurement systems have been reported for better understanding the diurnal and seasonal changes of vegetation photosynthesis. This study introduces a newly developed automated SIF field measurement system (Auto-SIF, 500-800 nm, FWHM=0.74 nm, SSI=0.38 nm, SNR=1000:1, see figure 1) in China and its initial results for inferring photosynthesis of different crops including soybean (three types), maize (two types) and rice (two types). The experiments were conducted at the test crop field affiliated to the Institute of Genetics and Development Biology, Chinese Academy of Sciences. The Auto-SIF incorporates two observation modes, i.e., reference panel mode and target mode (see figure 1), and the two modes can be switched very quickly through an electrical motor. All diurnal super-spectra data and SIFs of crops were collected in clear days and with a finer time interval of 1minute, therefore they can be easily resampled to different time intervals (see figure 2) in order for convenient comparisons with other data from different observation platforms, like 30-minute tower-flux GPP data. For better understanding of crop photosynthesis, Li-6400 XT (LI-COR, Inc.) and TES-1339R light meter were respectively used in this study to simultaneously obtain diurnal dynamics of leaf-level SIFs and sun incoming flux. Due to the availability of wide spectral range of Auto-SIF (500-800 nm), the photochemical reflectance index (PRI) and NDVI were also calculated to assess the diurnal SIFs and photosynthesis performances among different crops. This study presents a primary analyses of field diurnal canopy/leaf SIFs, PRI, NDVI of different crops , and may provide a better understanding of crop photosynthesis.
NASA Astrophysics Data System (ADS)
Pan, S.; Yang, J.; Zhang, J.; Xu, R.; Dangal, S. R. S.; Zhang, B.; Tian, H.
2016-12-01
Africa is one of the most vulnerable regions in the world to climate change and climate variability. Much concern has been raised about the impacts of climate and other environmental factors on water resource and food security through the climate-water-food nexus. Understanding the responses of crop yield and water use efficiency to environmental changes is particularly important because Africa is well known for widespread poverty, slow economic growth and agricultural systems particularly sensitive to frequent and persistent droughts. However, the lack of integrated understanding has limited our ability to quantify and predict the potential of Africa's agricultural sustainability and freshwater supply, and to better manage the system for meeting an increasing food demand in a way that is socially and environmentally or ecologically sustainable. By using the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed the spatial and temporal patterns of crop yield, evapotranspiration (ET) and water use efficiency across entire Africa in the past 35 years (1980-2015) and the rest of the 21st century (2016-2099). Our preliminary results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion (about 50%), elevated atmospheric CO2 concentration, and nitrogen deposition. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Climate extremes especially droughts and heat wave have largely reduced crop yield in the most vulnerable regions. Our results indicate that N fertilizer could be a major driver to improve food security in Africa. Future climate warming could reduce crop yield and shift cropland distribution. Our study further suggests that improving water use efficiency through land management practices including the increased uses of fertilizers and irrigation will be the key for reducing the loss of crop yield in a warming climate and extreme weather.
Dynamic versus static allocation policies in multipurpose multireservoir systems
NASA Astrophysics Data System (ADS)
Tilmant, A.; Goor, Q.; Pinte, D.; van der Zaag, P.
2007-12-01
As the competition for water is likely to increase in the near future due to socioeconomic development and population growth, water resources managers will face hard choices when allocating water between competing users. Because water is a vital resource used in multiple sectors, including the environment, the allocation is inherently a political and social process, which is likely to become increasingly scrutinized as the competition grows between the different sectors. Since markets are usually absent or ineffective, the allocation of water between competing demands is achieved administratively taking into account key objectives such as economic efficiency, equity and maintaining the ecological integrity. When crop irrigation is involved, water is usually allocated by a system of annual rights to use a fixed, static, volume of water. In a fully-allocated basin, moving from a static to a dynamic allocation process, whereby the policies are regularly updated according to the hydrologic status of the river basin, is the first step towards the development of river basin management strategies that increase the productivity of water. More specifically, in a multipurpose multireservoir system, continuously adjusting release and withdrawal decisions based on the latest hydrologic information will increase the benefits derived from the system. However, the extent to which such an adjustment can be achieved results from complex spatial and temporal interactions between the physical characteristics of the water resources system (storage, natural flows), the economic and social consequences of rationing and the impacts on natural ecosystems. The complexity of the decision-making process, which requires the continuous evaluation of numerous trade-offs, calls for the use of integrated hydrologic-economic models. This paper compares static and dynamic management approaches for a cascade of hydropower-irrigation reservoirs using stochastic dual dynamic programming (SDDP) formulations. As its name indicates, SDDP is an extension of SDP that removes the curse of dimensionality found in discrete SDP and can therefore be used to analyze large-scale water resources systems. For the static approach, the multiobjective (irrigation-hydropower) optimization problem is solved using the constraint method, i.e. net benefits from hydropower generation are maximized and irrigation water withdrawals are additional constraints. In the dynamic approach, the SDDP model seeks to maximize the net benefits of both hydropower and irrigation crop production. A cascade of 8 reservoirs in the Turkish and Syrian parts of the Euphrates river basin is used as a case study.
Organic carbon dynamics and soil stability in five semiarid agroecosystems
USDA-ARS?s Scientific Manuscript database
In the semiarid Texas High Plains where continuous cotton (CTN) is the dominate cropping practice, alternative agroecosystems such as integrated crop-livestock agroecosystems (ICL) are gaining interest for their versatility in management approaches to conserve water in this water-limited environment...
A bioenergy feedstock/vegetable double-cropping system
USDA-ARS?s Scientific Manuscript database
Certain warm-season vegetable crops may lend themselves to bioenergy double-cropping systems, which involve growing a winter annual bioenergy feedstock crop followed by a summer annual crop. The objective of the study was to compare crop productivity and weed communities in different pumpkin product...
Cong, Rihuan; Wang, Xiujun; Xu, Minggang; Ogle, Stephen M.; Parton, William J.
2014-01-01
Soil organic matter models are widely used to study soil organic carbon (SOC) dynamics. Here, we used the CENTURY model to simulate SOC in wheat-corn cropping systems at three long-term fertilization trials. Our study indicates that CENTURY can simulate fertilization effects on SOC dynamics under different climate and soil conditions. The normalized root mean square error is less than 15% for all the treatments. Soil carbon presents various changes under different fertilization management. Treatment with straw return would enhance SOC to a relatively stable level whereas chemical fertilization affects SOC differently across the three sites. After running CENTURY over the period of 1990–2050, the SOC levels are predicted to increase from 31.8 to 52.1 Mg ha−1 across the three sites. We estimate that the carbon sequestration potential between 1990 and 2050 would be 9.4–35.7 Mg ha−1 under the current high manure application at the three sites. Analysis of SOC in each carbon pool indicates that long-term fertilization enhances the slow pool proportion but decreases the passive pool proportion. Model results suggest that change in the slow carbon pool is the major driver of the overall trends in SOC stocks under long-term fertilization. PMID:24751981
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle
The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less
Zhang, Jie; Balkovič, Juraj; Azevedo, Ligia B; Skalský, Rastislav; Bouwman, Alexander F; Xu, Guang; Wang, Jinzhou; Xu, Minggang; Yu, Chaoqing
2018-06-15
This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China. Copyright © 2018. Published by Elsevier B.V.
Replacing fallow with continuous cropping reduces crop water productivity of semiarid wheat
USDA-ARS?s Scientific Manuscript database
Water supply frequently limits crop yield in semiarid cropping systems; water deficits can restrict yields in drought-affected subhumid regions. In semiarid wheat (Triticum aestivumL.)-based cropping systems, replacing an uncropped fallow period with a crop can increase precipitation use efficiency ...
Carbon Sequestration by Perennial Energy Crops: Is the Jury Still Out?
Agostini, Francesco; Gregory, Andrew S; Richter, Goetz M
Soil organic carbon (SOC) changes associated with land conversion to energy crops are central to the debate on bioenergy and their potential carbon neutrality. Here, the experimental evidence on SOC under perennial energy crops (PECs) is synthesised to parameterise a whole systems model and to identify uncertainties and knowledge gaps determining PECs being a sink or source of greenhouse gas (GHG). For Miscanthus and willow ( Salix spp.) and their analogues (switchgrass, poplar), we examine carbon (C) allocation to above- and belowground residue inputs, turnover rates and retention in the soil. A meta-analysis showed that studies on dry matter partitioning and C inputs to soils are plentiful, whilst data on turnover are rare and rely on few isotopic C tracer studies. Comprehensive studies on SOC dynamics and GHG emissions under PECs are limited and subsoil processes and C losses through leaching remain unknown. Data showed dynamic changes of gross C inputs and SOC stocks depending on stand age. C inputs and turnover can now be specifically parameterised in whole PEC system models, whilst dependencies on soil texture, moisture and temperature remain empirical. In conclusion, the annual net SOC storage change exceeds the minimum mitigation requirement (0.25 Mg C ha -1 year -1 ) under herbaceous and woody perennials by far (1.14 to 1.88 and 0.63 to 0.72 Mg C ha -1 year -1 , respectively). However, long-term time series of field data are needed to verify sustainable SOC enrichment, as the physical and chemical stabilities of SOC pools remain uncertain, although they are essential in defining the sustainability of C sequestration (half-life >25 years).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ye, Xujun, E-mail: yexujun@cc.hirosaki-u.ac.jp; Faculty of Agriculture and Life Sciences, Hirosaki University, Aomori 036-8561; Sakai, Kenshi, E-mail: ken@cc.tuat.ac.jp
Alternate bearing or masting is a yield variability phenomenon in perennial crops. The complex dynamics in this phenomenon have stimulated much ecological research. Motivated by data from an eight-year experiment with forty-eight individual trees, we explored the mechanism inherent to these dynamics in Satsuma mandarin (Citrus unshiu Marc.). By integrating high-resolution imaging technology, we found that the canopy structure and reproduction output of individual citrus crops are mutually dependent on each other. Furthermore, it was revealed that the mature leaves in early season contribute their energy to the fruiting of the current growing season, whereas the younger leaves show amore » delayed contribution to the next growing season. We thus hypothesized that the annual yield variability might be caused by the limited and time-delayed resource allocation in individual plants. A novel lattice model based on this hypothesis demonstrates that this pattern of resource allocation will generate oscillations and chaos in citrus yield.« less
CQESTR Simulation of Soil Organic Matter Dynamics in Long-term Agricultural Experiments across USA
NASA Astrophysics Data System (ADS)
Gollany, H.; Liang, Y.; Albrecht, S.; Rickman, R.; Follett, R.; Wilhelm, W.; Novak, J.
2009-04-01
Soil organic matter (SOM) has important chemical (supplies nutrients, buffers and adsorbs harmful chemical compounds), biological (supports the growth of microorganisms and micro fauna), and physical (improves soil structure and soil tilth, stores water, and reduces surface crusting, water runoff) functions. The loss of 20 to 50% of soil organic carbon (SOC) from USA soils after converting native prairie or forest to production agriculture is well documented. Sustainable management practices for SOC is critical for maintaining soil productivity and responsible utilization of crop residues. As crop residues are targeted for additional uses (e.g., cellulosic ethanol feedstock) developing C models that predict change in SOM over time with change in management becomes increasingly important. CQESTR, pronounced "sequester," is a process-based C balance model that relates organic residue additions, crop management and soil tillage to SOM accretion or loss. The model works on daily time-steps and can perform long-term (100-year) simulations. Soil organic matter change is computed by maintaining a soil C budget for additions, such as crop residue or added amendments like manure, and organic C losses through microbial decomposition. Our objective was to simulate SOM changes in agricultural soils under a range of soil parent materials, climate and management systems using the CQESTR model. Long-term experiments (e.g. Champaign, IL, >100 yrs; Columbia, MO, >100 yrs; Lincoln, NE, 20 yrs) under various tillage practices, organic amendments, crop rotations, and crop residue removal treatments were selected for their documented history of the long-term effects of management practice on SOM dynamics. Simulated and observed values from the sites were significantly related (r2 = 94%, P < 0.001) with slope not significantly different from 1. Recent interest in crop residue removal for biofuel feedstock prompted us to address that as a management issue. CQESTR successfully simulated a substantial decline in SOM with 90% of crop residue removal for 50 years under various rotations at Columbia, MO and Champaign, IL. An increase in SOM following addition of manure was also well simulated. However, the model underestimated SOM for a fertilized treatment at Columbia. We estimated that a minimum of 8.0 Mg/ha/yr of crop residue and organic amendments (4.0 Mg C ha/yr) was required to prevent a decline in SOM at the Morrow Plots in Champaign, IL. More studies are needed to evaluate the CQESTR model's performance in predicting the amount of crop residue required to maintain the SOM concentration in different soils under a wide range of management and climatic conditions. Given the high correlation of simulated and observed SOM changes, CQESTR can be used to consider a wide range of scenarios before making recommendations or implementing proposed changes. CQESTR in conjunction with the local conditions can guide planning and development of sustainable crop and soil management practices.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-04-19
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-01-01
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536
NASA Astrophysics Data System (ADS)
Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.
2012-10-01
Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
Soil quality and the solar corridor crop system
USDA-ARS?s Scientific Manuscript database
The solar corridor crop system (SCCS) is designed for improved crop productivity based on highly efficient use of solar radiation by integrating row crops with drilled or solid-seeded crops in broad strips (corridors) that also facilitate establishment of cover crops for year-round soil cover. The S...
Soil Quality and the Solar Corridor Crop System
USDA-ARS?s Scientific Manuscript database
The solar corridor crop system (SCCS) is designed for improved crop productivity based on highly efficient use of solar radiation by integrating row crops with drilled or solid-seeded crops in broad strips (corridors) that also facilitate establishment of cover crops for year-round soil cover. The S...
NASA Astrophysics Data System (ADS)
Jeffries, G. R.; Cohn, A.
2016-12-01
Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.
Farm-scale costs and returns for second generation bioenergy cropping systems in the US Corn Belt
NASA Astrophysics Data System (ADS)
Manatt, Robert K.; Hallam, Arne; Schulte, Lisa A.; Heaton, Emily A.; Gunther, Theo; Hall, Richard B.; Moore, Ken J.
2013-09-01
While grain crops are meeting much of the initial need for biofuels in the US, cellulosic or second generation (2G) materials are mandated to provide a growing portion of biofuel feedstocks. We sought to inform development of a 2G crop portfolio by assessing the profitability of novel cropping systems that potentially mitigate the negative effects of grain-based biofuel crops on food supply and environmental quality. We analyzed farm-gate costs and returns of five systems from an ongoing experiment in central Iowa, USA. The continuous corn cropping system was most profitable under current market conditions, followed by a corn-soybean rotation that incorporated triticale as a 2G cover crop every third year, and a corn-switchgrass system. A novel triticale-hybrid aspen intercropping system had the highest yields over the long term, but could only surpass the profitability of the continuous corn system when biomass prices exceeded foreseeable market values. A triticale/sorghum double cropping system was deemed unviable. We perceive three ways 2G crops could become more cost competitive with grain crops: by (1) boosting yields through substantially greater investment in research and development, (2) increasing demand through substantially greater and sustained investment in new markets, and (3) developing new schemes to compensate farmers for environmental benefits associated with 2G crops.
Mixed crop-livestock systems: an economic and environmental-friendly way of farming?
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.
Martins, Karla Vilaça; Dourado-Neto, Durval; Reichardt, Klaus; de Jong van Lier, Quirijn; Favarin, José Laércio; Sartori, Felipe Fadel; Felisberto, Guilherme; Mello, Simone da Costa
2017-01-01
The improvement of agronomic practices and the use of high technology in field crops contributes for significant increases in maize productivity, and may have altered the dynamics of nutrient uptake and partition by the plant. Official recommendations for fertilizer applications to the maize crop in Brazil and in many countries are based on critical soil nutrient contents and are relatively outdated. Since the factors that interact in an agricultural production system are dynamic, mathematical modeling of the growth process turns out to be an appropriate tool for these studies. Agricultural modeling can expand our knowledge about the interactions prevailing in the soil-plant-atmosphere system. The objective of this study is to propose a methodology for characterizing the micronutrient composition of different organs and their extraction, and export during maize crop development, based on modeling nutrient uptake, crop potential evapotranspiration and micronutrient partitioning in the plant, considering the production environment. This preliminary characterization study (experimental growth analysis) considers the temporal variation of the micronutrient uptake rate in the aboveground organs, which defines crop needs and the critical nutrient content of the soil solution. The methodology allowed verifying that, initially, the highest fraction of dry matter, among aboveground organs, was assigned to the leaves. After the R1 growth stage, the largest part of dry matter was partitioned to the stalk, which in this growth stage is the main storage organ of the maize plant. During the reproductive phase, the highest fraction of dry matter was conferred to the reproductive organs, due to the high demand for carbohydrates for grain filling. The micronutrient (B, Cu, Fe, Mn, and Zn) content follows a power model, with higher values for the initial growth stages of development and leveling off to minimum values at the R6 growth stage. The proposed model allows to verify that fertilizer recommendations should be related to the temporal variability of micronutrient absorption rates, in contrast to the classic recommendation based on the critical soil micronutrient content. The maximum micronutrient absorption rates occur between the reproductive R4 and R5 growth stages. These evaluations allowed to predict the maximum micronutrient requirements, considered equal to respective stalk sap concentrations. PMID:28919900
Yang, Zhenping; Yang, Wenping; Li, Shengcai; Hao, Jiaomin; Su, Zhifeng; Sun, Min; Gao, Zhiqiang; Zhang, Chunlai
2016-01-01
As the major crops in north China, spring crops are usually planted from April through May every spring and harvested in fall. Wheat is also a very common crop traditionally planted in fall or spring and harvested in summer year by year. This continuous cropping system exhibited the disadvantages of reducing the fertility of soil through decreasing microbial diversity. Thus, management of microbial diversity in the rhizosphere plays a vital role in sustainable crop production. In this study, ten common spring crops in north China were chosen sole-cropped and four were chosen intercropped with peanut in wheat fields after harvest. Denaturing gradient gel electrophoresis (DGGE) and DNA sequencing of one 16S rDNA fragment were used to analyze the bacterial diversity and species identification. DGGE profiles showed the bacterial community diversity in rhizosphere soil samples varied among various crops under different cropping systems, more diverse under intercropping system than under sole-cropping. Some intercropping-specific bands in DGGE profiles suggested that several bacterial species were stimulated by intercropping systems specifically. Furthermore, the identification of these dominant and functional bacteria by DNA sequencing indicated that intercropping systems are more beneficial to improve soil fertility. Compared to intercropping systems, we also observed changes in microbial community of rhizosphere soil under sole-crops. The rhizosphere bacterial community structure in spring crops showed a strong crop species-specific pattern. More importantly, Empedobacter brevis, a typical plant pathogen, was only found in the carrot rhizosphere, suggesting carrot should be sown prudently. In conclusion, our study demonstrated that crop species and cropping systems had significant effects on bacterial community diversity in the rhizosphere soils. We strongly suggest sorghum, glutinous millet and buckwheat could be taken into account as intercropping crops with peanut; while hulled oat, mung bean or foxtail millet could be considered for sowing in wheat fields after harvest in North China.
NASA Astrophysics Data System (ADS)
Mangiarotti, Sylvain; Drapeau, Laurent
2013-04-01
The global modeling approach aims to obtain parsimonious models of observed dynamics from few or single time series (Letellier et al. 2009). Specific algorithms were developed and validated for this purpose (Mangiarotti et al. 2012a). This approach was applied to the dynamics of cereal crops in semi-arid region using the vegetation index derived from satellite data as a proxy of the dynamics. A low-dimensional autonomous model could be obtained. The corresponding attractor is characteristic of weakly dissipative chaos and exhibits a toroidal-like structure. At present, only few theoretical cases of such chaos are known, and none was obtained from real world observations. Under smooth conditions, a robust validation of three-dimensional chaotic models can be usually performed based on the topological approach (Gilmore 1998). Such approach becomes more difficult for weakly dissipative systems, and almost impossible under noisy observational conditions. For this reason, another validation approach is developed which consists in comparing the forecasting skill of the model to other forecasts for which no dynamical model is required. A data assimilation process is associated to the model to estimate the model's skill; several schemes are tested (simple re-initialization, Extended and Ensemble Kalman Filters and Back and Forth Nudging). Forecasts without model are performed based on the search of analogous states in the phase space (Mangiarotti et al. 2012b). The comparison reveals the quality of the model's forecasts at short to moderate horizons and contributes to validate the model. These results suggest that the dynamics of cereal crops can be reasonably approximated by low-dimensional chaotic models, and also bring out powerful arguments for chaos. Chaotic models have often been used as benchmark to test data assimilation schemes; the present work shows that such tests may not only have a theoretical interest, but also almost direct applicative potential. Moreover, other global models could be obtained for other regions. The model considered here is not a particular case which highlights the usefulness to investigate and to widen this field of modeling and research. References: Letellier, C., Aguirre, L.A., Freitas, U.S., 2009. Frequently asked questions about global modeling. Chaos, 19, doi:10.1063/1.3125705. Gilmore R., 1998. Topological analysis of chaotic dynamical systems. Review of Modern Physics, 70, 1455-1530. Mangiarotti, S., Coudret, R., Drapreau, L., Jarlan, L., 2012a. Polynomial Search and Global Modeling - two algorithms for modelling chaos. Physical Review E, 86(4), 046205. Mangiarotti, S., Mazzega, P., Mougin, E., Hiernaux, P., 2012b. Predictability of vegetation cycles over the semi-arid region of Gourma (Mali) from forecasts of AVHRR-NDVI signals. Remote Sensing of Environment, 123, 246-257.
Pathogen evolution across the agro-ecological interface: implications for disease management.
Burdon, Jeremy J; Thrall, Peter H
2008-02-01
Infectious disease is a major causal factor in the demography of human, plant and animal populations. While it is generally accepted in medical, veterinary and agricultural contexts that variation in host resistance and pathogen virulence and aggressiveness is of central importance to understanding patterns of infection, there has been remarkably little effort to directly investigate causal links between population genetic structure and disease dynamics, and even less work on factors influencing host-pathogen coevolution. The lack of empirical evidence is particularly surprising, given the potential for such variation to not only affect disease dynamics and prevalence, but also when or where new diseases or pathotypes emerge. Increasingly, this lack of knowledge has led to calls for an integrated approach to disease management, incorporating both ecological and evolutionary processes. Here, we argue that plant pathogens occurring in agro-ecosystems represent one clear example where the application of evolutionary principles to disease management would be of great benefit, as well as providing model systems for advancing our ability to generalize about the long-term coevolutionary dynamics of host-pathogen systems. We suggest that this is particularly the case given that agro-ecological host-pathogen interactions represent a diversity of situations ranging from those that only involve agricultural crops through to those that also include weedy crop relatives or even unrelated native plant communities. We begin by examining some of the criteria that are important in determining involvement in agricultural pathogen evolution by noncrop plants. Throughout we use empirical examples to illustrate the fact that different processes may dominate in different systems, and suggest that consideration of life history and spatial structure are central to understanding dynamics and direction of the interaction. We then discuss the implications that such interactions have for disease management in agro-ecosystems and how we can influence those outcomes. Finally, we identify several major gaps where future research could increase our ability to utilize evolutionary principles in managing disease in agro-ecosystems.
Sandia National Laboratories: Bumper crop of partnerships
of IR Dynamics LLC of Santa Fe, is working with Sandia's Nelson Bell (1815) through a Cooperative Research and Development Agreement. IR Dynamics is developing thermochromic materials to control infrared analysis of human visual perception and cognition with dynamic content. IR Dynamics LLC: The Santa Fe
Understanding Arsenic Dynamics in Agronomic Systems to ...
This review is on arsenic in agronomic systems, and covers processes that influence the entry of arsenic into the human food supply. The scope is from sources of arsenic (natural and anthropogenic) in soils, biogeochemical and rhizosphere processes that control arsenic speciation and availability, through to mechanisms of uptake by crop plants and potential mitigation strategies. This review makes a case for taking steps to prevent or limit crop uptake of arsenic, wherever possible, and to work toward a long-term solution to the presence of arsenic in agronomic systems. The past two decades have seen important advances in our understanding of how biogeochemical and physiological processes influence human exposure to soil arsenic, and thus must now prompt an informed reconsideration and unification of regulations to protect the quality of agricultural and residential soils. Consumption of staple foods such as rice, beverages such as apple juice, or vegetables grown in historically arsenic-contaminated soils is now recognized as a tangible route of arsenic exposure that, in many cases, is more significant than exposure from drinking water. Understanding the sources of arsenic to crop plants and the factors that influence them is key to reducing exposure now and preventing exposure in future. In addition to the abundant natural sources of arsenic, there are a large number of industrial and agricultural sources of arsenic to the soil; from mining wastes, coal fly
NASA Astrophysics Data System (ADS)
Dempster, W.; Nelson, M.; Silverstone, S.; Allen, J.; Alling, A.; van Thillo, M.
A mixed crop consisting of cowpeas pinto beans and Apogee ultra-dwarf wheat was grown in Laboratory Biosphere a 40 m 3 closed life system equipped with 12000 watts of high pressure sodium lamps over planting beds with 5 37 m 2 of soil Similar to earlier reported experiments the concentration of carbon dioxide initially increased to 7860 ppm at 10 days after planting due to soil respiration plus CO 2 contributed from researchers breathing while in the chamber for brief periods before plant growth became substantial fell rapidly as plant growth increased up to 29 days after planting and then was maintained mostly in the range of about 200 -- 3000 ppm with a few excursions by CO 2 injections to feed plant growth Numerous analyses of rate of change of CO 2 concentration at many different concentrations and at many different days after planting reveals a strong dependence of fixation rates on CO 2 concentration In the middle period of growth days 31 -- 61 fixation rates doubled for CO 2 at 450 ppm compared to 270 ppm doubled again at 1000 ppm and increased a further 50 at 2040 ppm High productivity from these crops and the increase of fixation rates with elevated CO 2 concentration supports the concept that enhanced CO2 can be a useful strategy for remote life support systems
Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems
Reckling, Moritz; Bergkvist, Göran; Watson, Christine A.; Stoddard, Frederick L.; Zander, Peter M.; Walker, Robin L.; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann
2016-01-01
Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers. PMID:27242870
Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems.
Reckling, Moritz; Bergkvist, Göran; Watson, Christine A; Stoddard, Frederick L; Zander, Peter M; Walker, Robin L; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann
2016-01-01
Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers.
Using a System Model for Irrigation Management
NASA Astrophysics Data System (ADS)
de Souza, Leonardo; de Miranda, Eu; Sánchez-Román, Rodrigo; Orellana-González, Alba
2014-05-01
When using Systems Thinking variables involved in any process have a dynamic behavior, according to nonstatic relationships with the environment. In this paper it is presented a system dynamics model developed to be used as an irrigation management tool. The model involves several parameters related to irrigation such as: soil characteristics, climate data and culture's physiological parameters. The water availability for plants in the soil is defined as a stock in the model, and this soil water content will define the right moment to irrigate and the water depth required to be applied. The crop water consumption will reduce soil water content; it is defined by the potential evapotranspiration (ET) that acts as an outflow from the stock (soil water content). ET can be estimated by three methods: a) FAO Penman-Monteith (ETPM), b) Hargreaves-Samani (ETHS) method, based on air temperature data and c) Class A pan (ETTCA) method. To validate the model were used data from the States of Ceará and Minas Gerais, Brazil, and the culture was bean. Keyword: System Dynamics, soil moisture content, agricultural water balance, irrigation scheduling.
NASA Astrophysics Data System (ADS)
Betbeder, Julie; Fieuzal, Remy; Philippets, Yannick; Ferro-Famil, Laurent; Baup, Frederic
2016-04-01
This paper aims to evaluate the contribution of multitemporal polarimetric synthetic aperture radar (SAR) data for winter wheat and rapeseed crops parameters [height, leaf area index, and dry biomass (DB)] estimation, during their whole vegetation cycles in comparison to backscattering coefficients and optical data. Angular sensitivities and dynamics of polarimetric indicators were also analyzed following the growth stages of these two common crop types using, in total, 14 radar images (Radarsat-2), 16 optical images (Formosat-2, Spot-4/5), and numerous ground data. The results of this study show the importance of correcting the angular effect on SAR signals especially for copolarized signals and polarimetric indicators associated to single-bounce scattering mechanisms. The analysis of the temporal dynamic of polarimetric indicators has shown their high potential to detect crop growth changes. Moreover, this study shows the high interest of using SAR parameters (backscattering coefficients and polarimetric indicators) for crop parameters estimation during the whole vegetation cycle instead of optical vegetation index. They particularly revealed their high potential for rapeseed height and DB monitoring [i.e., Shannon entropy polarimetry (r2=0.70) and radar vegetation index (r2=0.80), respectively].
Assessment of Land Degradation and Greening in Ken River Basin of Central India
NASA Astrophysics Data System (ADS)
Pandey, Ashish; Palmate, Santosh S.
2017-04-01
Natural systems have significant impact of land degradation on biodiversity loss, food and water insecurity. To achieve the sustainable development goals, advances in remote sensing and geographical information systems (GIS) are progressively utilized to combat climate change, land degradation and poverty issues of developing country. The Ken River Basin (KRB) has dominating land cover pattern of agriculture and forest area. Nowadays, this pattern is affected due to climate change and anthropogenic activity like deforestation. In this study, land degradation and greening status of KRB of Central India during the years 2001 to 2013 have been assessed using MODIS land cover (MCD12Q1) data sets. International Geosphere Biosphere Programme (IGBP) land cover data has been extracted from the MCD12Q1 data product. Multiple rasters of MODIS landcover were analyzed and compared for assigning unique combination of land cover dynamics employing ArcGIS software. Result reveals that 14.38% natural vegetation was degraded, and crop land and woody savannas were greened by 9.68% to 6.94% respectively. Natural vegetation degradation have been observed in the upper KRB area, and resulted to increase in crop land (3418.87 km2) and woody savannas (1242.23 km2) area. Due to transition of 1043.6 km2 area of deciduous broadleaf forest to woody savannas greening was also observed. Moreover, both crop land and woody savannas showed inter-transitions of 669.31 km2 into crop land to woody savannas, and 874.09 km2 into woody savannas to crop land. The present analysis reveals that natural vegetation has more land conversions into woody savannas and crop land in the KRB area. Further, Spatial change analysis shows that land degradation and greening has occurred mostly in the upper part of the KRB. The study reveals that the land transition information can be useful for proper planning and management of natural resources.
Age-dependent population dynamics of the bioenergy crop Miscanthus x giganteus in Illinois
USDA-ARS?s Scientific Manuscript database
Rising global demand for liquid fuels, coupled with new technologies for converting biomass to ethanol, have generated intense interest in the development of herbaceous perennial bioenergy crops. Some plant species being considered as biofeedstocks share traits with invasive species and have histori...
NASA Astrophysics Data System (ADS)
Darby, S. E.; Chapman, A.; Hackney, C. R.; Leyland, J.; Parsons, D. R.; Aalto, R. E.; Nicholas, A. P.; Best, J.
2016-12-01
The Vietnamese Mekong delta is one of the world's largest rice producing regions, but it is facing a major sustainability challenge. The delta is being `drowned' by rising relative sea-levels, a situation that is being exacerbated by a reduction in the supply of rivers sediments due to a combination of climate change and sediment trapping linked to the construction of large hydropower dams in upstream countries. Poverty is prevalent and farmers face many challenges, such as declining productivity, income insecurity and debt; they are therefore reliant on natural ecosystem services, notably soil nutrient replenishment by sediment deposition during floods, to minimise dependence on chemical fertilisers. Meanwhile, the drive to intensify rice production (a key national policy goal that has underpinned the region's recent economic development) has been achieved by replacing the traditional use of `low' (0-2m in height) dyke networks with `high' (>3.5m) dyke networks. Since rice production takes place within these dyke rings, this has enabled a switch from traditional cultivation techniques (double cropping within low dyke rings) to a new system of triple cropping (in which an extra crop can be grown due to the exclusion of flood waters during the monsoon season) within the high dykes. This involves trading off immediate benefits (protection against floods; improved rice production) against long term disadvantages (the exclusion of sediment accelerates relative sea-level rise, adding to flood risk in the long term, while sediment borne nutrients are key to agricultural productivity in the long term). Here we use systems dynamics modelling to demonstrate that current rice cultivation strategies are a maladaptation which, under a future of declining sediment loads due to upstream hydropower development, are not sustainable in the long term and present recommendations for more sustainable water management policies in the delta's rice growing region.
Trickling filter for urea and bio-waste processing - dynamic modelling of nitrogen cycle
NASA Astrophysics Data System (ADS)
Zhukov, Anton; Hauslage, Jens; Tertilt, Gerin; Bornemann, Gerhild
Mankind’s exploration of the solar system requires reliable Life Support Systems (LSS) enabling long duration manned space missions. In the absence of frequent resupply missions, closure of the LSS will play a very important role and its maximisation will to a large extent drive the selection of appropriate LSS architectures. One of the significant issues on the way to full closure is to effectively utilise biological wastes such as urine, inedible biomass etc. A very promising concept of biological waste reprocessing is the use of trickling filters which are currently being developed and investigated by DLR, Cologne, Germany. The concept is called Combined Regenerative Organic-Food Production (C.R.O.P.) and is based on the microbiological treatment of biological wastes and reprocessing them into aqueous fertilizer which can directly be used in a greenhouse for food production. Numerous experiments have been and are being conducted by DLR in order to fully understand and characterize the process. The human space exploration group of the Technical University of Munich (TUM) in cooperation with DLR has started to establish a dynamic model of the trickling filter system to be able to assess its performance on the LSS level. In the first development stage the model covers the nitrogen cycle enabling to simulate urine processing. This paper describes briefly the C.R.O.P. concept and the status of the trickling filter model development. The model is based on enzyme-catalyzed reaction kinetics for the fundamental microbiological reaction chain and is created in MATLAB. Verification and correlation of the developed model with experiment results has been performed. Several predictive studies for batch sequencing behavior have been performed, demonstrating a good capability of C.R.O.P. concept to be used in closed LSS. Achieved results are critically discussed and way forward is presented.
Ye, Qing; Yang, Xiaoguang; Dai, Shuwei; ...
2015-06-05
Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.
Crop growth and associated life support for a lunar farm
NASA Technical Reports Server (NTRS)
Volk, Tyler; Cullingford, Hatice
1992-01-01
Supporting human life on a lunar base will require growing many different food crops. This paper investigates the growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) for general similarities and differences, along with associated material flows of the gases, liquids, and solids in a lunar farm. The human dietary requirements are compared with the protein, carbohydrate, and lipid contents of these hydroponically grown, high-productivity crops to derive a lunar farm diet. A simple and general analytical model is used to calculate the mass fluxes of CO2, H2O, HNO3, and O2 during the life cycle of each of the four crops. The resulting farm crop areas and corresponding biomass production rates are given. One significant conclusion of this study is that there is a 'lipid problem' associated with the incorporation of these four crops into a viable diet.
The century experiment: the first twenty years of UC Davis' Mediterranean agroecological experiment.
Wolf, Kristina M; Torbert, Emma E; Bryant, Dennis; Burger, Martin; Denison, R Ford; Herrera, Israel; Hopmans, Jan; Horwath, Will; Kaffka, Stephen; Kong, Angela Y Y; Norris, R F; Six, Johan; Tomich, Thomas P; Scow, Kate M
2018-02-01
The Century Experiment at the Russell Ranch Sustainable Agriculture Facility at the University of California, Davis provides long-term agroecological data from row crop systems in California's Central Valley starting in 1993. The Century Experiment was initially designed to study the effects of a gradient of water and nitrogen availability on soil properties and crop performance in ten different cropping systems to measure tradeoffs and synergies between agricultural productivity and sustainability. Currently systems include 11 different cropping systems-consisting of four different crops and a cover crop mixture-and one native grass system. This paper describes the long-term core data from the Century Experiment from 1993-2014, including crop yields and biomass, crop elemental contents, aerial-photo-based Normalized Difference Vegetation Index data, soil properties, weather, chemical constituents in irrigation water, winter weed populations, and operational data including fertilizer and pesticide application amounts and dates, planting dates, planting quantity and crop variety, and harvest dates. This data set represents the only known long-term set of data characterizing food production and sustainability in irrigated and rainfed Mediterranean annual cropping systems. There are no copyright restrictions associated with the use of this dataset. © 2018 by the Ecological Society of America.
Murúa, M. Gabriela; Cazado, Lucas E.; Casmuz, Augusto; Herrero, M. Inés; Villagrán, M. Elvira; Vera, Alejandro; Sosa-Gómez, Daniel R.; Gastaminza, Gerardo
2016-01-01
The Heliothinae complex in Argentina encompasses Helicoverpa gelotopoeon (Dyar), Helicoverpa zea (Boddie), Helicoverpa armigera (Hübner), and Chloridea virescens (Fabricius). In Tucumán, the native species H. gelotopoeon is one of the most voracious soybean pests and also affects cotton and chickpea, even more in soybean-chickpea succession cropping systems. Differentiation of the Heliothinae complex in the egg, larva, and pupa stages is difficult. Therefore, the observation of the adult wing pattern design and male genitalia is useful to differentiate species. The objective of this study was to identify the species of the Heliothinae complex, determine population fluctuations of the Heliothinae complex in soybean and chickpea crops using male moths collected in pheromone traps in Tucuman province, and update the geographical distribution of H. armigera in Argentina. The species found were H. gelotopoeon, H. armigera, H. zea, and C. virescens. Regardless of province, county, crop, and year, the predominant species was H. gelotopoeon. Considering the population dynamics of H. gelotopoeon and H. armigera in chickpea and soybean crops, H. gelotopoeon was the most abundant species in both crops, in all years sampled, and the differences registered were significant. On the other hand, according to the Sistema Nacional Argentino de Vigilancia y Monitoreo de Plagas (SINAVIMO) database and our collections, H. armigera was recorded in eight provinces and 20 counties of Argentina, and its larvae were found on soybean, chickpea, sunflower crops and spiny plumeless thistle (Carduus acanthoides). This is the first report of H. armigera in sunflower and spiny plumeless thistle in Argentina. PMID:27324588
Soil quality monitoring in an area with land use change
NASA Astrophysics Data System (ADS)
Wilson, Marcelo; Gabioud, Emmanuel; Sasal, María Carolina; Oszust, José; Paz Gonzalez, Antonio
2013-04-01
The characterization of the soil quality through soil quality indicators (SQI), provides an effective method for the monitoring of the impacts to soil by use and management decisions. The key is to identify variables that are sensitive to changes in the soil functions and processes. The native forest area of Entre Ríos (Argentina) is associated with a constant change in land use, with an increase in recent years in agricultural use, especially for soybean crop. The aim was to monitor soil quality in three soils of an area of this area where native forest is being replaced by an agricultural system based in soybean crop, using a a minimum data set (MDS) previously selected for three soil type. The three soils selected were a Vertic Argiudoll, an Aquic Argiudoll and a Vertic Ocracualf. Treatments included plots with continuous cropping with different number of years under soybean crop, crop-pasture rotation, long-term pasture (PP), and uncropped land (UC) in pristine situation, which was taken as a reference. The crops were sowed under no tillage system and some plots were systematized with terraces contour to runoff management. The selection of a group of soil indicators in a MDS, was developed locally because it must be different for each soil type and each particular use. Total organic carbon (TOC), aggregate stability and pH were common indicators. Furthermore, it was assessed macroporosity, total porosity, cation exchange capacity two biological indicators (microbial biomass Carbon and potentially mineralizable Nitrogen) and A horizon soil mass, as a measure of the soil erosion. Statistical analysis, as linear regression analysis, ANOVA and cluster analysis were used. The soil indicators showed the changes caused by soil use, being more marked deterioration in the Vertic Ocracualf. TOC, microbial biomass Carbon and aggregate stability were the most sensitive SQI. However, positive changes were observed in potentially mineralizable Nitrogen, wiht PP. In the Vertic Argiudoll, the changes caused by agricultural use were significant in the plots with most years of continuous cropping as compared with UC and PP treatments, whereas in the Vertic Ocracualf with few years under agriculture, processes of soil deterioration started to be detected. The Aquic Argiudoll showed high resilience through all SQI. In the Vertic Ocracualf, we recommended that the period of crops rotation should be shorter than the period under pasture, to maintain the soil quality. The native forest should be the basis of sustainable production systems in the area. In addition, the agricultural use should be defined according to the soil limitations, and the dynamic soil qualities.
AgMIP: Next Generation Models and Assessments
NASA Astrophysics Data System (ADS)
Rosenzweig, C.
2014-12-01
Next steps in developing next-generation crop models fall into several categories: significant improvements in simulation of important crop processes and responses to stress; extension from simplified crop models to complex cropping systems models; and scaling up from site-based models to landscape, national, continental, and global scales. Crop processes that require major leaps in understanding and simulation in order to narrow uncertainties around how crops will respond to changing atmospheric conditions include genetics; carbon, temperature, water, and nitrogen; ozone; and nutrition. The field of crop modeling has been built on a single crop-by-crop approach. It is now time to create a new paradigm, moving from 'crop' to 'cropping system.' A first step is to set up the simulation technology so that modelers can rapidly incorporate multiple crops within fields, and multiple crops over time. Then the response of these more complex cropping systems can be tested under different sustainable intensification management strategies utilizing the updated simulation environments. Model improvements for diseases, pests, and weeds include developing process-based models for important diseases, frameworks for coupling air-borne diseases to crop models, gathering significantly more data on crop impacts, and enabling the evaluation of pest management strategies. Most smallholder farming in the world involves integrated crop-livestock systems that cannot be represented by crop modeling alone. Thus, next-generation cropping system models need to include key linkages to livestock. Livestock linkages to be incorporated include growth and productivity models for grasslands and rangelands as well as the usual annual crops. There are several approaches for scaling up, including use of gridded models and development of simpler quasi-empirical models for landscape-scale analysis. On the assessment side, AgMIP is leading a community process for coordinated contributions to IPCC AR6 that involves the key modeling groups from around the world including North America, Europe, South America, Sub-Saharan Africa, South Asia, East Asia, and Australia and Oceania. This community process will lead to mutually agreed protocols for coordinated global and regional assessments.
Agronomic responses to late-seeded cover crops in a semiarid region
USDA-ARS?s Scientific Manuscript database
Intensification of cropping systems in the Great Plains beyond annual cropping practices may be limited by inadequate precipitation, short growing seasons, and highly variable climatic conditions. Inclusion of cover crops in dryland cropping systems may serve as an effective intensification strateg...
USDA-ARS?s Scientific Manuscript database
Potato cropping system practices substantially affect soil microbial communities and the development of soilborne diseases. Cropping systems incorporating soil health management practices, such as longer rotations, disease-suppressive crops, reduced tillage, and/or organic amendments can potentially...
USDA-ARS?s Scientific Manuscript database
Understanding how intensification of abiotic stress due to global climate change affects crop yields is important for continued agricultural productivity. Coupling genomic technologies with physiological crop responses in a dynamic field environment is an effective approach to dissect the mechanisms...
Spatio-temporal dynamics of Fusarium head blight and Trichothecene toxin types in Canada
USDA-ARS?s Scientific Manuscript database
In many parts of the world Fusarium graminearum is the primary causal agent of Fusarium head blight (FHB), a disease of cereal crops that adversely affects crop yield, food safety, and animal health. We previously demonstrated population structure associated with differences in trichothecene toxin t...
The effect of total carbon on microscopic soil properties and implications for crop production
USDA-ARS?s Scientific Manuscript database
Soil structure is a dynamic property affected by physical, chemical, and microbiological processes. Addition of organic matter to soils and the use of different management practices have been reported to impact soil structure and crop production. Moderation in soil temperature and increases in mic...
NASA Astrophysics Data System (ADS)
Ren, W.; Huang, Y.; Tao, B.; Zhu, X.; Tian, H.
2017-12-01
The agriculture sector is estimated to be responsible for 12% of the total greenhouse gas emissions, particularly for 52% of CH4 and 84% of N2O. It has been predicted that the world population would reach 9.7 billion by 2050 and require a 60 percent increase in total agricultural production above the level of 2005-07, which would potentially further boost greenhouse gas emissions from agroecosystems. The growing concerns over food security and rapid rate of global warming necessitates the development of conservation management (or climate-smart soil management) that can ensure high crop yield and meanwhile markedly enhance soil sequestration and reduce GHG emissions. In this study, we synthesize multi-source datasets and apply an improved agroecosystem model to quantitatively investigate the dynamics of CH4 and N2O fluxes as influenced by conservation management practices in cropping systems of Asia (such as wheat, corn, and rice) for exploring the potential of those practices to mitigate and adapt to climate change. Our preliminary results suggest that the conservation tillage (e.g., reduced and no tillage) can largely suppress CH4 emissions from Asia's rice paddies, although they, to some extent, may stimulate NO2 emissions, comparing with the conventional tillage.
NASA Astrophysics Data System (ADS)
den Besten, Nadja I.; Pande, Saket; Savenije, Hubert H. G.
2016-05-01
Maharashtra is one of the states in India that has witnessed one of the highest rates of farmer suicides as proportion of total number of suicides. Most of the farmer suicides in Maharashtra are from semi-arid divisions such as Marathwada where cotton has been historically grown. Other dominant crops produced include cereals, pulses, oilseeds and sugarcane. Cotton (fibers), oilseeds and sugarcane providing highest value addition per unit cultivated area and cereals and pulses the least. Hence it is not surprising that smallholders take risks growing high value crops without "visualising" the risks it entails such as those corresponding to price and weather shocks.We deploy recently developed smallholder socio-hydrology modelling framework to understand the underlying dynamics of the crisis. It couples the dynamics of six main variables that are most relevant at the scale of a smallholder: water storage capacity (root zone storage and other ways of water storage), capital, livestock, soil fertility and fodder biomass. The hydroclimatic variability is accounted for at sub-annual scale and influences the socio-hydrology at annual scale. The model incorporates rule-based adaptation mechanisms (e.g., adjusting expenditures on food and fertilizers, selling livestocks) of smallholders when they face adverse conditions, such as high variability in rainfall or in agricultural prices. The model is applied to two adjoining divisions of Maharashtra: Marathwada and Desh. The former is the division with relatively higher farmer suicide rates than the latter. Diverse spatial data sets of precipitation, potential evaporation, soil, agricultural census based farm inputs, cropping pattern and prices are used to understand the dynamics of small farmers in these divisions, and to attribute farmer distress rates to soil types, hydroclimatic variability and crops grown.Comparative socio-hydrologic assessment across the two regions confirms existing narratives: low (soil) water storage capacities, no irrigation and poor access to alternative sources of incomes are to blame for the crisis, suggesting that smart indigenous solutions such as rain-water harvesting and better integration of smallholder systems to efficient agricultural supply chains are needed to tackle this development challenge.
Current and Projected Carbon Dynamics in US Agricultural Systems
NASA Astrophysics Data System (ADS)
Ogle, S. M.; Paustian, K.; Zhang, Y.; Kent, J.; Gurung, R.; Klotz, R.
2016-12-01
Agricultural lands occur across a variety of landscapes in the United States, and carbon dynamics are largely controlled by management decisions along with edaphic characteristics, climate and other environmental drivers. Due to the influence of management, there is potential to sequester carbon in soils with adoption of conservation practices, such as setting aside degraded land from production, limiting tillage disturbance, enhancing crop production with higher yielding varieties, planting cover crops, and restoring wetlands where they have been drained for crop production. In 2010, the level of sequestration in mineral soils across US croplands was 48 million metric tonnes CO2 equivalent, which is down from the high during the past 25 years of 90 million metric tonnes CO2 equivalent. In contrast, drained wetlands that are used for crop production were emitting 22.1 million metric tonnes CO2 equivalent in 2010. In the short term, restoring drained wetlands would decrease CO2emissions to the atmosphere, and even with the additional CH4 emissions from restored wetlands, there would an overall reduction in greenhouse gas emissions from these lands. In turn, this would make a significant contribution to the USDA Climate Smart Agriculture Plan for reducing greenhouse gas emissions by 120 million metric tonnes CO2 equivalent in support of the Paris Agreement. The potential to sequester carbon in the future will also be impacted by climate change, in addition to the management decisions of land managers. We simulated future carbon dynamics through 2060 based on climate change projections for RCP 2.5, 4.5 and 8.5 scenarios, with and without CO2 fertilization effects. We are using the results as input to a general equilibrium model for the agricultural economic sector to better understand the economic consequences of climate change and the potential for greenhouse gas mitigation. By evaluating the influence of climate change and economic welfare, our study is providing a basis to understand the potential long-term contribution of carbon sequestration in support of a Climate Smart Agriculture Program in the United States.
Karki, Sandhya; Elsgaard, Lars; Kandel, Tanka P; Lærke, Poul Erik
2015-03-01
Empirical greenhouse gas (GHG) flux estimates from diverse peatlands are required in order to derive emission factors for managed peatlands. This study on a drained fen peatland quantified the annual GHG balance (Carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), and C exported in crop yield) from spring barley (SB) and reed canary grass (RCG) using static opaque chambers for GHG flux measurements and biomass yield for indirectly estimating gross primary production (GPP). Estimates of ecosystem respiration (ER) and GPP were compared with more advanced but costly and labor-intensive dynamic chamber studies. Annual GHG balance for the two cropping systems was 4.0 ± 0.7 and 8.1 ± 0.2 Mg CO2-Ceq ha(-1) from SB and RCG, respectively (mean ± standard error, n = 3). Annual CH4 emissions were negligible (<0.006 Mg CO2-Ceq ha(-1)), and N2O emissions contributed only 4-13 % of the full GHG balance (0.5 and 0.3 Mg CO2-Ceq ha(-1) for SB and RCG, respectively). The statistical significance of low CH4 and N2O fluxes was evaluated by a simulation procedure which showed that most of CH4 fluxes were within the range that could arise from random variation associated with actual zero-flux situations. ER measured by static chamber and dynamic chamber methods was similar, particularly when using nonlinear regression techniques for flux calculations. A comparison of GPP derived from aboveground biomass and from measuring net ecosystem exchange (NEE) showed that GPP estimation from biomass might be useful, or serve as validation, for more advanced flux measurement methods. In conclusion, combining static opaque chambers for measuring ER of CO2 and CH4 and N2O fluxes with biomass yield for GPP estimation worked well in the drained fen peatland cropped to SB and RCG and presented a valid alternative to estimating the full GHG balance by dynamic chambers.
Crop diversity effects on productivity and economic returns under dryland agriculture
USDA-ARS?s Scientific Manuscript database
Increasing crop diversity has been identified as a method to improve agronomic performance of cropping systems and increase provision of ecosystem services. However, there is a need to understand the economic performance of more diverse cropping systems. Crop productivity and economic net returns we...
Statistical modeling of yield and variance instability in conventional and organic cropping systems
USDA-ARS?s Scientific Manuscript database
Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...
USDA-ARS?s Scientific Manuscript database
In the Mid-Atlantic region, there is increasing interest in the use of relay-cropping strategies to establish cover crops in corn cropping systems. Recent studies have demonstrated the potential to establish annual ryegrass and red clover cover crops at the V5 corn growth stage using a high-clearan...
Perspectives on genetically modified crops and food detection.
Lin, Chih-Hui; Pan, Tzu-Ming
2016-01-01
Genetically modified (GM) crops are a major product of the global food industry. From 1996 to 2014, 357 GM crops were approved and the global value of the GM crop market reached 35% of the global commercial seed market in 2014. However, the rapid growth of the GM crop-based industry has also created controversies in many regions, including the European Union, Egypt, and Taiwan. The effective detection and regulation of GM crops/foods are necessary to reduce the impact of these controversies. In this review, the status of GM crops and the technology for their detection are discussed. As the primary gap in GM crop regulation exists in the application of detection technology to field regulation, efforts should be made to develop an integrated, standardized, and high-throughput GM crop detection system. We propose the development of an integrated GM crop detection system, to be used in combination with a standardized international database, a decision support system, high-throughput DNA analysis, and automated sample processing. By integrating these technologies, we hope that the proposed GM crop detection system will provide a method to facilitate comprehensive GM crop regulation. Copyright © 2015. Published by Elsevier B.V.
Neural network simulation of soil NO3 dynamic under potato crop system
NASA Astrophysics Data System (ADS)
Goulet-Fortin, Jérôme; Morais, Anne; Anctil, François; Parent, Léon-Étienne; Bolinder, Martin
2013-04-01
Nitrate leaching is a major issue in sandy soils intensively cropped to potato. Modelling could test and improve management practices, particularly as regard to the optimal N application rates. Lack of input data is an important barrier for the application of classical process-based models to predict soil NO3 content (SNOC) and NO3 leaching (NOL). Alternatively, data driven models such as neural networks (NN) could better take into account indicators of spatial soil heterogeneity and plant growth pattern such as the leaf area index (LAI), hence reducing the amount of soil information required. The first objective of this study was to evaluate NN and hybrid models to simulate SNOC in the 0-40 cm soil layer considering inter-annual variations, spatial soil heterogeneity and differential N application rates. The second objective was to evaluate the same methodology to simulate seasonal NOL dynamic at 1 m deep. To this aim, multilayer perceptrons with different combinations of driving meteorological variables, functions of the LAI and state variables of external deterministic models have been trained and evaluated. The state variables from external models were: drainage estimated by the CLASS model and the soil temperature estimated by an ICBM subroutine. Results of SNOC simulations were compared to field data collected between 2004 and 2011 at several experimental plots under potato cropping systems in Québec, Eastern Canada. Results of NOL simulation were compared to data obtained in 2012 from 11 suction lysimeters installed in 2 experimental plots under potato cropping systems in the same region. The most performing model for SNOC simulation was obtained using a 4-input hybrid model composed of 1) cumulative LAI, 2) cumulative drainage, 3) soil temperature and 4) day of year. The most performing model for NOL simulation was obtained using a 5-input NN model composed of 1) N fertilization rate at spring, 2) LAI, 3) cumulative rainfall, 4) the day of year and 5) the percentage of clay content. The MAE was 22% for SNOC simulation and 23% for NOL simulation. High sensitivity to LAI suggests that the model may take into account field and sub-field spatial variability and support N management. Further studies are needed to fully validate the method, particularly in the case of NOL simulation.
NASA Astrophysics Data System (ADS)
Amon-Armah, Frederick; Yiridoe, Emmanuel K.; Ahmad, Nafees H. M.; Hebb, Dale; Jamieson, Rob; Burton, David; Madani, Ali
2013-11-01
Government priorities on provincial Nutrient Management Planning (NMP) programs include improving the program effectiveness for environmental quality protection, and promoting more widespread adoption. Understanding the effect of NMP on both crop yield and key water-quality parameters in agricultural watersheds requires a comprehensive evaluation that takes into consideration important NMP attributes and location-specific farming conditions. This study applied the Soil and Water Assessment Tool (SWAT) to investigate the effects of crop and rotation sequence, tillage type, and nutrient N application rate on crop yield and the associated groundwater leaching and sediment loss. The SWAT model was applied to the Thomas Brook Watershed, located in the most intensively managed agricultural region of Nova Scotia, Canada. Cropping systems evaluated included seven fertilizer application rates and two tillage systems (i.e., conventional tillage and no-till). The analysis reflected cropping systems commonly managed by farmers in the Annapolis Valley region, including grain corn-based and potato-based cropping systems, and a vegetable-horticulture system. ANOVA models were developed and used to assess the effects of crop management choices on crop yield and two water-quality parameters (i.e., leaching and sediment loading). Results suggest that existing recommended N-fertilizer rate can be reduced by 10-25 %, for grain crop production, to significantly lower leaching ( P > 0.05) while optimizing the crop yield. The analysis identified the nutrient N rates in combination with specific crops and rotation systems that can be used to manage leaching while balancing impacts on crop yields within the watershed.
Integrated crop-livestock systems and cover crop grazing in the Northern Great Plains
USDA-ARS?s Scientific Manuscript database
Integrating crops and livestock has been identified as an approach to sustainably intensify agricultural systems, increasing production while reducing the need for external inputs, building soil health, and increasing economic returns. Cover crops and grazing these cover crops are a natural fit with...
Long-term cropping systems study
USDA-ARS?s Scientific Manuscript database
This long-term study has been conducted on the Agronomy Farm at ARDC since the early 1970’s. In the beginning, the objectives were mainly related to crop production as affected by different cropping systems. The cropping systems included in the study are Continuous Corn, Soybean, and Sorghum; 2-year...
Sharma, S. B.; Rego, T. J.; Mohiuddin, M.; Rao, V. N.
1996-01-01
The significance of double crop (intercrop and sequential crop), single crop (rainy season crop fallow from June to September), and rotations on densities of Heterodera cajani, Helicotylenchus retusus, and Rotylenchulus reniformis was studied on Vertisol (Typic Pellusterts) between 1987 and 1993. Cowpea (Vigna sinensis), mungbean (Phaseolus aureus), and pigeonpea (Cajanus cajan) greatly increased the population densities of H. cajani and suppressed the population densities of other plant-parasitic nematodes. Mean population densities of H. cajani were about 8 times lower in single crop systems than in double crop systems, with pigeonpea as a component intercrop. Plots planted to sorghum, safflower, and chickpea in the preceding year contained fewer H. cajani eggs and juveniles than did plots previously planted to pigeonpea, cowpea, or mungbean. Continuous cropping of sorghum in the rainy season and safflower in the post-rainy season markedly reduced the population density of H. cajani. Sorghum, safflower, and chickpea favored increased population densities of H. retusus. Adding cowpea to the system resulted in a significant increase in the densities of R. reniformis. Mean densities of total plant-parasitic nematodes were three times greater in double crop systems, with pigeonpea as a component intercrop than in single crop systems with rainy season fallow component. Cropping systems had a regulatory effect on the nematode populations and could be an effective nematode management tactic. Intercropping of sorghum with H. cajani tolerant pigeonpea could be effective in increasing the productivity of traditional production systems in H. cajani infested regions. PMID:19277141
NASA Astrophysics Data System (ADS)
Uździcka, Bogna; Stróżecki, Marcin; Urbaniak, Marek; Juszczak, Radosław
2017-07-01
The aim of this paper is to demonstrate that spectral vegetation indices are good indicators of parameters describing the intensity of CO2 exchange between crops and the atmosphere. Measurements were conducted over 2011-2013 on plots of an experimental arable station on winter wheat, winter rye, spring barley, and potatoes. CO2 fluxes were measured using the dynamic closed chamber system, while spectral vegetation indices were determined using SKYE multispectral sensors. Based on spectral data collected in 2011 and 2013, various models to estimate net ecosystem productivity and gross ecosystem productivity were developed. These models were then verified based on data collected in 2012. The R2 for the best model based on spectral data ranged from 0.71 to 0.83 and from 0.78 to 0.92, for net ecosystem productivity and gross ecosystem productivity, respectively. Such high R2 values indicate the utility of spectral vegetation indices in estimating CO2 fluxes of crops. The effects of the soil background turned out to be an important factor decreasing the accuracy of the tested models.
A half-century analysis of landscape dynamics in southern Québec, Canada.
Jobin, Benoît; Latendresse, Claudie; Baril, Alain; Maisonneuve, Charles; Boutin, Céline; Côté, Dominique
2014-04-01
We studied landscape dynamics for three time periods (<1950, 1965, and 1997) along a gradient of agricultural intensity from highly intensive agriculture to forested areas in southern Québec. Air photos were analyzed to obtain long-term information on land cover (crop and habitat types) and linear habitats (hedgerows and riparian habitats) and landscape metrics were calculated to quantify changes in habitat configuration. Anthropogenic areas increased in all types of landscapes but mostly occurred in the highly disturbed cash crop dominated landscape. Perennial crops (pasture and hayfields) were largely converted into annual crops (corn and soybean) between 1965 and 1997. The coalescence of annual crop fields resulted in a more homogeneous agricultural landscape. Old fields and forest cover was consistently low and forest fragmentation remained stable through time in the intensive agriculture landscapes. However, forest cover increased and forest fragmentation receded in the forest-dominated landscapes following farm abandonment and the transition of old fields into forests. Tree-dominated hedgerows and riparian habitats increased in areas with intensive agriculture. Observed changes in land cover classes are related to proximate factors, such as surficial deposits and topography. Agriculture intensification occurred in areas highly suitable for agriculture whereas farm abandonment was observed in poor-quality agriculture terrains. Large-scale conversion of perennial crops into annual crops along with continued urbanization exerts strong pressures on residual natural habitats and their inhabiting wildlife. The afforestation process occurring in the more forested landscapes along with the addition of tree-dominated hedgerows and riparian habitats in the agriculture-dominated landscapes should improve landscape ecological value.
Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.
Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias
2017-11-03
Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.
Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Corn Farmscapes
Cottrell, Ted E.; Tillman, P. Glynn
2015-01-01
The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States but little is known concerning its spatiotemporal distribution in corn cropping systems. Therefore, the spatiotemporal distribution of C. hilaris in farmscapes, when corn was adjacent to cotton, peanut, or both, was examined weekly. The spatial patterns of C. hilaris counts were analyzed using Spatial Analysis by Distance Indices methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops in corn–peanut–cotton farmscapes. This stink bug was detected in six of seven corn–cotton farmscapes, four of six corn–peanut farmscapes, and in both corn–peanut–cotton farmscapes. The frequency of C. hilaris in cotton (89.47%) was significantly higher than in peanut (7.02%) or corn (3.51%). This stink bug fed on noncrop hosts that grew in field borders adjacent to crops. The spatial distribution of C. hilaris in crops and the capture of C. hilaris adults and nymphs in pheromone-baited traps near noncrop hosts indicated that these hosts were sources of this stink bug dispersing into crops, primarily cotton. Significant aggregated spatial distributions were detected in cotton on some dates within corn–peanut–cotton farmscapes. Maps of local clustering indices depicted small patches of C. hilaris in cotton or cotton–sorghum at the peanut–cotton interface. Factors affecting the spatiotemporal dynamics of C. hilaris in corn farmscapes are discussed. PMID:25843581
Lalthanzara, H; Ramanujam, S N; Jha, L K
2011-09-01
Earthworm population dynamics was studied in two agroforestry systems in the tropical hilly terrain of Mizoram, north-east India, over a period of 24 months, from July 2002 to June 2004. Two sites of agroforestry situated at Sakawrtuichhun (SKT) and Pachhunga University College (PUC) campus, Aizawl, having pineapple as the main crop, were selected for detail studies on population dynamics. Five of the total twelve species of earthworm reported from the state were recorded in the study sites. The density of earthworm ranged from 6 to 243 ind.m(-2) and biomass from 3.2 - 677.64 g.m(-2) in SKT. Comparatively the density and biomass in PUC, which is at relatively higher altitude were lowerwith a range of 0 to 176 ind.m(-2) and biomass from 0 - 391.36 g.m(-2) respectively. Population dynamics of earthworm was significantly correlated with rainfall and physical characters of the soil. Earthworm biomass was significantly affected by rainfall and moisture content of the soil. The influence of chemical factors was relatively less.
Plants for space plantations. [crops for closed life support systems
NASA Technical Reports Server (NTRS)
Nikishanova, T. I.
1978-01-01
Criteria for selection of candidate crops for closed life support systems are presented and discussed, and desired characteristics of candidate higher plant crops are given. Carbohydrate crops, which are most suitable, grown worldwide are listed and discussed. The sweet potato, ipomoea batatas Poir., is shown to meet the criteria to the greatest degree, and the criteria are recommended as suitable for initial evaluation of candidate higher plant crops for such systems.
USDA-ARS?s Scientific Manuscript database
The tarnished plant bug, Lygus lineolaris (Palisot De Beauvois) is a highly polyphagous insect that feeds on numerous wild and cultivated host plants. Although transgenic crops expressing insecticidal toxins have been available for approximately 20 years for some insect crop pests, none have been d...
USDA-ARS?s Scientific Manuscript database
This research analyzes two groundwater conservation policies in the Kansas High Plains located within the Ogallala aquifer: 1) cost-share assistance to increase irrigation efficiency; and 2) incentive payments to convert irrigated crop production to dryland crop production. To compare the cost-effec...
USDA-ARS?s Scientific Manuscript database
Hybridization is known to occur between cultivated and wild populations of numerous plant species. This represents a major mechanism by which a wild population’s genetic structure and evolutionary dynamics could be altered. Studying crop-derived alleles in wild populations is also relevant to assess...
Combined use of neutron thermalization and electromagnetic sensing in assessing soil water dynamics
USDA-ARS?s Scientific Manuscript database
Agriculture is by far the largest consumer of available fresh water, accounting for 70% of withdrawals worldwide. By meeting increased future demands for food and fiber, our needs will need to be met by improving the efficient use of both irrigation and precipitation for crop production. Field crop ...
USDA-ARS?s Scientific Manuscript database
An improved ant colony optimization (ACO) formulation for the allocation of crops and water to different irrigation areas is developed. The formulation enables dynamic adjustment of decision variable options and makes use of visibility factors (VFs, the domain knowledge that can be used to identify ...
USDA-ARS?s Scientific Manuscript database
The endospore-forming bacterium Pasteuria penetrans is an obligate parasite of root-knot nematodes (Meloidogyne spp.). This study was a continuation of earlier research to determine the effect of crop sequence on abundance of the bacterium, and was conducted from 2000 to 2008 at a field site natura...
NASA Astrophysics Data System (ADS)
Babushkina, Elena A.; Belokopytova, Liliana V.; Shah, Santosh K.; Zhirnova, Dina F.
2018-05-01
Interrelations of the yield variability of the main crops (wheat, barley, and oats) with hydrothermal regime and growth of conifer trees ( Pinus sylvestris and Larix sibirica) in forest-steppes were investigated in Khakassia, South Siberia. An attempt has been made to understand the role and mechanisms of climatic impact on plants productivity. It was found that amongst variables describing moisture supply, wetness index had maximum impact. Strength of climatic response and correlations with tree growth are different for rain-fed and irrigated crops yield. Separated high-frequency variability components of yield and tree-ring width have more pronounced relationships between each other and with climatic variables than their chronologies per se. Corresponding low-frequency variability components are strongly correlated with maxima observed after 1- to 5-year time shift of tree-ring width. Results of analysis allowed us to develop original approach of crops yield dynamics reconstruction on the base of high-frequency variability component of the growth of pine and low-frequency one of larch.
Crop Species Diversity Changes in the United States: 1978–2012
Aguilar, Jonathan; Gramig, Greta G.; Hendrickson, John R.; Archer, David W.; Forcella, Frank; Liebig, Mark A.
2015-01-01
Anecdotal accounts regarding reduced US cropping system diversity have raised concerns about negative impacts of increasingly homogeneous cropping systems. However, formal analyses to document such changes are lacking. Using US Agriculture Census data, which are collected every five years, we quantified crop species diversity from 1978 to 2012, for the contiguous US on a county level basis. We used Shannon diversity indices expressed as effective number of crop species (ENCS) to quantify crop diversity. We then evaluated changes in county-level crop diversity both nationally and for each of the eight Farm Resource Regions developed by the National Agriculture Statistics Service. During the 34 years we considered in our analyses, both national and regional ENCS changed. Nationally, crop diversity was lower in 2012 than in 1978. However, our analyses also revealed interesting trends between and within different Resource Regions. Overall, the Heartland Resource Region had the lowest crop diversity whereas the Fruitful Rim and Northern Crescent had the highest. In contrast to the other Resource Regions, the Mississippi Portal had significantly higher crop diversity in 2012 than in 1978. Also, within regions there were differences between counties in crop diversity. Spatial autocorrelation revealed clustering of low and high ENCS and this trend became stronger over time. These results show that, nationally counties have been clustering into areas of either low diversity or high diversity. Moreover, a significant trend of more counties shifting to lower rather than to higher crop diversity was detected. The clustering and shifting demonstrates a trend toward crop diversity loss and attendant homogenization of agricultural production systems, which could have far-reaching consequences for provision of ecosystem system services associated with agricultural systems as well as food system sustainability. PMID:26308552
New horizons. [assessment of technology developed and utilized under various NASA programs
NASA Technical Reports Server (NTRS)
1975-01-01
The contribution of space exploration and space related research to the future of man and the accomplishments of the space program are assessed. Topics discussed include: the role of applications satellites in crop surveillance, land use surveys, weather forecasting, education, communications, and pollution monitoring; planetary studies which examine the origin and evolution of the solar system, including dynamic processes that bear directly on earth's environment; and fuel conservation and development of new energy sources.
NASA Astrophysics Data System (ADS)
Weindl, Isabelle; Popp, Alexander; Bodirsky, Benjamin Leon; Rolinski, Susanne; Lotze-Campen, Hermann; Biewald, Anne; Humpenöder, Florian; Dietrich, Jan Philipp; Stevanović, Miodrag
2017-12-01
Land use change has been the primary driving force of human alteration of terrestrial ecosystems. With 80% of agricultural land dedicated to livestock production, the sector is an important lever to attenuate land requirements for food production and carbon emissions from land use change. In this study, we quantify impacts of changing human diets and livestock productivity on land dynamics and depletion of carbon stored in vegetation, litter and soils. Across all investigated productivity pathways, lower consumption of livestock products can substantially reduce deforestation (47-55%) and cumulative carbon losses (34-57%). On the supply side, already minor productivity growth in extensive livestock production systems leads to substantial CO2 emission abatement, but the emission saving potential of productivity gains in intensive systems is limited, also involving trade-offs with soil carbon stocks. If accounting for uncertainties related to future trade restrictions, crop yields and pasture productivity, the range of projected carbon savings from changing diets increases to 23-78%. Highest abatement of carbon emissions (63-78%) can be achieved if reduced consumption of animal-based products is combined with sustained investments into productivity increases in plant production. Our analysis emphasizes the importance to integrate demand- and supply-side oriented mitigation strategies and to combine efforts in the crop and livestock sector to enable synergies for climate protection.
Yuan, Pan; Ding, Guang-Da; Cai, Hong-Mei; Jin, Ke-Mo; Broadley, Martin Roger; Xu, Fang-Sen; Shi, Lei
2016-08-01
An important adaptation of plants to phosphorus (P) deficiency is to alter root system architecture (RSA) to increase P acquisition from the soil, but soil-based observations of RSA are technically challenging, especially in mature plants. The aim of this study was to investigate the root development and RSA of oilseed rape (Brassica napus L.) under low and high soil P conditions during an entire growth cycle. A new large Brassica-rhizotron system (approx. 118-litre volume) was developed to study the RSA dynamics of B. napus 'Zhongshuang11' in soils, using top-soils supplemented with low P (LP) or high P (HP) for a full plant growth period. Total root length (TRL), root tip number (RTN), root length density (RLD), biomass and seed yield traits were measured. TRL and RTN increased more rapidly in HP than LP plants from seedling to flowering stages. Both traits declined from flowering to silique stages, and then increased slightly in HP plants; in contrast, root senescence was observed in LP plants. RSA parameters measured from the polycarbonate plates were empirically consistent with analyses of excavated roots. Seed yield and shoot dry weights were closely associated positively with root dry weights, TRL, RLD and RTN at both HP and LP. The Brassica-rhizotron system is an effective method for soil-based root phenotyping across an entire growth cycle. Given that root senescence is likely to occur earlier under low P conditions, crop P deficiency is likely to affect late water and nitrogen uptake, which is critical for efficient resource use and optimal crop yields. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Environmental and management impacts on temporal variability of soil hydraulic properties
NASA Astrophysics Data System (ADS)
Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.
2012-04-01
Soil hydraulic properties underlie temporal changes caused by different natural and management factors. Rainfall intensity, wet-dry cycles, freeze-thaw cycles, tillage and plant effects are potential drivers of the temporal variability. For agricultural purposes it is important to determine the possibility of targeted influence via management. In no-till systems e.g. root induced soil loosening (biopores) is essential to counteract natural soil densification by settling. The present work studies two years of temporal evolution of soil hydraulic properties in a no-till crop rotation (durum wheat-field pea) with two cover crops (mustard and rye) having different root systems (taproot vs. fibrous roots) as well as a bare soil control. Soil hydraulic properties such as near-saturated hydraulic conductivity, flow weighted pore radius, pore number and macroporosity are derived from measurements using a tension infiltrometer. The temporal dynamics are then analysed in terms of potential driving forces. Our results revealed significant temporal changes of hydraulic conductivity. When approaching saturation, spatial variability tended to dominate over the temporal evolution. Changes in near-saturated hydraulic conductivity were mainly a result of changing pore number, while the flow weighted mean pore radius showed less temporal dynamic in the no-till system. Macroporosity in the measured range of 0 to -10 cm pressure head ranged from 1.99e-4 to 8.96e-6 m3m-3. The different plant coverage revealed only minor influences on the observed system dynamics. Mustard increased slightly the flow weighted mean pore radius, being 0.090 mm in mustard compared to 0.085 mm in bare soil and 0.084 mm in rye. Still pore radius changes were of minor importance for the overall temporal dynamics. Rainfall was detected as major driving force of the temporal evolution of structural soil hydraulic properties at the site. Soil hydraulic conductivity in the slightly unsaturated range (-7 cm to -10 cm) showed a similar time course as a moving average of rainfall. Drying induced a decrease in conductivity while wetting of the soil resulted in higher conductivity values. Approaching saturation however, the drying phase showed a different behaviour with increasing values of hydraulic conductivity. This may be explained probably by formation of cracks acting as large macropores. We concluded that aggregate coalescence as a function of capillary forces and soil rheologic properties (cf. Or et al., 2002) are a main predictor of temporal dynamics of near saturated soil hydraulic properties while different plant covers only had a minor effect on the observed system dynamics. Or, D., Ghezzehei, T.A. 2002. Modeling post-tillage soil structural dynamics. a review. Soil Till Res. 64, 41-59.
The Use of Cover Crops as Climate-Smart Management in Midwest Cropping Systems
NASA Astrophysics Data System (ADS)
Basche, A.; Miguez, F.; Archontoulis, S.; Kaspar, T.
2014-12-01
The observed trends in the Midwestern United States of increasing rainfall variability will likely continue into the future. Events such as individual days of heavy rain as well as seasons of floods and droughts have large impacts on agricultural productivity and the natural resource base that underpins it. Such events lead to increased soil erosion, decreased water quality and reduced corn and soybean yields. Winter cover crops offer the potential to buffer many of these impacts because they essentially double the time for a living plant to protect and improve the soil. However, at present, cover crops are infrequently utilized in the Midwest (representing 1-2% of row cropped land cover) in particular due to producer concerns over higher costs and management, limited time and winter growing conditions as well as the potential harm to corn yields. In order to expand their use, there is a need to quantify how cover crops impact Midwest cropping systems in the long term and namely to understand how to optimize the benefits of cover crops while minimizing their impacts on cash crops. We are working with APSIM, a cropping systems platform, to specifically quantify the long term future impacts of cover crop incorporation in corn-based cropping systems. In general, our regional analysis showed only minor changes to corn and soybean yields (<1% differences) when a cover crop was or was not included in the simulation. Further, a "bad spring" scenario (where every third year had an abnormally wet/cold spring and cover crop termination and planting cash crop were within one day) did not result in any major changes to cash crop yields. Through simulations we estimate an average increase of 4-9% organic matter improvement in the topsoil and an average decrease in soil erosion of 14-32% depending on cover crop planting date and growth. Our work is part of the Climate and Corn-based Cropping Systems Coordinated Agriculture Project (CSCAP), a collaboration of eleven Midwestern institutions established to evaluate how conservation practices, including cover crops, improve the resilience of Midwest agriculture to future change. Such collaborations can help better quantify long term impacts of conservation practices on the landscape that ultimately lead to more climate-smart management of such agricultural systems.
Detecting crop growth stages of maize and soybeans by using time-series MODIS data
NASA Astrophysics Data System (ADS)
Sakamoto, T.; Wardlow, B. D.; Gitelson, A. A.; Verma, S. B.; Suyker, A. E.; Arkebauer, T. J.
2009-12-01
The crop phenological stages are one of essential parameters for evaluating crop productivity based on a crop simulation model. In this study, we improved a method named the Wavelet-based Filter for detecting Crop Phenology (WFCP) for detecting the specific phenological dates of maize and soybeans. The improved method was applied to MODIS-derived Wide Dynamic Range Vegetation Index (WDRVI) over a 6-year period (2003 to 2008) for three experimental fields planted to either maize or soybeans as part of the Carbon Sequestration Program (CSP) at the University of Nebraska-Lincoln (UNL). Using the ground-based crop growth stage observations collected by the CSP, it was confirmed that the improved method can estimate the specific phenological dates of maize (V2.5, R1, R5 and R6) and soybeans (V1, R5, R6 and R7) with reasonable accuracy.
Lamichhane, Jay Ram; Devos, Yann; Beckie, Hugh J; Owen, Micheal D K; Tillie, Pascal; Messéan, Antoine; Kudsk, Per
2017-06-01
Conventionally bred (CHT) and genetically modified herbicide-tolerant (GMHT) crops have changed weed management practices and made an important contribution to the global production of some commodity crops. However, a concern is that farm management practices associated with the cultivation of herbicide-tolerant (HT) crops further deplete farmland biodiversity and accelerate the evolution of herbicide-resistant (HR) weeds. Diversification in crop systems and weed management practices can enhance farmland biodiversity, and reduce the risk of weeds evolving herbicide resistance. Therefore, HT crops are most effective and sustainable as a component of an integrated weed management (IWM) system. IWM advocates the use of multiple effective strategies or tactics to manage weed populations in a manner that is economically and environmentally sound. In practice, however, the potential benefits of IWM with HT crops are seldom realized because a wide range of technical and socio-economic factors hamper the transition to IWM. Here, we discuss the major factors that limit the integration of HT crops and their associated farm management practices in IWM systems. Based on the experience gained in countries where CHT or GMHT crops are widely grown and the increased familiarity with their management, we propose five actions to facilitate the integration of HT crops in IWM systems within the European Union.
Owusu-Edusei, K; Biddle, E A
2007-04-01
Cost-effective rollover protective structures (CROPS) are less costly model-specific rollover protective structure (ROPS) retrofits that are being developed and evaluated with the hope of increasing adoption and eventually preventing or mitigating injuries due to tractor overturns. A dynamic cohort of the estimated retrofittable non-ROPS tractors (accounting for attrition due to aging) was tracked over a 20-year period to determine the expected costs, as well as the expected number of fatal and non-fatal injuries resulting from tractor overturns. Two alternatives were tracked: No-ROPS and Install-CROPS. For a starting cohort size of 1,065,164 (an estimate for the year 2004), the Install-CROPS option prevented an estimated total of 878 (192 fatal and 686 non-fatal) injuries over the 20-year period. Expected costs were $513 million (cost of installing CROPS on all the non-ROPS tractors plus cost of the associated injuries) and $284 million (cost of injuries resulting from the No-ROPS option) over the same time period. Thus, the net cost per injury prevented was $260,820. When the cost of intervention ($1000 for purchasing, shipping, and installation of existing ROPS retrofit) was used in the analysis, the cost-effectiveness ratio was $927,000 per injury prevented over the 20-year period. Thus, installing CROPS instead of existing ROPS retrofits improved the cost-effectiveness ratio substantially, with a 72% reduction in the net cost per injury prevented.
Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement
Wu, Alex; Song, Youhong; van Oosterom, Erik J.; Hammer, Graeme L.
2016-01-01
The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation. PMID:27790232
Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement.
Wu, Alex; Song, Youhong; van Oosterom, Erik J; Hammer, Graeme L
2016-01-01
The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.
HERBICIDE SENSITIVITY OF ECHINOCHLOA CRUS-GALLI POPULATIONS: A COMPARISON BETWEEN CROPPING SYSTEMS.
Claerhout, S; De Cauwer, B; Reheul, D
2014-01-01
Echinochloa crus-galli populations exhibit high morphological variability and their response to herbicides varies from field to field. Differential response to herbicides could reflect differences in selection pressure, caused by years of cropping system related herbicide usage. This study investigates the relation between herbicide sensitivity of Echinochloa crus-galli populations and the cropping system to which they were subjected. The herbicide sensitivity of Echinochloa crus-galli was evaluated for populations collected on 18 fields, representing three cropping systems, namely (1) a long-term organic cropping system, (2) a conventional cropping system with corn in crop rotation or (3) a conventional cropping system with long-term monoculture of corn. Each cropping system was represented by 6 E. crus-galli populations. All fields were located on sandy soils. Dose-response pot experiments were conducted in the greenhouse to assess the effectiveness of three foliar-applied corn herbicides: nicosulfuron (ALS-inhibitor), cycloxydim (ACCase-inhibitor) and topramezone (HPPD-inhibitor), and two soil-applied corn herbicides: S-metolachlor and dimethenamid-P (both VLCFA-inhibitors). Foliar-applied herbicides were tested at a quarter, half and full recommended doses. Soil-applied herbicides were tested within a dose range of 0-22.5 g a.i. ha(-1) for S-metolachlor and 0-45 g a.i. ha(-1) for dimethenamid-P. Foliar-applied herbicides were applied at the three true leaves stage. Soil-applied herbicides were treated immediately after sowing the radicle-emerged seeds. All experiments were performed twice. The foliage dry weight per pot was determined four weeks after treatment. Plant responses to herbicides were expressed as biomass reduction (%, relative to the untreated control). Sensitivity to foliar-applied herbicides varied among cropping systems. Compared to populations from monoculture corn fields, populations originating from organic fields were significantly more sensitive to cycloxydim, topramezone and nicosulfuron (resp. 5.3%, 5.9% and 12.3%). Populations from the conventional crop rotation system showed intermediate sensitivity levels. Contrary to foliar-applied herbicides, the effectiveness of soil-applied herbicides was not affected by cropping system. Integrated weed management may be necessary to preserve herbicide efficacy on the long term.
Effects of biochar addition to soil on nitrogen fluxes in a winter wheat lysimeter experiment
NASA Astrophysics Data System (ADS)
Hüppi, Roman; Leifeld, Jens; Neftel, Albrecht; Conen, Franz; Six, Johan
2014-05-01
Biochar is a carbon-rich, porous residue from pyrolysis of biomass that potentially increases crop yields by reducing losses of nitrogen from soils and/or enhancing the uptake of applied fertiliser by the crops. Previous research is scarce about biochar's ability to increase wheat yields in temperate soils or how it changes nitrogen dynamics in the field. In a lysimeter system with two different soils (sandy/silt loam) nitrogen fluxes were traced by isotopic 15N enriched fertiliser to identify changes in nitrous oxide emissions, leaching and plant uptake after biochar addition. 20t/ha woodchip-waste biochar (pH=13) was applied to these soils in four lysimeters per soil type; the same number of lysimeters served as a control. The soils were cropped with winter wheat during the season 2012/2013. 170 kg-N/ha ammonium nitrate fertiliser with 10% 15N was applied in 3 events during the growing season and 15N concentrations where measured at different points in time in plant, soil, leachate and emitted nitrous oxide. After one year the lysimeter system showed no difference between biochar and control treatment in grain- and straw yield or nitrogen uptake. However biochar did reduce nitrous oxide emissions in the silt loam and losses of nitrate leaching in sandy loam. This study indicates potential reduction of nitrogen loss from cropland soil by biochar application but could not confirm increased yields in an intensive wheat production system.
RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment
NASA Astrophysics Data System (ADS)
Di, L.; Yu, G.; Kang, L.
2014-12-01
Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.
Murúa, M Gabriela; Cazado, Lucas E; Casmuz, Augusto; Herrero, M Inés; Villagrán, M Elvira; Vera, Alejandro; Sosa-Gómez, Daniel R; Gastaminza, Gerardo
2016-01-01
The Heliothinae complex in Argentina encompasses Helicoverpa gelotopoeon (Dyar), Helicoverpa zea (Boddie), Helicoverpa armigera (Hübner), and Chloridea virescens (Fabricius). In Tucumán, the native species H. gelotopoeon is one of the most voracious soybean pests and also affects cotton and chickpea, even more in soybean-chickpea succession cropping systems. Differentiation of the Heliothinae complex in the egg, larva, and pupa stages is difficult. Therefore, the observation of the adult wing pattern design and male genitalia is useful to differentiate species. The objective of this study was to identify the species of the Heliothinae complex, determine population fluctuations of the Heliothinae complex in soybean and chickpea crops using male moths collected in pheromone traps in Tucuman province, and update the geographical distribution of H. armigera in Argentina. The species found were H. gelotopoeon, H. armigera, H. zea, and C. virescens. Regardless of province, county, crop, and year, the predominant species was H. gelotopoeon Considering the population dynamics of H. gelotopoeon and H. armigera in chickpea and soybean crops, H. gelotopoeon was the most abundant species in both crops, in all years sampled, and the differences registered were significant. On the other hand, according to the Sistema Nacional Argentino de Vigilancia y Monitoreo de Plagas (SINAVIMO) database and our collections, H. armigera was recorded in eight provinces and 20 counties of Argentina, and its larvae were found on soybean, chickpea, sunflower crops and spiny plumeless thistle (Carduus acanthoides). This is the first report of H. armigera in sunflower and spiny plumeless thistle in Argentina. © The Author 2016. Published by Oxford University Press on behalf of the Entomological Society of America.
Agricultural conversion of floodplain ecosystems: implications for groundwater quality.
Schilling, Keith E; Jacobson, Peter J; Vogelgesang, Jason A
2015-04-15
With current trends of converting grasslands to row crop agriculture in vulnerable areas, there is a critical need to evaluate the effects of land use on groundwater quality in large river floodplain systems. In this study, groundwater hydrology and nutrient dynamics associated with three land cover types (grassland, floodplain forest and cropland) were assessed at the Cedar River floodplain in southeastern Iowa. The cropland site consisted of newly-converted grassland, done specifically for our study. Our objectives were to evaluate spatial and temporal variations in groundwater hydrology and quality, and quantify changes in groundwater quality following land conversion from grassland to row crop in a floodplain. We installed five shallow and one deep monitoring wells in each of the three land cover types and recorded water levels and quality over a three year period. Crop rotations included soybeans in year 1, corn in year 2 and fallow with cover crops during year 3 due to river flooding. Water table levels behaved nearly identically among the sites but during the second and third years of our study, NO₃-N concentrations in shallow floodplain groundwater beneath the cropped site increased from 0.5 mg/l to more than 25 mg/l (maximum of 70 mg/l). The increase in concentration was primarily associated with application of liquid N during June of the second year (corn rotation), although site flooding may have exacerbated NO₃-N leaching. Geophysical investigation revealed differences in ground conductivity among the land cover sites that related significantly to variations in groundwater quality. Study results provide much-needed information on the effects of different land covers on floodplain groundwater and point to challenges ahead for meeting nutrient reduction goals if row crop land use expands into floodplains. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, J.; Wang, X.; Wang, W.
2010-12-01
The Kaidu River originates from the central southern slopes of the Tian Shan from where it flows through the Yulduz Basin and the Yanqi Basin into Lake Bosten. There has been intensive agricultural development along the Kaidu River in the Yanqi Basin. Corn and pepper are two of the main crops. Here, we present a study includes comparisons of soil organic carbon (SOC) between typical native vegtation types (e.g., Glycyrhiza uralensis Fisch, Achnatherum splendens and Sophora alopecuroides Linn) and agricultural crops (i.e., corn and pepper). Fourteen soil pits were sampled at five depths (0-5, 5-15, 15-30, 30-50 and 50-100 cm) in August 2010 (Figure 1). Soil organic matter are determined using the traditional Walkley and Black method and Loss-on-ignition at 375°C for 17 hours. As expected, agricultural soils contain higher SOC than non-agriculatural lands. Native vegetation has various effects on vertical distribution of SOC. We discuss how root system influences SOC dynamics along the Kaidu River in the central Xinjiang, China. Fig. 1. Map of sampling sites along the Kaidu River in northwestern China.
Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli
2017-10-01
Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1 yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.
Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.; ...
2016-10-03
The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.
The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less
USDA-ARS?s Scientific Manuscript database
Cover crops are a key component of conservation cropping systems. They can also be a key component of integrated crop-livestock systems by offering high-quality forage during short periods between cash crops. The impact of cattle grazing on biologically active soil C and N fractions has not receiv...
NASA Astrophysics Data System (ADS)
Zhang, J.; Becker-Reshef, I.; Justice, C. O.
2013-12-01
Although agricultural production has been rising in the past years, drought remains the primary cause of crop failure, leading to food price instability and threatening food security. The recent 'Global Food Crisis' in 2008, 2011 and 2012 has put drought and its impact on crop production at the forefront, highlighting the need for effective agricultural drought monitoring. Satellite observations have proven a practical, cost-effective and dynamic tool for drought monitoring. However, most satellite based methods are not specially developed for agriculture and their performances for agricultural drought monitoring still need further development. Wheat is the most widely grown crop in the world, and the recent droughts highlight the importance of drought monitoring in major wheat producing areas. As the largest wheat producing state in the US, Kansas plays an important role in both global and domestic wheat markets. Thus, the objective of this study is to investigate the capabilities of remotely sensed crop indicators for effective agricultural drought monitoring in Kansas wheat-grown regions using MODIS data and crop yield statistics. First, crop indicators such as NDVI, anomaly and cumulative metrics were calculated. Second, the varying impacts of agricultural drought at different stages were explored by examining the relationship between the derived indicators and yields. Also, the starting date of effective agricultural drought early detection and the key agricultural drought alert period were identified. Finally, the thresholds of these indicators for agricultural drought early warning were derived and the implications of these indicators for agricultural drought monitoring were discussed. The preliminary results indicate that drought shows significant impacts from the mid-growing-season (after Mid-April); NDVI anomaly shows effective drought early detection from Late-April, and Late-April to Early-June can be used as the key alert period for agricultural drought early warning; and drought occurring in Early-May has the most significant agricultural impacts. This research intends to help prototype an agricultural drought alert system, which could alert crop analysts to agricultural drought vulnerable areas/periods and provide tools for assessing crop outlooks in these regions.
USDA-ARS?s Scientific Manuscript database
Chemical products such as pesticides have been used to increase crop production, especially in undeveloped countries. Poultry litter, the combination of feces and bedding materials, has also been used as an alternative to improve soil quality for crop production. In this study, five treatments were ...
Inexplicable or Simply Unexplained? The Management of Maize Seed in Mexico
Dyer, George A.; López-Feldman, Alejandro
2013-01-01
Farmer management of plant germplasm pre-dates crop domestication, but humans’ role in crop evolution and diversity remains largely undocumented and often contested. Seemingly inexplicable practices observed throughout agricultural history, such as exchanging or replacing seed, continue to structure crop populations across the developing world. Seed management practices can be construed as events in the life history of crops and management data used to model crop demography, but this requires suitable quantitative data. As a prerequisite to addressing the causes and implications of maize seed management, we describe its patterns of variation across Mexico by drawing from the literature and new analysis. We find that rates of seed replacement, introduction and diffusion differ significantly across regions and altitudinal zones, but interactions among explanatory factors can obscure patterns of variation. The type, source, geographic origin and ownership of seed help explain observed rates. Yet, controlling for the characteristics of germplasm barely reduces interregional differences vastly exceeding variation across elevations. With few exceptions, monotonic altitudinal trends are absent. Causal relationships between management practices and the physical environment could determine farmers’ wellbeing and crop conservation in the face of climate change. Scarce and inconsistent data on management nevertheless could prevent an understanding of these relationships. Current conceptions on the management and dynamics of maize diversity are founded on a patchwork of observations in surprisingly few and dissimilar environments. Our estimates of management practices should shed light on differences in maize population dynamics across Mexico. Consistency with previous studies spanning over a decade suggests that common sets of forces are present within large areas, but causal associations remain unknown. The next step in explaining crop diversity should address variation in seed management across space and time simultaneously while identifying farmers’ values and motivations as underlying forces. PMID:23840847
Inexplicable or simply unexplained? The management of maize seed in Mexico.
Dyer, George A; López-Feldman, Alejandro
2013-01-01
Farmer management of plant germplasm pre-dates crop domestication, but humans' role in crop evolution and diversity remains largely undocumented and often contested. Seemingly inexplicable practices observed throughout agricultural history, such as exchanging or replacing seed, continue to structure crop populations across the developing world. Seed management practices can be construed as events in the life history of crops and management data used to model crop demography, but this requires suitable quantitative data. As a prerequisite to addressing the causes and implications of maize seed management, we describe its patterns of variation across Mexico by drawing from the literature and new analysis. We find that rates of seed replacement, introduction and diffusion differ significantly across regions and altitudinal zones, but interactions among explanatory factors can obscure patterns of variation. The type, source, geographic origin and ownership of seed help explain observed rates. Yet, controlling for the characteristics of germplasm barely reduces interregional differences vastly exceeding variation across elevations. With few exceptions, monotonic altitudinal trends are absent. Causal relationships between management practices and the physical environment could determine farmers' wellbeing and crop conservation in the face of climate change. Scarce and inconsistent data on management nevertheless could prevent an understanding of these relationships. Current conceptions on the management and dynamics of maize diversity are founded on a patchwork of observations in surprisingly few and dissimilar environments. Our estimates of management practices should shed light on differences in maize population dynamics across Mexico. Consistency with previous studies spanning over a decade suggests that common sets of forces are present within large areas, but causal associations remain unknown. The next step in explaining crop diversity should address variation in seed management across space and time simultaneously while identifying farmers' values and motivations as underlying forces.
Putting mechanisms into crop production models.
Boote, Kenneth J; Jones, James W; White, Jeffrey W; Asseng, Senthold; Lizaso, Jon I
2013-09-01
Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop growth and development and at season-end, final yield. Their ability to integrate effects of genetics, environment and crop management have led to applications ranging from understanding gene function to predicting potential impacts of climate change. The history of crop models is reviewed briefly, and their level of mechanistic detail for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use efficiency is discussed. Crop models have improved steadily over the past 30-40 years, but much work remains. Improvements are needed for the prediction of transpiration response to elevated CO₂ and high temperature effects on phenology and reproductive fertility, and simulation of root growth and nutrient uptake under stressful edaphic conditions. Mechanistic improvements are needed to better connect crop growth to genetics and to soil fertility, soil waterlogging and pest damage. Because crop models integrate multiple processes and consider impacts of environment and management, they have excellent potential for linking research from genomics and allied disciplines to crop responses at the field scale, thus providing a valuable tool for deciphering genotype by environment by management effects. © 2013 John Wiley & Sons Ltd.
The potential of plant microbiota in reducing postharvest food loss.
Buchholz, Franziska; Kostić, Tanja; Sessitsch, Angela; Mitter, Birgit
2018-03-26
The role of the plant microbiota in plant establishment, growth and health is well studied, but the dynamics of postharvest crop microbiota and its role in postharvest crop quality are largely unexplored, although food loss is an enormous issue worldwide. The microbiota might be especially important during crop storage by either preventing or favouring rots, or quality loss due to, for example, sprouting, saccharification, water loss or spoilage. We need more research on plant-microbe interactions in postharvest crops to be in future able to provide microbial solutions for plant production along the whole food chain from field to fork. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.
NASA Technical Reports Server (NTRS)
1978-01-01
The author has identified the following significant results. Yield modelling for crop production estimation derived a means of predicting the within-a-year yield and the year-to-year variability of yield over some fixed or randomly located unit of area. Preliminary studies indicated that the requirements for interpreting LANDSAT data for yield may be sufficiently similar to those of signature extension that it is feasible to investigate the automated estimation of production. The concept of an advanced yield model consisting of both spectral and meteorological components was endorsed. Rationale for using meteorological parameters originated from known between season and near harvest dynamics in crop environmental-condition-yield relationships.
Lammoglia, Sabine-Karen; Moeys, Julien; Barriuso, Enrique; Larsbo, Mats; Marín-Benito, Jesús-María; Justes, Eric; Alletto, Lionel; Ubertosi, Marjorie; Nicolardot, Bernard; Munier-Jolain, Nicolas; Mamy, Laure
2017-03-01
The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.
Graves, Emily E; Holyoak, Marcel; Rodd Kelsey, T; Meese, Robert J
2013-01-01
Population trends represent a minimum amount of information required to assess the conservation status of a species. However, understanding and detecting trends can be complicated by variation among habitats and regions, and by dispersal connecting habitats through source-sink dynamics. We analyzed trends in breeding populations between habitats and regions to better understand the overall dynamics of a species' decline. Specifically, we analyzed historical trends in breeding populations of tricolored blackbirds (Agelaius tricolor) using breeding records from 1907 to 2009. The species breeds itinerantly and ephemerally uses multiple habitat types and breeding areas, which make interpretation of trends complex. We found overall abundance declines of 63% between 1935 and 1975. Since 1980 overall declines became nonsignificant and obscure despite large amounts of data from 1980 to 2009. Temporal trends differed between breeding habitat types and were associated with regional differences in population declines. A new habitat, triticale crops (a wheat-rye hybrid grain) produced colonies 40× larger, on average, than other breeding habitats, and contributed to a change in regional distribution since it primarily occurred in a single region. The mechanism for such an effect is not clear, but could represent the local availability of foodstuffs in the landscape rather than something specific to triticale crops. While variation in trends among habitats clearly occurred, they could not easily be ascribed to source-sink dynamics, ecological traps, habitat selection or other detailed ecological mechanisms. Nonetheless, such exchanges provide valuable information to guide management of dynamic systems. PMID:24101977
NASA Astrophysics Data System (ADS)
Gahlot, S.; Lin, T. S.; Jain, A. K.; Baidya Roy, S.; Sehgal, V. K.; Dhakar, R.
2017-12-01
With changing environmental conditions, such as climate and elevated atmospheric CO2 concentrations, questions about food security can be answered by modeling crops based on our understanding of the dynamic crop growth processes and interactions between the crops and their environment in the form of carbon, water and energy fluxes. These interactions and their effect on cropland ecosystems are non-linear because of the feedback mechanisms. Hence, process-based modelling approach can be used to conduct numerical experiments to derive insights into these processes and interactive feedbacks. In this study we have implemented dynamic crop growth processes for wheat into a data-modeling framework, Integrated Science Assessment Model (ISAM), to estimate the impacts of different factors like CO2 fertilization, irrigation, nitrogen limitation and climate change on wheat in India. In specific, we have implemented wheat-specific phenology, C3 photosynthesis mechanism and phenology-specific carbon allocation schemes for assimilated carbon to leaf, stem, root and grain pools. Crop growth limiting stress factors like nutrients, temperature and light have been included. The impact of high temperatures on leaf senescence, anthesis and grain filling has been modeled and found to be causing significant reduction in yield in the recent years. Field data from an experimental wheat site located at the Indian Agricultural Research Institute (IARI), New Delhi, India has been collected for aboveground biomass and leaf area index (LAI) for two growing seasons 2014-15 and 2015-16. This data has been used to study the phenology, growing season length, thermal requirements and growth stages of wheat. Using the field data, the dynamic model for wheat has been evaluated for the site level seasonal variability in leaf area index (LAI) and aboveground biomass. The variations in carbon, water and energy fluxes, plant height and rooting depth have been analyzed on the site level. Model experiments have been performed to calculate the yield for wheat for India for the historical years. In order to identify wheat production regions in India that are prone to one or multiple stresses in years to come, model experiments have been performed based on future climate scenarios RCP 4.5 and 8.5.
Jakovac, Catarina Conte; Dutrieux, Loïc Paul; Siti, Latifah; Peña-Claros, Marielos; Bongers, Frans
2017-01-01
Shifting cultivation is the main land-use system transforming landscapes in riverine Amazonia. Increased concentration of the human population around villages and increasing market integration during the last decades may be causing agricultural intensification. Studies have shown that agricultural intensification, i.e. higher number of swidden-fallow cycles and shorter fallow periods, reduces crop productivity of swiddens and the regrowth capacity of fallows, undermining the resilience of the shifting cultivation system as a whole. We investigated the temporal and spatial dynamics of shifting cultivation in Brazilian Amazonia to test the hypotheses that (i) agriculture has become more intensive over time, and (ii) patterns of land-use intensity are related to land accessibility and human population density. We applied a breakpoint-detection algorithm to Landsat time-series spanning three decades (1984-2015) and retrieved the temporal dynamics of shifting cultivation fields, which go through alternating phases of crop production (swidden) and secondary forest regrowth (fallow). We found that fallow-period length has decreased from 6.4 to 5.1 years on average, and that expansion over old-growth forest has slowed down over time. Shorter fallow periods and higher frequency of slash and burn cycles are practiced closer to residences and around larger villages. Our results indicate that shifting cultivation in riverine Amazonia has gone through a process of agricultural intensification in the past three decades. The resulting landscape is predominantly covered by young secondary forests (≤ 12 yrs old), and 20% of it have gone through intensive use. Reversing this trend and avoiding the negative consequences of agricultural intensification requires land use planning that accounts for the constraints of land use in riverine areas.
Dutrieux, Loïc Paul; Siti, Latifah; Peña-Claros, Marielos; Bongers, Frans
2017-01-01
Shifting cultivation is the main land-use system transforming landscapes in riverine Amazonia. Increased concentration of the human population around villages and increasing market integration during the last decades may be causing agricultural intensification. Studies have shown that agricultural intensification, i.e. higher number of swidden-fallow cycles and shorter fallow periods, reduces crop productivity of swiddens and the regrowth capacity of fallows, undermining the resilience of the shifting cultivation system as a whole. We investigated the temporal and spatial dynamics of shifting cultivation in Brazilian Amazonia to test the hypotheses that (i) agriculture has become more intensive over time, and (ii) patterns of land-use intensity are related to land accessibility and human population density. We applied a breakpoint-detection algorithm to Landsat time-series spanning three decades (1984–2015) and retrieved the temporal dynamics of shifting cultivation fields, which go through alternating phases of crop production (swidden) and secondary forest regrowth (fallow). We found that fallow-period length has decreased from 6.4 to 5.1 years on average, and that expansion over old-growth forest has slowed down over time. Shorter fallow periods and higher frequency of slash and burn cycles are practiced closer to residences and around larger villages. Our results indicate that shifting cultivation in riverine Amazonia has gone through a process of agricultural intensification in the past three decades. The resulting landscape is predominantly covered by young secondary forests (≤ 12 yrs old), and 20% of it have gone through intensive use. Reversing this trend and avoiding the negative consequences of agricultural intensification requires land use planning that accounts for the constraints of land use in riverine areas. PMID:28727828
Quantitative attribution of major driving forces on soil organic carbon dynamics
Wu, Yiping; Liu, Shuguang; Tan, Zhengxi
2015-01-01
Soil organic carbon (SOC) storage plays a major role in the global carbon cycle and is affected by many factors including land use/management changes (e.g., biofuel production-oriented changes). However, the contributions of various factors to SOC changes are not well understood and quantified. This study was designed to investigate the impacts of changing farming practices, initial SOC levels, and biological enhancement of grain production on SOC dynamics and to attribute the relative contributions of major driving forces (CO2 enrichment and farming practices) using a fractional factorial modeling design. The case study at a crop site in Iowa in the United States demonstrated that the traditional corn-soybean (CS) rotation could still accumulate SOC over this century (from 4.2 to 6.8 kg C/m2) under the current condition; whereas the continuous-corn (CC) system might have a higher SOC sequestration potential than CS. In either case, however, residue removal could reduce the sink potential substantially. Long-term simulation results also suggested that the equilibrium SOC level may vary greatly (∼5.7 to ∼11 kg C/m2) depending on cropping systems and management practices, and projected growth enhancement could make the magnitudes higher (∼7.8 to ∼13 kg C/m2). Importantly, the factorial design analysis indicated that residue management had the most significant impact (contributing 49.4%) on SOC changes, followed by CO2 Enrichment (37%), Tillage (6.2%), the combination of CO2Enrichment-Residue removal (5.8%), and Fertilization (1.6%). In brief, this study is valuable for understanding the major forces driving SOC dynamics of agroecosystems and informative for decision-makers when seeking the enhancement of SOC sequestration potential and sustainability of biofuel production, especially in the Corn Belt region of the United States.
Mobile Phenotyping System Using an Aeromotively Stabilized Cable-Driven Robot
NASA Astrophysics Data System (ADS)
Newman, M. B.; Zygielbaum, A. I.
2017-12-01
Agricultural researchers are constantly attempting to generate superior agricultural crops. Whether this means creating crops with greater yield, crops that are more resilient to disease, or crops that can tolerate harsh environments with fewer failures, test plots of these experimental crops must be studied in real-world environments with minimal invasion to determine how they will perform in full-scale agricultural settings. To monitor these crops without interfering with their natural growth, a noninvasive sensor system has been implemented. This system, instituted by the College of Agricultural Sciences and Natural Resources at the University of Nebraska - Lincoln (UNL), uses a system of poles, cables, and winches to support and maneuver a sensor platform above the crops at an outdoor phenotyping site. In this work, we improve upon the UNL outdoor phenotyping system presenting the concept design for a mobile, cable-driven phenotyping system as opposed to a permanent phenotyping facility. One major challenge in large-scale, cable-driven robots is stability of the end-effector. As a result, this mobile system seeks to use a novel method of end-effector stabilization using an onboard rotor drive system, herein referred to as the Instrument Platform Aeromotive Stabilization System (IPASS). A prototype system is developed and analyzed to determine the viability of IPASS.
Diversifying crop rotations with pulses enhances system productivity
Gan, Yantai; Hamel, Chantal; O’Donovan, John T.; Cutforth, Herb; Zentner, Robert P.; Campbell, Con A.; Niu, Yining; Poppy, Lee
2015-01-01
Agriculture in rainfed dry areas is often challenged by inadequate water and nutrient supplies. Summerfallowing has been used to conserve rainwater and promote the release of nitrogen via the N mineralization of soil organic matter. However, summerfallowing leaves land without any crops planted for one entire growing season, creating lost production opportunity. Additionally, summerfallowing has serious environmental consequences. It is unknown whether alternative systems can be developed to retain the beneficial features of summerfallowing with little or no environmental impact. Here, we show that diversifying cropping systems with pulse crops can enhance soil water conservation, improve soil N availability, and increase system productivity. A 3-yr cropping sequence study, repeated for five cycles in Saskatchewan from 2005 to 2011, shows that both pulse- and summerfallow-based systems enhances soil N availability, but the pulse system employs biological fixation of atmospheric N2, whereas the summerfallow-system relies on ‘mining’ soil N with depleting soil organic matter. In a 3-yr cropping cycle, the pulse system increased total grain production by 35.5%, improved protein yield by 50.9%, and enhanced fertilizer-N use efficiency by 33.0% over the summerfallow system. Diversifying cropping systems with pulses can serve as an effective alternative to summerfallowing in rainfed dry areas. PMID:26424172
Long-term Agroecosystem Research in the Northern Great Plains.
NASA Astrophysics Data System (ADS)
Schmer, M.; Sanderson, M.; Liebig, M. A.; Wienhold, B.; Awada, T.; Papiernik, S.; Osborne, S.; Kemp, W.; Okalebo, J. A.; Riedall, W.
2015-12-01
The Northern Great Plains is the bread basket of the United States, accounting for a substantial portion of U.S. agricultural production. This region faces critical challenges regarding balancing food needs, resource conservation (e.g Ogallala aquifer), environmental concerns, and rural economy development. Developing transformative, multifunctional systems will require equally imaginative and efficient tools to help farmers manage complex agroecosystems in a rapidly changing climate. The Northern Plains long-term agroecosystem research (LTAR) site at Mandan, ND and the Platte River High Plains LTAR (ARS/University of Nebraska-Lincoln) at Lincoln, NE in collaboration with USDA-ARS research units in Brookings, SD and Fargo, ND are collaborating to address the grand challenge of providing and sustaining multiple service provisions from Northern Great Plains agroecosystems. We propose to attain these goals through sustainable intensification based on the adoption of conservation agriculture principles including reduced soil disturbance, livestock integration, and greater complexity and diversity in the cropping system. Here, we summarize new concepts these locations have pioneered in dynamic cropping systems, resource use efficiency, and agricultural management technologies. As part of the LTAR network, we will conduct long-term cross-site research to design and assess new agricultural practices and systems aimed at improving our understanding of decision making processes and outcomes across an array of agricultural systems.
Impact of rapeseed cropping on the soil carbon balance
NASA Astrophysics Data System (ADS)
Moffat, Antje Maria; Herbst, Mathias; Huth, Vytas; Andres, Monique; Augustin, Jürgen
2015-04-01
Winter oilseed rape is the dominant biofuel crop in the young moraine landscape in Northern Germany. Since the cultivation of biofuel crops requires sustainability compared to fossil fuels by law, detailed knowledge about their green house gas (GHG) balance is necessary. The soil carbon balance is one of the key contributors to the total GHG balance and also very important for the assessment of soil fertility. However, the knowledge about the impact of different management practices on the soil carbon balance is very limited up to now. Therefore, we investigated the carbon fluxes of winter oilseed rape at field plots near Dedelow/Uckermark in NE Germany with different treatments of fertilization (mineral versus organic) and tillage (no-till and mulch-till versus ploughing). The dynamics of the carbon fluxes are mainly driven by the current climatic conditions but the overall response depends strongly on the ecosystem state (with its physiological and microbiological properties) which is affected by management. To get the full carbon flux dynamics but also the impact of the different management practices, two different approaches were used: The eddy covariance technique to get continuous fluxes throughout the year and the manual chamber technique to detect flux differences between specific management practices. The manual chamber measurements were conducted four-weekly as all-day campaigns using a flow-through non-steady-state closed chamber system. The fluxes in-between campaigns were gap-filled based on functional relationships with soil and air temperature (for the ecosystem respiration) and photosynthetic active radiation (for the gross primary production). All results presented refer to the cropping season 2012-2013. The combination of the two measurement techniques allows the evaluation of chamber fluxes including an independent estimate of the error on the overall balances. Despite the considerable errors, there are significant differences in the soil carbon balance between the tillage and fertilization treatments - ranging from net losses to net gains in the soil carbon stock.
Basso, Bruno; Giola, Pietro; Dumont, Benjamin; Migliorati, Massimiliano De Antoni; Cammarano, Davide; Pruneddu, Giovanni; Giunta, Francesco
2016-01-01
Future climatic changes may have profound impacts on cropping systems and affect the agronomic and environmental sustainability of current N management practices. The objectives of this work were to i) evaluate the ability of the SALUS crop model to reproduce experimental crop yield and soil nitrate dynamics results under different N fertilizer treatments in a farmer’s field, ii) use the SALUS model to estimate the impacts of different N fertilizer treatments on NO3- leaching under future climate scenarios generated by twenty nine different global circulation models, and iii) identify the management system that best minimizes NO3- leaching and maximizes yield under projected future climate conditions. A field experiment (maize-triticale rotation) was conducted in a nitrate vulnerable zone on the west coast of Sardinia, Italy to evaluate N management strategies that include urea fertilization (NMIN), conventional fertilization with dairy slurry and urea (CONV), and no fertilization (N0). An ensemble of 29 global circulation models (GCM) was used to simulate different climate scenarios for two Representative Circulation Pathways (RCP6.0 and RCP8.5) and evaluate potential nitrate leaching and biomass production in this region over the next 50 years. Data collected from two growing seasons showed that the SALUS model adequately simulated both nitrate leaching and crop yield, with a relative error that ranged between 0.4% and 13%. Nitrate losses under RCP8.5 were lower than under RCP6.0 only for NMIN. Accordingly, levels of plant N uptake, N use efficiency and biomass production were higher under RCP8.5 than RCP6.0. Simulations under both RCP scenarios indicated that the NMIN treatment demonstrated both the highest biomass production and NO3- losses. The newly proposed best management practice (BMP), developed from crop N uptake data, was identified as the optimal N fertilizer management practice since it minimized NO3- leaching and maximized biomass production over the long term. PMID:26784113
Impacts of Agricultural Decision Making and Adaptive Management on Food Security in Africa
NASA Astrophysics Data System (ADS)
Caylor, K. K.; Evans, T. P.; Estes, L. D.; Sheffield, J.; Plale, B. A.; Attari, S.
2014-12-01
Despite massive investments in food aid, agricultural extension, and seed/fertilizer subsidies, nearly 1 billion people in the developing world are food insecure and vulnerable to climate variability. Sub-Saharan Africa is most vulnerable, as approximately 25% of its people are undernourished (FAO/FAOSTAT 2013) and 96% of its cropland is rainfed (FAO 2002). The ability of subsistence farmers to respond to changes in water availability involves both inter-and intra-seasonal adaptation. Adaptive capacity diminishes over the season as decisions are made, resources are used, and the set of possible futures becomes restricted. Assessing the intra-seasonal adaptive capacity of smallholders requires integrating physical models of hydrological and agricultural dynamics with farmer decision-making at fine temporal (e.g. weekly) and spatial (e.g. crop field) scales. However, there is an intrinsic challenge to modeling the dynamics of these sociohydrologic systems, because important and uncharacterized spatial and temporal scale mismatches exist between the level at which the water resource is best understood and the level at which human dynamics are more predictable. For example, the skill of current process-based land surface models is primarily confined to short-term (daily to weekly), national- to regional-scale assessments, and reliable agricultural yield estimates and forecasts for small-scale farming systems remain elusive. In contrast, process-based social science modeling has focused on agent-based approaches that generate fine-scale (individual to community) dynamics over rather coarse time scales (yearly to decadal). A major obstacle to addressing this mismatch is the fundamental fact that the highest skill domain of one framework is essentially unpredictable in the other. We present a coupled sociohydrological observation framework designed to addressing this gap, and demonstrate its utility to understand relationships between climate variability, decision making, and crop production for subsistence agriculturalists in Kenya and Zambia.
Wheat yield and yield stability of eight dryland crop rotations
USDA-ARS?s Scientific Manuscript database
The winter wheat (Triticum aestivum L.)-fallow (WF) dryland production system employed in the Central Great Plains has evolved in the past 40 years to include a diversity of other crops, with a reduction in fallow frequency. Wheat remains the base crop for essentially all cropping systems. Decisions...
Intensifying a semi-arid dryland crop rotation by replacing fallow with pea
USDA-ARS?s Scientific Manuscript database
Increasing dryland cropping system intensity in the semi-arid central Great Plains by reducing frequency of fallow can add diversity to cropping systems and decrease erosion potential. However elimination of the periodic fallow phase has been shown to reduce yields of subsequent crops in this region...
Diverse rotations and poultry litter improves soybean yield
USDA-ARS?s Scientific Manuscript database
Continuous cropping systems without rotations or cover crops are perceived as unsustainable for long-term yield and soil health. Continuous systems, defined as continually producing a crop on the same parcel of land for more than three years, is thought to reduce yields. Given that crop rotations a...
Deriving crop calendar using NDVI time-series
NASA Astrophysics Data System (ADS)
Patel, J. H.; Oza, M. P.
2014-11-01
Agricultural intensification is defined in terms as cropping intensity, which is the numbers of crops (single, double and triple) per year in a unit cropland area. Information about crop calendar (i.e. number of crops in a parcel of land and their planting & harvesting dates and date of peak vegetative stage) is essential for proper management of agriculture. Remote sensing sensors provide a regular, consistent and reliable measurement of vegetation response at various growth stages of crop. Therefore it is ideally suited for monitoring purpose. The spectral response of vegetation, as measured by the Normalized Difference Vegetation Index (NDVI) and its profiles, can provide a new dimension for describing vegetation growth cycle. The analysis based on values of NDVI at regular time interval provides useful information about various crop growth stages and performance of crop in a season. However, the NDVI data series has considerable amount of local fluctuation in time domain and needs to be smoothed so that dominant seasonal behavior is enhanced. Based on temporal analysis of smoothed NDVI series, it is possible to extract number of crop cycles per year and their crop calendar. In the present study, a methodology is developed to extract key elements of crop growth cycle (i.e. number of crops per year and their planting - peak - harvesting dates). This is illustrated by analysing MODIS-NDVI data series of one agricultural year (from June 2012 to May 2013) over Gujarat. Such an analysis is very useful for analysing dynamics of kharif and rabi crops.
NASA Astrophysics Data System (ADS)
Dhungel, S.; Barber, M. E.
2016-12-01
The objectives of this paper are to use an automated satellite-based remote sensing evapotranspiration (ET) model to assist in parameterization of a cropping system model (CropSyst) and to examine the variability of consumptive water use of various crops across the watershed. The remote sensing model is a modified version of the Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC™) energy balance model. We present the application of an automated python-based implementation of METRIC to estimate ET as consumptive water use for agricultural areas in three watersheds in Eastern Washington - Walla Walla, Lower Yakima and Okanogan. We used these ET maps with USDA crop data to identify the variability of crop growth and water use for the major crops in these three watersheds. Some crops, such as grapes and alfalfa, showed high variability in water use in the watershed while others, such as corn, had comparatively less variability. The results helped us to estimate the range and variability of various crop parameters that are used in CropSyst. The paper also presents a systematic approach to estimate parameters of CropSyst for a crop in a watershed using METRIC results. Our initial application of this approach was used to estimate irrigation application rate for CropSyst for a selected farm in Walla Walla and was validated by comparing crop growth (as Leaf Area Index - LAI) and consumptive water use (ET) from METRIC and CropSyst. This coupling of METRIC with CropSyst will allow for more robust parameters in CropSyst and will enable accurate predictions of changes in irrigation practices and crop rotation, which are a challenge in many cropping system models.
NASA Astrophysics Data System (ADS)
Chen, Bin
2018-04-01
Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.
NASA Technical Reports Server (NTRS)
Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.
1996-01-01
Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.
NASA Astrophysics Data System (ADS)
Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.
Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO_2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainability of a CELSS that will enable management of diverse complex systems on Earth.
Mitchell, C; Sherman, L; Nielsen, S; Nelson, P; Trumbo, P; Hodges, T; Hasegawa, P; Bressan, R; Ladisch, M; Auslander, D
1996-01-01
Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.
Ouyang, Wei; Wei, Xinfeng; Hao, Fanghua
2013-04-15
There are two kinds of land policies, the smallholding land policy (SLP) and the farmland policy (FLP) in China. The farmland nutrient dynamics under the two land policies were analysed with the soil system budget method. The averaged nitrogen (N) input of the SLP and the FLP over sixteen years increased about 23.9% and 33.3%, respectively and the phosphorus (P) input climbed about 39.1% and 42.3%, respectively. The statistical analysis showed that the land policies had significant impacts on N and P input from fertilizer and manure, but did not obviously affect the N input from seeds and biological N fixation. The efficiency percentage of N of the SLP and the FLP climbed about 54.5% and 59.4%, respectively, and the P efficiency improved by 52.7% and 82.6%, respectively. About the nutrient output, the F-test analysis indicated that the land polices had remarkable impacts on N output by crop uptake, ammonia volatilisation, denitrification, leaching and runoff, and P output by uptake, runoff, and leach. The balance showed that the absolute loss of N from land deceased about 43.6% and 46.0%, respectively, in the SLP and the FLP, and P discharge reduced about 34.2% and 75.2%, respectively. The F-test analysis of N and P efficiency and balance of between two polices both indicated that the FLP had significant impact on nutrient dynamic. With the Mitscherlich model, the correlations between nutrient input and crop uptake, usage efficiency and loss were analysed and showed that was a threshold value for the optimal nutrient input with the highest efficiency rate. For the optimal nutrient efficiency, the space for extra P addition was bigger than the N input. The FLP have more advantage than the SLP on the crop yield, nutrient efficiency and environmental discharge. Copyright © 2013 Elsevier B.V. All rights reserved.
Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.
Hammer, Graeme L; van Oosterom, Erik; McLean, Greg; Chapman, Scott C; Broad, Ian; Harland, Peter; Muchow, Russell C
2010-05-01
Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on diverse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.
Using dual-purpose crops in sheep-grazing systems.
Dove, Hugh; Kirkegaard, John
2014-05-01
The utilisation of dual-purpose crops, especially wheat and canola grown for forage and grain production in sheep-grazing systems, is reviewed. When sown early and grazed in winter before stem elongation, later-maturing wheat and canola crops can be grazed with little impact on grain yield. Recent research has sought to develop crop- and grazing-management strategies for dual-purpose crops. Aspects examined have been grazing effects on crop growth, recovery and yield development along with an understanding of the grazing value of the crop fodder, its implications for animal nutrition and grazing management to maximise live-weight gain. By alleviating the winter 'feed gap', the increase in winter stocking rate afforded by grazing crops allows crop and livestock production to be increased simultaneously on the same farm. Integration of dual-purpose wheat with canola on mixed farms provides further systems advantages related to widened operational windows, weed and disease control and risk management. Dual-purpose crops are an innovation that has potential to assist in addressing the global food-security challenge. © 2013 Society of Chemical Industry.
NASA Astrophysics Data System (ADS)
Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.
2014-12-01
The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.
NASA Astrophysics Data System (ADS)
Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.
2014-07-01
The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.
NASA Astrophysics Data System (ADS)
Bodner, G.; Loiskandl, W.; Kaul, H.-P.
2009-04-01
Soil structure is a dynamic property subject to numerous natural and human influences. It is recognized as fundamental for sustainable functioning of soil. Therefore knowledge of management impacts on the sensitive structural states of soil is decisive in order to avoid soil degradation. The stabilization of the soil's (macro)pore system and eventually the improvement of its infiltrability are essential to avoid runoff and soil erosion, particularly in view of an increasing probability of intense rainfall events. However structure-related soil properties generally have a high natural spatiotemporal variability that interacts with the potential influence of agricultural land use. This complicates a clear determination of management vs. environmental effects and requires adequate measurement methods, allowing a sufficient spatiotemporal resolution to estimate the impact of the targeted management factors within the natural dynamics of soil structure. A common method to assess structure-related soil hydraulic properties is tension infiltrometry. A major advantage of tension infiltrometer measurements is that no or only minimum soil disturbance is necessary and several structure-controlled water transmission properties can readily be derived. The method is more time- and cost-efficient compared to laboratory measurements of soil hydraulic properties, thus enabling more replications. Furthermore in situ measurements of hydraulic properties generally allow a more accurate reproduction of field soil water dynamics. The present study analyses the impact of two common agricultural management options on structure related hydraulic properties based on tension infiltrometer measurements. Its focus is the identification of the role of management within the natural spatiotemporal variability, particularly in respect to seasonal temporal dynamics. Two management approaches are analysed, (i) cover cropping as a "plant-based" agro-environmental measure, and (ii) tillage with different intensities including conventional tillage with a mouldboard plough, reduced tillage with a chisel plough and no-tillage. The results showed that the plant-based management measure of cover cropping had only minor influence on near-saturated hydraulic conductivity (kh) and flow weighted mean pore radius (λm). Substantial over-winter changes were found with a significant increase in kh and a reduction in the pore radius. A spatial trend in soil texture along the cover cropped slope resulted in a higher kh at lower pressure heads at the summit with higher fractions of coarse particles, while kh tended to be highest at the toeslope towards saturation. Cover crop management accounted for a maximum of 9.7% of the total variability in kh, with a decreasing impact towards the unsaturated range. A substantial difference to bare soil in the cover cropped treatments could be identified in relation to a stabilization of macro-pores over winter. The different tillage treatments had a substantial impact on near-saturated kh and pore radius. Although conventional tillage showed the highest values in kh and λm, settling of the soil after the ploughing event tended to reduce differences over time compared to the other tillage methods. The long-term no-tillage (10 years) however had the lowest values of kh at all measurement dates. The high contents of silt and fine sand probably resulted in soil densification that was not counterbalanced sufficiently by biological structure forming agents. The study could show that soil structure related hydraulic properties are subject to a substantial seasonal variability. A comprehensive assessment of agricultural measures such as tillage or cover cropping requires an estimate of these temporal dynamics and their interaction with the management strategies. Particularly for plant-based management measures such as cover cropping, which represent a less intense intervention in the structural states of the soil compared to tillage, this was evident, as the main mechanism revealed for this measure was structure stabilization over time. While spatial variability is mostly controlled in designed experiments, the role of temporal variability is often underestimated. From our study we concluded that (i) a proper understanding of processes involved in management effects on soil structure must take into consideration the dynamic nature of the respective soil properties, (ii) experimental planning for studies regarding management impacts on soil structure should allow an estimation of temporal variability, and (iii) for this purpose tension infiltrometry provides an efficient measurement tool to assess structure related soil hydraulic properties.
Spatial dynamics and control of a crop pathogen with mixed-mode transmission.
McQuaid, Christopher Finn; van den Bosch, Frank; Szyniszewska, Anna; Alicai, Titus; Pariyo, Anthony; Chikoti, Patrick Chiza; Gilligan, Christopher Aidan
2017-07-01
Trade or sharing that moves infectious planting material between farms can, for vertically-transmitted plant diseases, act as a significant force for dispersal of pathogens, particularly where the extent of material movement may be greater than that of infected vectors or inoculum. The network over which trade occurs will then effect dispersal, and is important to consider when attempting to control the disease. We consider the difference that planting material exchange can make to successful control of cassava brown streak disease, an important viral disease affecting one of Africa's staple crops. We use a mathematical model of smallholders' fields to determine the effect of informal trade on both the spread of the pathogen and its control using clean-seed systems, determining aspects that could limit the damage caused by the disease. In particular, we identify the potentially detrimental effects of markets, and the benefits of a community-based approach to disease control.
Tanou, Georgia; Ziogas, Vasileios; Molassiotis, Athanassios
2017-01-01
Despite the fact that the usage of foliar nutrients has long history, many aspects of fertilization through leaves are still unknown. Herein, we review the current knowledge regarding the canopy fertilization putting special emphasis on Fe nutrition and briefly provide insights into the nanofertilizer technology of the foliar feeding of fruit crops. In addition, this paper discusses the main aspects of the foliar application of biostimulants regarding crucial factors of fruit cropping systems, such as fruit yield/size, tolerance to environmental stresses, and nutrient availability. Also, we specifically discuss the role of hydrogen peroxide (H2O2) and nitric oxide (NO) as priming molecules and their possible cross-talk with biostimulants in fruit tree physiology. Finally, a view of the key issues for future fundamental and applied research in the topic is put forward. PMID:28203243
Greenhouse gas emissions from traditional and biofuels cropping systems
USDA-ARS?s Scientific Manuscript database
Cropping systems can have a tremendous effect on the greenhouse gas emissions from soils. The objectives of this study were to compare greenhouse gas emissions from traditional (continuous corn or corn/soybean rotation) and biomass (miscanthus, sorghum, switchgrass) cropping systems. Biomass croppin...
ERIC Educational Resources Information Center
Miyake, Saori; Renouf, Marguerite; Peterson, Ann; McAlpine, Clive; Smith, Carl
2012-01-01
Recent energy and climate policies, particularly in the developed world, have increased demand for bioenergy as an alternative, which has led to both direct and indirect land-use changes and an array of environmental and socio-economic concerns. A comprehensive understanding of the land-use dynamics of bioenergy crop production is essential for…
2016-01-01
Research on perennial staple crops has increased in the past ten years due to their potential to improve ecosystem services in agricultural systems. However, multiple past breeding efforts as well as research on traditional ratoon systems mean there is already a broad body of literature on perennial crops. In this review, we compare the development of research on perennial staple crops, including wheat, rice, rye, sorghum, and pigeon pea. We utilized the advanced search capabilities of Web of Science, Scopus, ScienceDirect, and Agricola to gather a library of 914 articles published from 1930 to the present. We analyzed the metadata in the entire library and in collections of literature on each crop to understand trends in research and publishing. In addition, we applied topic modeling to the article abstracts, a type of text analysis that identifies frequently co-occurring terms and latent topics. We found: 1.) Research on perennials is increasing overall, but individual crops have each seen periods of heightened interest and research activity; 2.) Specialist journals play an important role in supporting early research efforts. Research often begins within communities of specialists or breeders for the individual crop before transitioning to a more general scientific audience; 3.) Existing perennial agricultural systems and their domesticated crop material, such as ratoon rice systems, can provide a useful foundation for breeding efforts, accelerating the development of truly perennial crops and farming systems; 4.) Primary research is lacking for crops that are produced on a smaller scale globally, such as pigeon pea and sorghum, and on the ecosystem service benefits of perennial agricultural systems. PMID:27213283
NASA Astrophysics Data System (ADS)
Islami, Titiek; Wisnubroto, Erwin; Utomo, Wani
2016-04-01
Three years field experiments were conducted to study the effect of chemical and mechanical weed control on soil quality and erosion under cassava cropping system. The experiment were conducted at University Brawijaya field experimental station, Jatikerto, Malang, Indonesia. The experiments were carried out from 2011 - 2014. The treatments consist of three cropping system (cassava mono culture; cassava + maize intercropping and cassava + peanut intercropping), and two weed control method (chemical and mechanical methods). The experimental result showed that the yield of cassava first year and second year did not influenced by weed control method and cropping system. However, the third year yield of cassava was influence by weed control method and cropping system. The cassava yield planted in cassava + maize intercropping system with chemical weed control methods was only 24 t/ha, which lower compared to other treatments, even with that of the same cropping system used mechanical weed control. The highest cassava yield in third year was obtained by cassava + peanuts cropping system with mechanical weed control method. After three years experiment, the soil of cassava monoculture system with chemical weed control method possessed the lowest soil organic matter, and soil aggregate stability. During three years of cropping soil erosion in chemical weed control method, especially on cassava monoculture, was higher compared to mechanical weed control method. The soil loss from chemical control method were 40 t/ha, 44 t/ha and 54 t/ha for the first, second and third year crop. The soil loss from mechanical weed control method for the same years was: 36 t/ha, 36 t/ha and 38 t/ha. Key words: herbicide, intercropping, soil organic matter, aggregate stability.
Naab, Jesse B.; Mahama, George Y.; Yahaya, Iddrisu; Prasad, P. V. V.
2017-01-01
Conservation agriculture (CA) practices are being widely promoted in many areas in sub-Saharan Africa to recuperate degraded soils and improve ecosystem services. This study examined the effects of three tillage practices [conventional moldboard plowing (CT), hand hoeing (MT) and no-tillage (NT)], and three cropping systems (continuous maize, soybean–maize annual rotation, and soybean/maize intercropping) on soil quality, crop productivity, and profitability in researcher and farmer managed on-farm trials from 2010 to 2013 in northwestern Ghana. In the researcher managed mother trial, the CA practices of NT, residue retention and crop rotation/intercropping maintained higher soil organic carbon, and total soil N compared to conventional tillage practices after 4 years. Soil bulk density was higher under NT than under CT soils in the researcher managed mother trails or farmers managed baby trials after 4 years. In the researcher managed mother trial, there was no significant difference between tillage systems or cropping systems in maize or soybean yields in the first three seasons. In the fourth season, crop rotation had the greatest impact on maize yields with CT maize following soybean increasing yields by 41 and 49% compared to MT and NT maize, respectively. In the farmers’ managed trials, maize yield ranged from 520 to 2700 kg ha-1 and 300 to 2000 kg ha-1 for CT and NT, respectively, reflecting differences in experience of farmers with NT. Averaged across farmers, CT cropping systems increased maize and soybean yield ranging from 23 to 39% compared with NT cropping systems. Partial budget analysis showed that the cost of producing maize or soybean is 20–29% cheaper with NT systems and gives higher returns to labor compared to CT practice. Benefit-to-cost ratios also show that NT cropping systems are more profitable than CT systems. We conclude that with time, implementation of CA practices involving NT, crop rotation, intercropping of maize and soybean along with crop residue retention presents a win–win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. The biggest challenge, however, remains with producing enough biomass and retaining same on the field. PMID:28680427
Reconciling pesticide reduction with economic and environmental sustainability in arable farming.
Lechenet, Martin; Bretagnolle, Vincent; Bockstaller, Christian; Boissinot, François; Petit, Marie-Sophie; Petit, Sandrine; Munier-Jolain, Nicolas M
2014-01-01
Reducing pesticide use is one of the high-priority targets in the quest for a sustainable agriculture. Until now, most studies dealing with pesticide use reduction have compared a limited number of experimental prototypes. Here we assessed the sustainability of 48 arable cropping systems from two major agricultural regions of France, including conventional, integrated and organic systems, with a wide range of pesticide use intensities and management (crop rotation, soil tillage, cultivars, fertilization, etc.). We assessed cropping system sustainability using a set of economic, environmental and social indicators. We failed to detect any positive correlation between pesticide use intensity and both productivity (when organic farms were excluded) and profitability. In addition, there was no relationship between pesticide use and workload. We found that crop rotation diversity was higher in cropping systems with low pesticide use, which would support the important role of crop rotation diversity in integrated and organic strategies. In comparison to conventional systems, integrated strategies showed a decrease in the use of both pesticides and nitrogen fertilizers, they consumed less energy and were frequently more energy efficient. Integrated systems therefore appeared as the best compromise in sustainability trade-offs. Our results could be used to re-design current cropping systems, by promoting diversified crop rotations and the combination of a wide range of available techniques contributing to pest management.
Reconciling Pesticide Reduction with Economic and Environmental Sustainability in Arable Farming
Lechenet, Martin; Bretagnolle, Vincent; Bockstaller, Christian; Boissinot, François; Petit, Marie-Sophie; Petit, Sandrine; Munier-Jolain, Nicolas M.
2014-01-01
Reducing pesticide use is one of the high-priority targets in the quest for a sustainable agriculture. Until now, most studies dealing with pesticide use reduction have compared a limited number of experimental prototypes. Here we assessed the sustainability of 48 arable cropping systems from two major agricultural regions of France, including conventional, integrated and organic systems, with a wide range of pesticide use intensities and management (crop rotation, soil tillage, cultivars, fertilization, etc.). We assessed cropping system sustainability using a set of economic, environmental and social indicators. We failed to detect any positive correlation between pesticide use intensity and both productivity (when organic farms were excluded) and profitability. In addition, there was no relationship between pesticide use and workload. We found that crop rotation diversity was higher in cropping systems with low pesticide use, which would support the important role of crop rotation diversity in integrated and organic strategies. In comparison to conventional systems, integrated strategies showed a decrease in the use of both pesticides and nitrogen fertilizers, they consumed less energy and were frequently more energy efficient. Integrated systems therefore appeared as the best compromise in sustainability trade-offs. Our results could be used to re-design current cropping systems, by promoting diversified crop rotations and the combination of a wide range of available techniques contributing to pest management. PMID:24887494
USDA-ARS?s Scientific Manuscript database
Diversification of farm enterprises is important to maintain sustainable production systems. Systems that integrate crops and livestock may prove beneficial to each enterprise. Our objectives were to determine the effects of annual crops grazed in the fall and early-winter period on cow and calf gro...
USDA-ARS?s Scientific Manuscript database
Sustainable grain crop production on vulnerable claypan soils requires improved knowledge of long-term impacts of conservation cropping systems (CS) with reduced inputs. Therefore, effects of CS and landscape positions (LP) on corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum...
Characteristics of nitrogen balance in open-air and greenhouse vegetable cropping systems of China.
Ti, Chaopu; Luo, Yongxia; Yan, Xiaoyuan
2015-12-01
Nitrogen (N) loss from vegetable cropping systems has become a significant environmental issue in China. In this study, estimation of N balances in both open-air and greenhouse vegetable cropping systems in China was established. Results showed that the total N input in open-air and greenhouse vegetable cropping systems in 2010 was 5.44 and 2.60 Tg, respectively. Chemical fertilizer N input in the two cropping systems was 201 kg N ha(-1) per season (open-air) and 478 kg N ha(-1) per season (greenhouse). The N use efficiency (NUE) was 25.9 ± 13.3 and 19.7 ± 9.4% for open-air and greenhouse vegetable cropping systems, respectively, significantly lower than that of maize, wheat, and rice. Approximately 30.6% of total N input was accumulated in soils and 0.8% was lost by ammonia volatilization in greenhouse vegetable system, while N accumulation and ammonia volatilization accounted for 19.1 and 11.1%, respectively, of total N input in open-air vegetable systems.
The Role of Crop Systems Simulation in Agriculture and Environment
USDA-ARS?s Scientific Manuscript database
Over the past 30 to 40 years, simulation of crop systems has advanced from a neophyte science with inadequate computing power into a robust and increasingly accepted science supported by improved software, languages, development tools, and computer capabilities. Crop system simulators contain mathe...
NASA Astrophysics Data System (ADS)
Zhang, Jie; Beusen, Arthur H. W.; Van Apeldoorn, Dirk F.; Mogollón, José M.; Yu, Chaoqing; Bouwman, Alexander F.
2017-04-01
Phosphorus (P) plays a vital role in global crop production and food security. In this study, we investigate the changes in soil P pool inventories calibrated from historical countrywide crop P uptake, using a 0.5-by-0.5° spatially explicit model for the period 1900-2010. Globally, the total P pool per hectare increased rapidly between 1900 and 2010 in soils of Europe (+31 %), South America (+2 %), North America (+15 %), Asia (+17 %), and Oceania (+17 %), while it has been stable in Africa. Simulated crop P uptake is influenced by both soil properties (available P and the P retention potential) and crop characteristics (maximum uptake). Until 1950, P fertilizer application had a negligible influence on crop uptake, but recently it has become a driving factor for food production in industrialized countries and a number of transition countries like Brazil, Korea, and China. This comprehensive and spatially explicit model can be used to assess how long surplus P fertilization is needed or how long depletions of built-up surplus P can continue without affecting crop yield.
Panda, B. B.; Raja, R.; Singh, Teekam; Tripathi, R.; Shahid, M.; Nayak, A. K.
2017-01-01
Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June–September) and land leftovers fallow after rice harvest in the post-rainy season (November–May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November–March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield. PMID:28437487
Lal, B; Gautam, Priyanka; Panda, B B; Raja, R; Singh, Teekam; Tripathi, R; Shahid, M; Nayak, A K
2017-01-01
Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June-September) and land leftovers fallow after rice harvest in the post-rainy season (November-May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November-March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield.
Clarke, Joseph D.; Alexander, Danny C.; Ward, Dennis P.; Ryals, John A.; Mitchell, Matthew W.; Wulff, Jacob E.; Guo, Lining
2013-01-01
Genetically modified (GM) crops currently constitute a significant and growing part of agriculture. An important aspect of GM crop adoption is to demonstrate safety and equivalence with respect to conventional crops. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for GM crop substantial equivalence assessment. To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway. PMID:24170158
Foundational and Translational Research Opportunities to Improve Plant Health
Michelmore, Richard; Coaker, Gitta; Bart, Rebecca; Beattie, Gwyn; Bent, Andrew; Bruce, Toby; Cameron, Duncan; Dangl, Jeff; Dinesh-Kumar, Savithramma; Edwards, Rob; Eves-van den Akker, Sebastian; Gassmann, Walter; Greenberg, Jean; Harrison, Richard; He, Ping; Hanley-Bowdoin, Linda; Harvey, Jagger; Huffaker, Alisa; Hulbert, Scot; Innes, Roger; Jones, Jonathan; Kaloshian, Isgouhi; Kamoun, Sophien; Katagiri, Fumiaki; Leach, Jan; Ma, Wenbo; McDowell, John; Medford, June; Meyers, Blake; Nelson, Rebecca; Oliver, Richard; Qi, Yiping; Saunders, Diane; Shaw, Michael; Smart, Christine; Subudhi, Prasanta; Torrance, Lesley; Tyler, Bret; Valent, Barbara; Walsh, John
2018-01-01
Summary This whitepaper reports the deliberations of a workshop focused on biotic challenges to plant health held in Washington, D.C. in September 2016. Ensuring health of food plants is critical to maintaining the quality and productivity of crops and for sustenance of the rapidly growing human population. There is a close linkage between food security and societal stability; however, global food security is threatened by the vulnerability of our agricultural systems to numerous pests, pathogens, weeds, and environmental stresses. These threats are aggravated by climate change, the globalization of agriculture, and an over-reliance on non-sustainable inputs. New analytical and computational technologies are providing unprecedented resolution at a variety of molecular, cellular, organismal, and population scales for crop plants as well as pathogens, pests, beneficial microbes, and weeds. It is now possible to both characterize useful or deleterious variation as well as precisely manipulate it. Data-driven, informed decisions based on knowledge of the variation of biotic challenges and of natural and synthetic variation in crop plants will enable deployment of durable interventions throughout the world. These should be integral, dynamic components of agricultural strategies for sustainable agriculture. PMID:28398839
NASA Astrophysics Data System (ADS)
Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo
2017-04-01
Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.
NASA Technical Reports Server (NTRS)
Paudel, Krishna P.; Limaye, Ashutosh; Hatch, Upton; Cruise, James; Musleh, Fuad
2005-01-01
We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.
Accessing genetic diversity for crop improvement.
Glaszmann, J C; Kilian, B; Upadhyaya, H D; Varshney, R K
2010-04-01
Vast germplasm collections are accessible but their use for crop improvement is limited-efficiently accessing genetic diversity is still a challenge. Molecular markers have clarified the structure of genetic diversity in a broad range of crops. Recent developments have made whole-genome surveys and gene-targeted surveys possible, shedding light on population dynamics and on the impact of selection during domestication. Thanks to this new precision, germplasm description has gained analytical power for resolving the genetic basis of trait variation and adaptation in crops such as major cereals, chickpea, grapevine, cacao, or banana. The challenge now is to finely characterize all the facets of plant behavior in carefully chosen materials. We suggest broadening the use of 'core reference sets' so as to facilitate material sharing within the scientific community.
The Challenges in the Development of a Long Duration Space Mission Food System
NASA Technical Reports Server (NTRS)
Perchonok, Michele H.; Swango, Beverly; Toerne, Mary E.; Russo, Dane M. (Technical Monitor)
2001-01-01
The Advanced Food System at Johnson Space Center/NASA will be responsible for supplying food to the crew for long duration exploratory missions. These missions require development of both a Transit Food System and of a Planetary Food System. The Transit Food System will consist of pre-packaged food of extended shelf life. It will be supplemented with salad crops that will be consumed fresh. The challenge is to develop a food system with a shelf life of 3 - 5 years that will use minimal power and create minimal waste from the food packaging. The Planetary Food System will allow for food processing of crops grown on the planetary surface due to the presence of some gravitational force. Crops will be processed to final products to provide a nutritious and acceptable diet for the crew. The food system must be flexible due to crop variation, availability, and shelf life. Crew meals, based on thesc: crops, must be nutritious, high quality, safe, and contain variety. The Advanced Food System becomes a fulcrum creating the right connection from crops to crew meals while dealing with issues of integration within a closed self-regenerative system (e.g., safety, waste production, volumes, water usage, etc.).
Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu
2018-01-01
We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.
Using cover crops and cropping systems for nitrogen management
USDA-ARS?s Scientific Manuscript database
The reasons for using cover crops and optimized cropping sequences to manage nitrogen (N) are to maximize economic returns, improve soil quality and productivity, and minimize losses of N that might adversely impact environmental quality. Cover crops and cropping systems’ effects on N management are...
Evaluation of Learning Group Approaches for Fostering Integrated Cropping Systems Management
ERIC Educational Resources Information Center
Blissett, Hana; Simmons, Steve; Jordan, Nicholas; Nelson, Kristen
2004-01-01
Cropping systems management requires integration of multiple forms of knowledge, practice, and learning by farmers, extension educators, and researchers. We evaluated the outcomes of participation in collaborative learning groups organized to address cropping systems and, specifically, challenges of integrated weed management. Groups were…
NASA Astrophysics Data System (ADS)
Kaneko, Daijiro
2015-04-01
Crop-monitoring systems with the unit of carbon-dioxide sequestration for environmental issues related to climate adaptation to global warming have been improved using satellite-based photosynthesis and meteorological conditions. Early management of crop status is desirable for grain production, stockbreeding, and bio-energy providing that the seasonal climate forecasting is sufficiently accurate. Incorrect seasonal forecasting of crop production can damage global social activities if the recognized conditions are unsatisfied. One cause of poor forecasting related to the atmospheric dynamics at the Earth surface, which reflect the energy budget through land surface, especially the oceans and atmosphere. Recognition of the relation between SST anomalies (e.g. ENSO, Atlantic Niño, Indian dipoles, and Ningaloo Niño) and crop production, as expressed precisely by photosynthesis or the sequestrated-carbon rate, is necessary to elucidate the mechanisms related to poor production. Solar radiation, surface air temperature, and water stress all directly affect grain vegetation photosynthesis. All affect stomata opening, which is related to the water balance or definition by the ratio of the Penman potential evaporation and actual transpiration. Regarding stomata, present data and reanalysis data give overestimated values of stomata opening because they are extended from wet models in forests rather than semi-arid regions commonly associated with wheat, maize, and soybean. This study applies a complementary model based on energy conservation for semi-arid zones instead of the conventional Penman-Monteith method. Partitioning of the integrated Net PSN enables precise estimation of crop yields by modifying the semi-closed stomata opening. Partitioning predicts production more accurately using the cropland distribution already classified using satellite data. Seasonal crop forecasting should include near-real-time monitoring using satellite-based process crop models to avoid social difficulties that can derive from uncertain seasonal predictions produced from long-term forecasting. Acknowledgement The author appreciates scientific discussions held with the application team of seasonal prediction at the Japan Agency for Marine-Earth Science and Technology. Key words: crop production, monitoring, forecasting, SST anomaly, remote sensing
NASA Astrophysics Data System (ADS)
Sulis, Mauro; Langensiepen, Matthias; Shrestha, Prabhakar; Schickling, Anke; Simmer, Clemens; Kollet, Stefan
2015-04-01
Vegetation has a significant influence on the partitioning of radiative forcing, the spatial and temporal variability of soil water and soil temperature. Therefore plant physiological properties play a key role in mediating and amplifying interactions and feedback mechanisms in the soil-vegetation-atmosphere continuum. Because of the direct impact on latent heat fluxes, these properties may also influence weather generating processes, such as the evolution of the atmospheric boundary layer (ABL). In land surface models, plant physiological properties are usually obtained from literature synthesis by unifying several plant/crop species in predefined vegetation classes. In this work, crop-specific physiological characteristics, retrieved from detailed field measurements, are included in the bio-physical parameterization of the Community Land Model (CLM), which is a component of the Terrestrial Systems Modeling Platform (TerrSysMP). The measured set of parameters for two typical European mid-latitudinal crops (sugar beet and winter wheat) is validated using eddy covariance measurements (sensible heat and latent heat) over multiple years from three measurement sites located in the North Rhine-Westphalia region, Germany. We found clear improvements of CLM simulations, when using the crop-specific physiological characteristics of the plants instead of the generic crop type when compared to the measurements. In particular, the increase of latent heat fluxes in conjunction with decreased sensible heat fluxes as simulated by the two new crop-specific parameter sets leads to an improved quantification of the diurnal energy partitioning. These findings are cross-validated using estimates of gross primary production extracted from net ecosystem exchange measurements. This independent analysis reveals that the better agreement between observed and simulated latent heat using the plant-specific physiological properties largely stems from an improved simulation of the photosynthesis process owing to a better estimation of the Rubisco enzyme kinematics. Finally, to evaluate the effects of the crop-specific parameterizations on the ABL dynamics, we perform a series of semi-idealized land-atmosphere coupled simulations by hypothesizing three cropland configurations. These numerical experiments reveal different heat and moisture budgets of the ABL that clearly impact the evolution of the boundary layer when using the crop-specific physiological properties.
Kost, Matthew A; Alexander, Helen M; Jason Emry, D; Mercer, Kristin L
2015-06-01
Hybridization produces strong evolutionary forces. In hybrid zones, selection can differentially occur on traits and selection intensities may differ among hybrid generations. Understanding these dynamics in crop-wild hybrid zones can clarify crop-like traits likely to introgress into wild populations and the particular hybrid generations through which introgression proceeds. In a field experiment with four crop-wild hybrid Helianthus annuus (sunflower) cross types, we measured growth and life history traits and performed phenotypic selection analysis on early season traits to ascertain the likelihood, and routes, of crop allele introgression into wild sunflower populations. All cross types overwintered, emerged in the spring, and survived until flowering, indicating no early life history barriers to crop allele introgression. While selection indirectly favored earlier seedling emergence and taller early season seedlings, direct selection only favored greater early season leaf length. Further, there was cross type variation in the intensity of selection operating on leaf length. Thus, introgression of multiple early season crop-like traits, due to direct selection for greater early season leaf length, should not be impeded by any cross type and may proceed at different rates among generations. In sum, alleles underlying early season sunflower crop-like traits are likely to introgress into wild sunflower populations.
Effect of Mixed Systems on Crop Productivity
NASA Astrophysics Data System (ADS)
Senturklu, Songul; Landblom, Douglas; Cihacek, Larry; Brevik, Eric
2017-04-01
The goals of this non-irrigated research has been to determine the effect of mixed systems integration on crop, soil, and beef cattle production in the northern Great Plains region of the United States. Over a 5-year period, growing spring wheat (HRSW-C) continuously year after year was compared to a 5-year crop rotation that included spring wheat (HRSW-R), cover crop (dual crop consisting of winter triticale/hairy vetch seeded in the fall and harvested for hay followed by a 7-species cover crop that was seeded in June after hay harvest), forage corn, field pea/barley, and sunflower. Control 5-year HRSW yield was 2690 kg/ha compared to 2757 kg/ha for HRSW grown in rotation. Available soil nitrogen (N) is often the most important limitation for crop production. Expensive fertilizer inputs were reduced in this study due to the mixed system's complementarity in which the rotation system that included beef cattle grazing sustained N availability and increased nutrient cycling, which had a positive effect on all crops grown in the rotation. Growing HRSW continuously requires less intensive management and in this research was 14.5% less profitable. Whereas, when crop management increased and complementing crops were grown in rotation to produce crops and provide feed for grazing livestock, soil nutrient cycling improved. Increased nutrient cycling increased crop rotation yields and yearling beef cattle steers that grazing annual forages in the rotation gain more body weight than similar steers grazing NGP native range. Results of this long-term research will be presented in a PICO format for participant discussion.
Xiong, Wu; Zhao, Qingyun; Xue, Chao; Xun, Weibing; Zhao, Jun; Wu, Huasong; Li, Rong; Shen, Qirong
2016-01-01
Long-term vanilla monocropping often results in the occurrence of vanilla Fusarium wilt disease, seriously affecting its production all over the world. In the present study, vanilla exhibited significantly less Fusarium wilt disease in the soil of a long-term continuously cropped black pepper orchard. The entire fungal communities of bulk and rhizosphere soils between the black pepper-vanilla system (i.e., vanilla cropped in the soil of a continuously cropped black pepper orchard) and vanilla monoculture system were compared through the deep pyrosequencing. The results showed that the black pepper-vanilla system revealed a significantly higher fungal diversity than the vanilla monoculture system in both bulk and rhizosphere soils. The UniFrac-weighted PCoA analysis revealed significant differences in bulk soil fungal community structures between the two cropping systems, and fungal community structures were seriously affected by the vanilla root system. In summary, the black pepper-vanilla system harbored a lower abundance of Fusarium oxysporum in the vanilla rhizosphere soil and increased the putatively plant-beneficial fungal groups such as Trichoderma and Penicillium genus, which could explain the healthy growth of vanilla in the soil of the long-term continuously cropped black pepper field. Thus, cropping vanilla in the soil of continuously cropped black pepper fields for maintaining the vanilla industry is executable and meaningful as an agro-ecological system.
Xiong, Wu; Zhao, Qingyun; Xue, Chao; Xun, Weibing; Zhao, Jun; Wu, Huasong; Li, Rong; Shen, Qirong
2016-01-01
Long-term vanilla monocropping often results in the occurrence of vanilla Fusarium wilt disease, seriously affecting its production all over the world. In the present study, vanilla exhibited significantly less Fusarium wilt disease in the soil of a long-term continuously cropped black pepper orchard. The entire fungal communities of bulk and rhizosphere soils between the black pepper-vanilla system (i.e., vanilla cropped in the soil of a continuously cropped black pepper orchard) and vanilla monoculture system were compared through the deep pyrosequencing. The results showed that the black pepper-vanilla system revealed a significantly higher fungal diversity than the vanilla monoculture system in both bulk and rhizosphere soils. The UniFrac-weighted PCoA analysis revealed significant differences in bulk soil fungal community structures between the two cropping systems, and fungal community structures were seriously affected by the vanilla root system. In summary, the black pepper-vanilla system harbored a lower abundance of Fusarium oxysporum in the vanilla rhizosphere soil and increased the putatively plant-beneficial fungal groups such as Trichoderma and Penicillium genus, which could explain the healthy growth of vanilla in the soil of the long-term continuously cropped black pepper field. Thus, cropping vanilla in the soil of continuously cropped black pepper fields for maintaining the vanilla industry is executable and meaningful as an agro-ecological system. PMID:26903995
NASA Astrophysics Data System (ADS)
Dempster, William F.; Nelson, M.; Silverstone, S.; Allen, J. P.
2009-04-01
A mixed crop consisting of cowpeas, pinto beans and Apogee ultra-dwarf wheat was grown in the Laboratory Biosphere, a 40 m 3 closed life system equipped with 12,000 W of high pressure sodium lamps over planting beds with 5.37 m 2 of soil. Similar to earlier reported experiments, the concentration of carbon dioxide initially increased to 7860 ppm at 10 days after planting due to soil respiration plus CO 2 contributed from researchers breathing while in the chamber for brief periods before plant growth became substantial. Carbon dioxide concentrations then fell rapidly as plant growth increased up to 29 days after planting and subsequently was maintained mostly in the range of about 200-3000 ppm (with a few excursions) by CO 2 injections to feed plant growth. Numerous analyses of rate of change of CO 2 concentration at many different concentrations and at many different days after planting reveal a strong dependence of fixation rates on CO 2 concentration. In the middle period of growth (days 31-61), fixation rates doubled for CO 2 at 450 ppm compared to 270 ppm, doubled again at 1000 ppm and increased a further 50% at 2000 ppm. High productivity from these crops and the increase of fixation rates with elevated CO 2 concentration supports the concept that enhanced CO 2 can be a useful strategy for remote life support systems. The data suggests avenues of investigation to understand the response of plant communities to increasing CO 2 concentrations in the Earth's atmosphere. Carbon balance accounting and evapotranspiration rates are included.
Cover crop biomass harvest for bioenergy: implications for crop productivity
USDA-ARS?s Scientific Manuscript database
Winter cover crops, such as rye (Secale cereale), are usually used in conservation agriculture systems in the Southeast. Typically, the cover crop is terminated two to three weeks before planting the summer crop, with the cover biomass left on the soil surface as a mulch. However, these cover crops ...
Origins of food crops connect countries worldwide
Achicanoy, Harold A.; Bjorkman, Anne D.; Navarro-Racines, Carlos; Guarino, Luigi; Flores-Palacios, Ximena; Engels, Johannes M. M.; Wiersema, John H.; Dempewolf, Hannes; Sotelo, Steven; Ramírez-Villegas, Julian; Castañeda-Álvarez, Nora P.; Fowler, Cary; Jarvis, Andy; Rieseberg, Loren H.; Struik, Paul C.
2016-01-01
Research into the origins of food plants has led to the recognition that specific geographical regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not been quantified. Here we determine the origins (‘primary regions of diversity’) of the crops comprising the food supplies and agricultural production of countries worldwide. We estimate the degree to which countries use crops from regions of diversity other than their own (‘foreign crops’), and quantify changes in this usage over the past 50 years. Countries are highly interconnected with regard to primary regions of diversity of the crops they cultivate and/or consume. Foreign crops are extensively used in food supplies (68.7% of national food supplies as a global mean are derived from foreign crops) and production systems (69.3% of crops grown are foreign). Foreign crop usage has increased significantly over the past 50 years, including in countries with high indigenous crop diversity. The results provide a novel perspective on the ongoing globalization of food systems worldwide, and bolster evidence for the importance of international collaboration on genetic resource conservation and exchange.
Soil profile organic carbon as affected by tillage and cropping systems
USDA-ARS?s Scientific Manuscript database
Reports on the long-term effects of tillage and cropping systems on soil organic carbon (SOC) sequestration in the entire rooting profile are limited. A long-term experiment with three cropping systems [continuous corn (CC), continuous soybean (CSB), and soybean-corn (SB-C)] in six primary tillage s...
A low-cost microcontroller-based system to monitor crop temperature and water status
USDA-ARS?s Scientific Manuscript database
A prototype microcontroller-based system was developed to automate the measurement and recording of soil-moisture status and canopy-, air-, and soil-temperature levels in cropped fields. Measurements of these conditions within the cropping system are often used to assess plant stress, and can assis...
Two contrasted future scenarios for the French agro-food system.
Billen, Gilles; Le Noë, Julia; Garnier, Josette
2018-10-01
Narratives of two prospective scenarios for the future of French agriculture were elaborated by pushing several trends already acting on the dynamics of the current system to their logical end. The first one pursues the opening and specialization characterizing the long-term evolution of the last 50 years of most French agricultural regions, while the second assumes a shift, already perceptible through weak signals, towards more autonomy at the farm and regional scales, a reconnection of crop and livestock farming and a more frugal human diet. A procedure is proposed to translate these qualitative narratives into a quantitative description of the corresponding nutrient fluxes using the GRAFS (Generalized Representation of Agro-Food Systems) methodology, thus allowing a comprehensive exploration of the agronomical and environmental performance of these two scenarios. The results show that the pursuit of the opening and specialization of French agriculture, even complying with regulations regarding reasoned fertilization, would result in considerable environmental burdens namely in terms of water pollution. The scenario generalizing organic farming practices, reconnection of crop and livestock farming systems and a demitarian human diet makes it possible to meet the future national food demand while still exporting significant amounts of cereals to the international market and ensuring better groundwater quality in most French regions. Copyright © 2018 Elsevier B.V. All rights reserved.
Liu, Luo; Xu, Xinliang; Zhuang, Dafang; Chen, Xi; Li, Shuang
2013-01-01
The multiple cropping practice is essential to agriculture because it has been shown to significantly increase the grain yield and promote agricultural economic development. In this study, potential multiple cropping systems in China are calculated based on meteorological observation data by using the Agricultural Ecology Zone (AEZ) model. Following this, the changes in the potential cropping systems in response to climate change between the 1960s and the 2010s were subsequently analyzed. The results indicate that the changes of potential multiple cropping systems show tremendous heterogeneity in respect to the spatial pattern in China. A key finding is that the magnitude of change of the potential cropping systems showed a pattern of increase both from northern China to southern China and from western China to eastern China. Furthermore, the area found to be suitable only for single cropping decreased, while the area suitable for triple cropping increased significantly from the 1960s to the 2000s. During the studied period, the potential multiple cropping index (PMCI) gap between rain-fed and irrigated scenarios increased from 18% to 24%, which indicated noticeable growth of water supply limitations under the rain-fed scenario. The most significant finding of this research was that from the 1960s to the 2000s climate change had led to a significant increase of PMCI by 13% under irrigated scenario and 7% under rain-fed scenario across the whole of China. Furthermore, the growth of the annual mean temperature is identified as the main reason underlying the increase of PMCI. It has also been noticed that across China the changes of potential multiple cropping systems under climate change were different from region to region.
Modeling and control for closed environment plant production systems
NASA Technical Reports Server (NTRS)
Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)
2002-01-01
A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.
NASA Technical Reports Server (NTRS)
Parton, William J.; Ojima, Dennis S.; Schimel, David S.; Kittel, Timothy G. F.
1992-01-01
During the past decade, a growing need to conduct regional assessments of long-term trends of ecosystem behavior and the technology to meet this need have converged. The Century model is the product of research efforts initially intended to develop a general model of plant-soil ecosystem dynamics for the North American central grasslands. This model is now being used to simulate plant production, nutrient cycling, and soil organic matter dynamics for grassland, crop, forest, and shrub ecosystems in various regions of the world, including temperate and tropical ecosystems. This paper will focus on the philosophical approach used to develop the structure of Century. The steps included were model simplification, parameterization, and testing. In addition, the importance of acquiring regional data bases for model testing and the present regional application of Century in the Great Plains, which focus on regional ecosystem dynamics and the effect of altering environmental conditions, are discussed.
Education and research in fluid dynamics
NASA Astrophysics Data System (ADS)
López González-Nieto, P.; Redondo, J. M.; Cano, J. L.
2009-04-01
Fluid dynamics constitutes an essential subject for engineering, since auronautic engineers (airship flights in PBL, flight processes), industrial engineers (fluid transportation), naval engineers (ship/vessel building) up to agricultural engineers (influence of the weather conditions on crops/farming). All the above-mentioned examples possess a high social and economic impact on mankind. Therefore, the fluid dynamics education of engineers is very important, and, at the same time, this subject gives us an interesting methodology based on a cycle relation among theory, experiments and numerical simulation. The study of turbulent plumes -a very important convective flow- is a good example because their theoretical governing equations are simple; it is possible to make experimental plumes in an aesy way and to carry out the corresponding numerical simulatons to verify experimental and theoretical results. Moreover, it is possible to get all these aims in the educational system (engineering schools or institutions) using a basic laboratory and the "Modellus" software.
NASA Astrophysics Data System (ADS)
Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha
2018-06-01
Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.
NASA Astrophysics Data System (ADS)
Austin, E.; Grandy, S.; Wickings, K.; McDaniel, M. D.; Robertson, P.
2016-12-01
Crop residues are potential biofuel feedstocks, but residue removal may result in reduced soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass and as well as help to mitigate the negative effects of residue removal by adding belowground C to stable soil C pools. In a no-till continuous corn bioenergy system in the northern portion of the US corn belt, we used 13CO2 pulse labeling to trace C in a winter rye (secale cereale) cover crop into different soil C pools for two years following rye termination. Corn stover contributed 66 (another 163 was in harvested corn stover), corn roots 57, rye shoot 61, rye roots 59, and rye rhizodeposits 27 g C m-2 to soil C. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools and much of the root-derived C was in mineral- associated soil fractions. Our results underscore the importance of cover crop roots vs. shoots as a source of soil C. Belowground C inputs from winter cover crops could substantially offset short term stover removal in this system.
NASA Technical Reports Server (NTRS)
Sand, F.; Christie, R.
1975-01-01
Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.
USDA-ARS?s Scientific Manuscript database
Trap cropping is a behaviorally-based pest management approach that functions by planting highly attractive plants next to a higher value crop so as to attract the pest to the trap crop plants, thus preventing or making less likely the arrival of the pest to the main crop (= cash crop). In 2012, a s...
Grand challenges for crop science
USDA-ARS?s Scientific Manuscript database
Crop science is a highly integrative science using the disciplines of conventional plant breeding, transgenic crop improvement, plant physiology, and cropping system sciences to develop improved varieties of agronomic, turf, and forage crops to produce feed, food, fuel, and fiber for our world's gro...
NASA Astrophysics Data System (ADS)
Amiro, B. D.; Tenuta, M.; Gao, X.; Gervais, M.
2016-12-01
The Fluxnet database has over 100 cropland sites, some of which have long-term (over a decade) measurements. Carbon neutrality is one goal of sustainable agriculture, although measurements over many annual cropping systems have indicated that soil carbon is often lost. Croplands are complex systems because the CO2 exchange depends on the type of crop, soil, weather, and management decisions such as planting date, nutrient fertilization and pest management strategy. Crop rotations are often used to decrease pest pressure, and can range from a simple 2-crop system, to have 4 or more crops in series. Carbon dioxide exchange has been measured using the flux-gradient technique since 2006 in agricultural systems in Manitoba, Canada. Two cropping systems are being followed: one that is a rotation of annual crops (corn, faba bean, spring wheat, rapeseed, barley, spring wheat, corn, soybean, spring wheat, soybean); and the other with a perennial phase of alfalfa/grass in years 3 to 6. Net ecosystem production ranged from a gain of 330 g C m-2 y-1 in corn to a loss of 75 g C m-2 y-1 in a poor spring-wheat crop. Over a decade, net ecosystem production for the annual cropping system was not significantly different from zero (carbon neutral), but the addition of the perennial phase increased the sink to 130 g C m-2 y-1. Once harvest removals were included, there was a net loss of carbon ranging from 77 g C m-2 y-1 in the annual system to 52 g C m-2 y-1 in the annual-perennial system; but neither of these were significantly different from zero. Termination of the perennial phase of the rotation only caused short-term increases in respiration. We conclude that both these systems were close to carbon-neutral over a decade even though they were tilled with a short growing season (90 to 130 days). We discuss the need for more datasets on agricultural systems to inform management options to increase the soil carbon sink.
NASA Astrophysics Data System (ADS)
Marcinkeviciene, A.; Boguzas, V.; Balnyte, S.; Pupaliene, R.; Velicka, R.
2013-02-01
The influence of crop rotation systems with different portions of nitrogen-fixing crops, intermediate crops, and organic fertilizers on the enzymatic activity and humus content of soils in organic farming was studied. The highest activity of the urease and invertase enzymes was determined in the soil under the crop rotation with 43% nitrogen-fixing crops and with perennial grasses applied twice per rotation. The application of manure and the growing of intermediate crops for green fertilizers did not provide any significant increase in the content of humus. The activity of urease slightly correlated with the humus content ( r = 0.30 at the significance level of 0.05 and r = 0.39 at the significance level of 0.01).
Network-assisted crop systems genetics: network inference and integrative analysis.
Lee, Tak; Kim, Hyojin; Lee, Insuk
2015-04-01
Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.
Operational seasonal forecasting of crop performance.
Stone, Roger C; Meinke, Holger
2005-11-29
Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.
Operational seasonal forecasting of crop performance
Stone, Roger C; Meinke, Holger
2005-01-01
Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097
Impact of crop rotation and soil amendments on long-term no-tilled soybean yields
USDA-ARS?s Scientific Manuscript database
Continuous cropping systems without cover crops are perceived as unsustainable for long-term yield and soil health. To test this, cropping sequence and cover crop effects on soybean (Glycine max L.) yields were assessed. Main effects were 10 cropping sequences of soybean, corn (Zea mays L.), and co...
Expert system for controlling plant growth in a contained environment
NASA Technical Reports Server (NTRS)
May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)
2011-01-01
In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".
Expert system for controlling plant growth in a contained environment
NASA Technical Reports Server (NTRS)
May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)
2009-01-01
In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.
Sediment and PM10 flux from no-tillage cropping systems in the Pacific Northwest
USDA-ARS?s Scientific Manuscript database
Wind erosion is a concern in the Inland Pacific Northwest (PNW) United States where the emission of fine particulates from winter wheat – summer fallow (WW/SF) dryland cropping systems during high winds degrade air quality. Although no-tillage cropping systems are not yet economically viable, these ...
USDA-ARS?s Scientific Manuscript database
Cover crops often provide many short- and long-term benefits to cropping systems. Legume cover crops can significantly reduce the N fertilizer requirement of non-legume cash crops that follow. The objectives of this presentation were to: I) educate stakeholders about the potential benefits of cover ...
Slewinski, Thomas L
2012-08-01
A dramatic change in agricultural crops is needed in order to keep pace with the demands of an increasing human population, exponential need for renewable fuels, and uncertain climatic changes. Grasses make up the vast majority of agricultural commodities. How these grasses capture, transport, and store carbohydrates underpins all aspects of crop productivity. Sink-source dynamics within the plant direct how much, where, and when carbohydrates are allocated, as well as determine the harvestable tissue. Carbohydrate partitioning can limit the yield capacity of these plants, thus offering a potential target for crop improvement. Grasses have the ability to buffer this sink-source interaction by transiently storing carbohydrates in stem tissue when production from the source is greater than whole-plant demand. These reserves improve yield stability in grain crops by providing an alternative source when photosynthetic capacity is reduced during the later phases of grain filling, or during periods of environmental and biotic stresses. Domesticated grasses such as sugarcane and sweet sorghum have undergone selection for high accumulation of stem carbohydrates, which serve as the primary sources of sugars for human and animal consumption, as well as ethanol production for fuel. With the enormous expectations placed on agricultural production in the near future, research into carbohydrate partitioning in grasses is essential for maintaining and increasing yields in grass crops. This review highlights the current knowledge of non-structural carbohydrate dynamics in grass stems and discusses the impacts of stem reserves in essential agronomic grasses.
NASA Astrophysics Data System (ADS)
Marohn, C.; Distel, A.; Dercon, G.; Wahyunto; Tomlinson, R.; Noordwijk, M. v.; Cadisch, G.
2012-09-01
The Indian Ocean tsunami of December 2004 had far reaching consequences for agriculture in Aceh province, Indonesia, and particularly in Aceh Barat district, 150 km from the seaquake epicentre. In this study, the spatial distribution and temporal dynamics of soil and groundwater salinity and their impact on tree crops were monitored in Aceh Barat from 2006 to 2008. On 48 sampling points along ten transects, covering 40 km of coastline, soil and groundwater salinity were measured and related to mortality and yield depression of the locally most important tree crops. Given a yearly rainfall of over 3000 mm, initial groundwater salinity declined rapidly from over 10 to less than 2 mS cm-1 within two years. On the other hand, seasonal dynamics of the groundwater table in combination with intrusion of saline water into the groundwater body led to recurring elevated salinity, sufficient to affect crops. Tree mortality and yield depression in the flooded area varied considerably between tree species. Damage to coconut (65% trees damaged) was related to tsunami run-up height, while rubber (50% trees damaged) was mainly affected by groundwater salinity. Coconut yields (-35% in average) were constrained by groundwater Ca2+ and Mg2+, while rubber yields (-65% on average) were related to groundwater chloride, pH and soil sodium. These findings have implications on planting deep-rooted tree crops as growth will be constrained by ongoing oscillations of the groundwater table and salinity.
Annual dynamics of wild bee densities: attractiveness and productivity effects of oilseed rape.
Riedinger, Verena; Mitesser, Oliver; Hovestadt, Thomas; Steffan-Dewenter, Ingolf; Holzschuh, Andrea
2015-05-01
Mass-flowering crops may affect long-term population dynamics, but effects on pollinators have never been studied across several years. We monitored wild bees in oilseed rape fields in 16 landscapes in Germany in two consecutive years. Effects on bee densities of landscape oilseed rape cover in the years of monitoring and in the previous years were evaluated with landscape data from three consecutive years. We fit empirical data to a mechanistic model to provide estimates for oilseed rape attractiveness and its effect on bee productivity in comparison to the rest of the landscape, and we evaluated consequences for pollinator densities in consecutive years. Our results show that high oilseed rape cover in the previous year enhances current densities of wild bees (except for bumble bees). Moreover, we show a strong attractiveness of and dilution on (i.e., decreasing bee densities with increasing landscape oilseed rape cover) oilseed rape for bees during flowering in the current year, modifying the effect of the previous year's oilseed rape cover in the case of wild bees (excluding Bombus). As long as other factors such as nesting sites or natural enemies do not limit bee reproduction, our findings suggest long-term positive effects of mass-flowering crops on bee populations, at least for non-Bombus generalists, which possibly help to maintain crop pollination services even when crop area increases. Similar effects are conceivable for other organisms providing ecosystem services in annual crops and should be considered in future studies.
Increasing Cropping System Diversity Balances Productivity, Profitability and Environmental Health
Davis, Adam S.; Hill, Jason D.; Chase, Craig A.; Johanns, Ann M.; Liebman, Matt
2012-01-01
Balancing productivity, profitability, and environmental health is a key challenge for agricultural sustainability. Most crop production systems in the United States are characterized by low species and management diversity, high use of fossil energy and agrichemicals, and large negative impacts on the environment. We hypothesized that cropping system diversification would promote ecosystem services that would supplement, and eventually displace, synthetic external inputs used to maintain crop productivity. To test this, we conducted a field study from 2003–2011 in Iowa that included three contrasting systems varying in length of crop sequence and inputs. We compared a conventionally managed 2-yr rotation (maize-soybean) that received fertilizers and herbicides at rates comparable to those used on nearby farms with two more diverse cropping systems: a 3-yr rotation (maize-soybean-small grain + red clover) and a 4-yr rotation (maize-soybean-small grain + alfalfa-alfalfa) managed with lower synthetic N fertilizer and herbicide inputs and periodic applications of cattle manure. Grain yields, mass of harvested products, and profit in the more diverse systems were similar to, or greater than, those in the conventional system, despite reductions of agrichemical inputs. Weeds were suppressed effectively in all systems, but freshwater toxicity of the more diverse systems was two orders of magnitude lower than in the conventional system. Results of our study indicate that more diverse cropping systems can use small amounts of synthetic agrichemical inputs as powerful tools with which to tune, rather than drive, agroecosystem performance, while meeting or exceeding the performance of less diverse systems. PMID:23071739
Increasing cropping system diversity balances productivity, profitability and environmental health.
Davis, Adam S; Hill, Jason D; Chase, Craig A; Johanns, Ann M; Liebman, Matt
2012-01-01
Balancing productivity, profitability, and environmental health is a key challenge for agricultural sustainability. Most crop production systems in the United States are characterized by low species and management diversity, high use of fossil energy and agrichemicals, and large negative impacts on the environment. We hypothesized that cropping system diversification would promote ecosystem services that would supplement, and eventually displace, synthetic external inputs used to maintain crop productivity. To test this, we conducted a field study from 2003-2011 in Iowa that included three contrasting systems varying in length of crop sequence and inputs. We compared a conventionally managed 2-yr rotation (maize-soybean) that received fertilizers and herbicides at rates comparable to those used on nearby farms with two more diverse cropping systems: a 3-yr rotation (maize-soybean-small grain + red clover) and a 4-yr rotation (maize-soybean-small grain + alfalfa-alfalfa) managed with lower synthetic N fertilizer and herbicide inputs and periodic applications of cattle manure. Grain yields, mass of harvested products, and profit in the more diverse systems were similar to, or greater than, those in the conventional system, despite reductions of agrichemical inputs. Weeds were suppressed effectively in all systems, but freshwater toxicity of the more diverse systems was two orders of magnitude lower than in the conventional system. Results of our study indicate that more diverse cropping systems can use small amounts of synthetic agrichemical inputs as powerful tools with which to tune, rather than drive, agroecosystem performance, while meeting or exceeding the performance of less diverse systems.
NASA Technical Reports Server (NTRS)
Baker, T. C. (Principal Investigator)
1982-01-01
A general methodology is presented for estimating a stratum's at-harvest crop acreage proportion for a given crop year (target year) from the crop's estimated acreage proportion for sample segments from within the stratum. Sample segments from crop years other than the target year are (usually) required for use in conjunction with those from the target year. In addition, the stratum's (identifiable) crop acreage proportion may be estimated for times other than at-harvest in some situations. A by-product of the procedure is a methodology for estimating the change in the stratum's at-harvest crop acreage proportion from crop year to crop year. An implementation of the proposed procedure as a statistical analysis system routine using the system's matrix language module, PROC MATRIX, is described and documented. Three examples illustrating use of the methodology and algorithm are provided.
Zhao, ZiHua; Shi, PeiJian; Men, XingYuan; Ouyang, Fang; Ge, Feng
2013-08-01
The relationship between crop richness and predator-prey interactions as they relate to pest-natural enemy systems is a very important topic in ecology and greatly affects biological control services. The effects of crop arrangement on predator-prey interactions have received much attention as the basis for pest population management. To explore the internal mechanisms and factors driving the relationship between crop richness and pest population management, we designed an experimental model system of a microlandscape that included 50 plots and five treatments. Each treatment had 10 repetitions in each year from 2007 to 2010. The results showed that the biomass of pests and their natural enemies increased with increasing crop biomass and decreased with decreasing crop biomass; however, the effects of plant biomass on the pest and natural enemy biomass were not significant. The relationship between adjacent trophic levels was significant (such as pests and their natural enemies or crops and pests), whereas non-adjacent trophic levels (crops and natural enemies) did not significantly interact with each other. The ratio of natural enemy/pest biomass was the highest in the areas of four crop species that had the best biological control service. Having either low or high crop species richness did not enhance the pest population management service and lead to loss of biological control. Although the resource concentration hypothesis was not well supported by our results, high crop species richness could suppress the pest population, indicating that crop species richness could enhance biological control services. These results could be applied in habitat management aimed at biological control, provide the theoretical basis for agricultural landscape design, and also suggest new methods for integrated pest management.
NASA Astrophysics Data System (ADS)
Boschetti, Mirco; Holectz, Francesco; Manfron, Giacinto; Collivignarelli, Francesco; Nelson, Andrew
2013-04-01
Updated information on crop typology and status are strongly required to support suitable action to better manage agriculture production and reduce food insecurity. In this field, remote sensing has been demonstrated to be a suitable tool to monitor crop condition however rarely the tested system became really operative. The ones today available, such as the European Commission MARS, are mainly based on the analysis of NDVI time series and required ancillary external information like crop mask to interpret the seasonal signal. This condition is not always guarantied worldwide reducing the potentiality of the remote sensing monitoring. Moreover in tropical countries cloud contamination strongly reduce the possibility of using optical remote sensing data for crop monitoring. In this framework we focused our analysis on the rice production monitoring in Asian tropical area. Rice is in fact the staple food for half of the world population (FAO 2004), in Asia almost 90% of the world's rice is produced and consumed and Rice and poverty often coincide. In this contest the production of reliable rice production information is of extreme interest. We tried to address two important issue in terms of required geospatial information for crop monitoring: rice crop detection (rice map) and seasonal dynamics analysis (phenology). We use both SAR and Optical data in order to exploit the potential complementarity of this system. Multi-temporal ASAR Wide Swath data are in fact the best option to deal with cloud contamination. SAR can easily penetrate the clouds providing information on the surface target. Temporal analysis of archive ASAR data allowed to derived accurate map, at 100m spatial resolution, of permanent rice cultivated areas. On the other and high frequency revisiting optical data, in this case MODIS, have been used to extract seasonal information for the year under analysis. MOD09A1 Surface Reflectance 8-Day L3 Global 500m have been exploited to derive time series of Vegetation Index. A temporal smoothing procedure based on Savitzky-Golay polynomial filter function was applied to the original 8-day composite VI data (EVI and NDVI) in order to eliminate spurious data which affect the time series and to produce an interpolated VI temporal profile. Finally within the area previously identify as rice by SAR analysis phenological estimation have been conducted. Crop growth minima and maxima, respectively indicator of rice transplanting and heading, have been identify from the derivative analysis time series. This procedure was tested in Bangladesh for the year 2011. Results showed that the combined use of both data typology represents the more suitable multisource framework to provide reliable information on rice crop growth. Preliminary maps analysis reveals how SAR rice detection was in agreement with local information and phenology extracted by MODIS data provided spatially distributed data comparable with local knowledge of crop calendar.
Impact of bioenergy production on carbon storage and soil functions
NASA Astrophysics Data System (ADS)
Prays, Nadia; Franko, Uwe
2016-04-01
An important renewable energy source is methane produced in biogas plants (BGPs) that convert plant material and animal excrements to biogas and a residue (BGR). If the plant material stems from crops produced specifically for that purpose, a BGP have a 'footprint' that is defined by the area of arable land needed for the production of these energy crops and the area for distributing the BGRs. The BGR can be used to fertilize these lands (reducing the need for carbon and nitrogen fertilizers), and the crop land can be managed to serve as a carbon sink, capturing atmospheric CO2. We focus on the ecological impact of different BGPs in Central Germany, with a specific interest in the long-term effect of BGR-fertilization on carbon storage within the footprint of a BGP. We therefore studied nutrient fluxes using the CANDY (CArbon and Nitrogen Dynamics) model, which processes site-specific information on soils, crops, weather, and land management to compute stocks and fluxes of carbon and nitrogen for agricultural fields. We used CANDY to calculated matter fluxes within the footprints of BGPs of different sizes, and studied the effect of the substrate mix for the BGP on the carbon dynamics of the soil. This included the land requirement of the BGR recycling when used as a fertilizer: the footprint of a BGP required for the production of the energy crop generally differs from its footprint required to take up its BGR. We demonstrate how these findings can be used to find optimal cropping choices and land management for sustainable soil use, maintaining soil fertility and other soil functions. Furthermore, site specific potentials and limitations for agricultural biogas production can be identified and applied in land-use planning.
NASA Astrophysics Data System (ADS)
Zarina, Livija; Zarina, Liga
2017-04-01
The nutrient balance in different crop rotations under organic cropping system has been investigated in Latvia at the Institute of Agricultural Resources and Economics since 2006. Latvia is located in a humid and moderate climatic region where the rainfall exceeds evaporation (soil moisture coefficient > 1) and the soil moisture regime is characteristic with percolation. The average annual precipitation is 670-850 mm. The average temperature varies from -6.7° C in January to 16.5 °C in July. The growing season is 175 - 185 days. The most widespread are podzolic soils and mainly they are present in agricultural fields in all regions of Latvia. In a wider sense the goal of the soil management in organic farming is a creation of the biologically active flora and fauna in the soil by maintaining a high level of soil organic matter which is good for crops nutrient balance. Crop rotation is a central component of organic farming systems and has many benefits, including growth of soil microbial activity, which may increase nutrient availability. The aim of the present study was to calculate nutrient balance for each crop in the rotations and average in each rotation. Taking into account that crop rotations can limit build-up of weeds, additionally within the ERA-net CORE Organic Plus transnational programs supported project PRODIVA the information required for a better utilization of crop diversification for weed management in North European organic arable cropping systems was summarized. It was found that the nutrient balance was influenced by nutrients uptake by biomass of growing crops in crop rotation. The number of weeds in the organic farming fields with crop rotation is dependent on the cultivated crops and the succession of crops in the crop rotation.
Automatic segmentation of trees in dynamic outdoor environments
USDA-ARS?s Scientific Manuscript database
Segmentation in dynamic outdoor environments can be difficult when the illumination levels and other aspects of the scene cannot be controlled. Specifically in agricultural contexts, a background material is often used to shield a camera's field of view from other rows of crops. In this paper, we ...
NASA Astrophysics Data System (ADS)
Kaffka, S.; Jenner, M.; Bucaram, S.; George, N.
2012-12-01
Both regulators and businesses need realistic estimates for the potential production of biomass feedstocks for biofuels and bioproducts. This includes the need to understand how climate change will affect mid-tem and longer-term crop performance and relative advantage. The California Biomass Crop Adoption Model is a partial mathematical programming optimization model that estimates the profit level needed for new crop adoption, and the crop(s) displaced when a biomass feedstock crop is added to the state's diverse set of cropping systems, in diverse regions of the state. Both yield and crop price, as elements of profit, can be varied. Crop adoption is tested against current farmer preferences derived from analysis of 10 years crop production data for all crops produced in California, collected by the California Department of Pesticide Regulation. Analysis of this extensive data set resulted in 45 distinctive, representative farming systems distributed across the state's diverse agro-ecological regions. Estimated yields and water use are derived from field trials combined with crop simulation, reported elsewhere. Crop simulation is carried out under different weather and climate assumptions. Besides crop adoption and displacement, crop resource use is also accounted, derived from partial budgets used for each crop's cost of production. Systematically increasing biofuel crop price identified areas of the state where different types of crops were most likely to be adopted. Oilseed crops like canola that can be used for biodiesel production had the greatest potential to be grown in the Sacramento Valley and other northern regions, while sugar beets (for ethanol) had the greatest potential in the northern San Joaquin Valley region, and sweet sorghum in the southern San Joaquin Valley. Up to approximately 10% of existing annual cropland in California was available for new crop adoption. New crops are adopted if the entire cropping system becomes more profitable. In particular, canola production resulted in less overall water use but increased farm profits. Most crop substitutions were resource neutral. If future climate is drier, more winter annual crops like canola are likely to be adopted. Crop displacement is also important for determining market-mediated effects of biomass crop production. Correctly estimating crop displacement at the local scale greatly improves upon estimates for indirect land use change derived from the macro-scale PE and CGE models currently used by US EPA and the California Air Resources Board.
NASA Astrophysics Data System (ADS)
Trisnawati, Indah; Azis, Abdul
2017-06-01
Many farms in regions of intensive crop production lack the habitats that historically provided resources to beneficial insects, and this lack has compromised the ability of farmers to rely on natural enemies for pest control. One of the strategies to boost populations of existing or naturally occurring beneficial insects is to supply them with appropriate habitat and alternative food sources, such as diversifying trap crop systems and plant populations in or around fields include perennials and flowering plants. Trap cropping using insectary plant that attracts beneficial insects as natural enemies, especially flowering plants, made for provision of habitat for predators or parasitoids that are useful for biological control. Perimeter trap cropping (PTC) is a method of integrated pest management in which the main crop is surrounded with a perimeter trap crop that is more attractive to pests. We observed PTC habitat modification and conventionaly-managed tobacco farms in Purwosari Village, Pasuruan (East Java) to evaluate the effectiveness of habitat modification management prescription (perimeter trap crop using flowering plant Crotalaria juncea) on agroecosystem natural enemies. Field tests were conducted in natural enemies (predator and parasitoid) abundance dynamic and diversity on tobacco field in Purwoasri, Pasuruan. Yellow pan trap, sweep net and hand collecting methods were applied in each 10 days during tobacco growth stage (vegetative, generative until reproductive/harvesting. The results showed that application perimeter trap crop with C. juncea in tobacco fields able to help arthropod conservation of natural enemies on all tobacco growth stages. These results were evidenced the increase in abundance of predators and parasitoids and the increased value of the Diversity Index (H') and Evenness Index (EH) in all tobacco growth phases. Composition of predator and parasitoid in the habitat modification field were more diverse than in the conventional field. Three specific predator species were found on habitat modification field, i.e.: Crocothemis servilia, Orthetrum sabina and Paratrechina sp., as well as specific parasitoid species, i.e.: Polistes sp. (vegetative stage), Chloromyia sp., Theronia sp., Sarcophaga sp. and Cletus sp (generative stage), Condylodtylus sp., Trichogramma sp. (reproductive stage). Trends in predator abundance toward parasitoid insects were indicated a positive linear trend, with the abundance of predator on habitat modification field has an influence on the level of 67.1% parasitoid.
Reevaluating Suitability Estimates Based on Dynamics of Cropland Expansion in the Brazilian Amazon
NASA Technical Reports Server (NTRS)
Morton, Douglas C.; Noojipady, Praveen; Macedo, Marcia M.; Victoria, Daniel C.; Bolfe, Edson L.
2016-01-01
Agricultural suitability maps are a key input for land use zoning and projections of cropland expansion. Suitability assessments typically consider edaphic conditions, climate, crop characteristics, and sometimes incorporate accessibility to transportation and market infrastructure. However, correct weighting among these disparate factors is challenging, given rapid development of new crop varieties, irrigation, and road networks, as well as changing global demand for agricultural commodities. Here, we compared three independent assessments of cropland suitability to spatial and temporal dynamics of agricultural expansion in the Brazilian state of Mato Grosso during 2001 2012. We found that areas of recent cropland expansion identified using satellite data were generally designated as low to moderate suitability for rainfed crop production. Our analysis highlighted the abrupt nature of suitability boundaries, rather than smooth gradients of agricultural potential, with little additional cropland expansion beyond the extent of the flattest areas (0-2% slope). Satellite-based estimates of the interannual variability in the use of existing crop areas also provided an alternate means to assess suitability. On average, cropland areas in the Cerrado biome had higher utilization (84%) than croplands in the Amazon region of northern Mato Grosso (74%). Areas of more recent expansion had lower utilization than croplands established before 2002, providing empirical evidence for lower suitability or alternative management strategies (e.g., pasture soya rotations) for lands undergoing more recent land use transitions. This unplanted reserve constitutes a large area of potentially available cropland (PAC)without further expansion, within the management limits imposed for pest management and fallow cycles. Using two key constraints on future cropland expansion, slope and restrictions on further deforestation of Amazon or Cerrado vegetation, we found little available flat land for further legal expansion of crop production in Mato Grosso. Dynamics of cropland expansion from more than a decade of satellite observations indicated narrow ranges of suitability criteria, restricting PAC under current policy conditions, and emphasizing the advantages of field-scale information to assess suitability and utilization.
Dynamic Model of the BIO-Plex Air Revitalization System
NASA Technical Reports Server (NTRS)
Finn, Cory; Meyers, Karen; Duffield, Bruce; Luna, Bernadette (Technical Monitor)
2000-01-01
The BIO-Plex facility will need to support a variety of life support system designs and operation strategies. These systems will be tested and evaluated in the BIO-Plex facility. An important goal of the life support program is to identify designs that best meet all size and performance constraints for a variety of possible future missions. Integrated human testing is a necessary step in reaching this goal. System modeling and analysis will also play an important role in this endeavor. Currently, simulation studies are being used to estimate air revitalization buffer and storage requirements in order to develop the infrastructure requirements of the BIO-Plex facility. Simulation studies are also being used to verify that the envisioned operation strategy will be able to meet all performance criteria. In this paper, a simulation study is presented for a nominal BIO-Plex scenario with a high-level of crop growth. A general description of the dynamic mass flow model is provided, along with some simulation results. The paper also discusses sizing and operations issues and describes plans for future simulation studies.
Shahzad, Muhammad; Hussain, Mubshar; Farooq, Muhammad; Farooq, Shahid; Jabran, Khawar; Nawaz, Ahmad
2017-11-01
Wheat productivity and profitability is low under conventional tillage systems as they increase the production cost, soil compaction, and the weed infestation. Conservation tillage could be a pragmatic option to sustain the wheat productivity and enhance the profitability on long term basis. This study was aimed to evaluate the economics of different wheat-based cropping systems viz. fallow-wheat, rice-wheat, cotton-wheat, mung bean-wheat, and sorghum-wheat, with zero tillage, conventional tillage, deep tillage, bed sowing (60/30 cm beds and four rows), and bed sowing (90/45 cm beds and six rows). Results indicated that the bed sown wheat had the maximum production cost than other tillage systems. Although both bed sowing treatments incurred the highest production cost, they generated the highest net benefits and benefit: cost ratio (BCR). Rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) had the highest net income (4129.7 US$ ha -1 ), BCR (2.87), and marginal rate of return compared with rest of the cropping systems. In contrast, fallow-wheat cropping system incurred the lowest input cost, but had the least economic return. In crux, rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) was the best option for getting the higher economic returns. Moreover, double cropping systems within a year are more profitable than sole planting of wheat under all tillage practices.
Smith, Richard G.; Atwood, Lesley W.; Warren, Nicholas D.
2014-01-01
Cover crops provide a variety of important agroecological services within cropping systems. Typically these crops are grown as monocultures or simple graminoid-legume bicultures; however, ecological theory and empirical evidence suggest that agroecosystem services could be enhanced by growing cover crops in species-rich mixtures. We examined cover crop productivity, weed suppression, stability, and carryover effects to a subsequent cash crop in an experiment involving a five-species annual cover crop mixture and the component species grown as monocultures in SE New Hampshire, USA in 2011 and 2012. The mean land equivalent ratio (LER) for the mixture exceeded 1.0 in both years, indicating that the mixture over-yielded relative to the monocultures. Despite the apparent over-yielding in the mixture, we observed no enhancement in weed suppression, biomass stability, or productivity of a subsequent oat (Avena sativa L.) cash crop when compared to the best monoculture component crop. These data are some of the first to include application of the LER to an analysis of a cover crop mixture and contribute to the growing literature on the agroecological effects of cover crop diversity in cropping systems. PMID:24847902
9 CFR 205.101 - Certification-request and processing.
Code of Federal Regulations, 2010 CFR
2010-01-01
... system will interpret the term “crop year” and how it will classify as to crop year an EFS not showing crop year; (10) Show what fee will be charged and explain how the costs of the system will be covered...
9 CFR 205.101 - Certification-request and processing.
Code of Federal Regulations, 2011 CFR
2011-01-01
... system will interpret the term “crop year” and how it will classify as to crop year an EFS not showing crop year; (10) Show what fee will be charged and explain how the costs of the system will be covered...
Soil Water Improvements with the Long Term Use of a Winter Rye Cover Crop
NASA Astrophysics Data System (ADS)
Basche, A.; Kaspar, T.; Archontoulis, S.; Jaynes, D. B.; Sauer, T. J.; Parkin, T.; Miguez, F.
2015-12-01
The Midwestern United States, a region that produces one-third of maize and one-quarter of soybeans globally, is projected to experience increasing rainfall variability with future climate change. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance soil water storage, reducing the risks of flooding and runoff as well as drought-induced crop water stress. While some research indicates that a winter cover crop in a maize-soybean rotation increases soil water, producers continue to be concerned that water use by cover crops will reduce water for a following cash crop. We analyzed continuous in-field soil moisture measurements over from 2008-2014 at a Central Iowa research site that has included a winter rye cover crop in a maize-soybean rotation for thirteen years. This period of study included years in the top third of wettest years on record (2008, 2010, 2014) as well as years in the bottom third of driest years (2012, 2013). We found the cover crop treatment to have significantly higher soil water storage from 2012-2014 when compared to the no cover crop treatment and in most years greater soil water content later in the growing season when a cover crop was present. We further found that the winter rye cover crop significantly increased the field capacity water content and plant available water compared to the no cover crop treatment. Finally, in 2012 and 2013, we measured maize and soybean biomass every 2-3 weeks and did not see treatment differences in crop growth, leaf area or nitrogen uptake. Final crop yields were not statistically different between the cover and no cover crop treatment in any of the years of this analysis. This research indicates that the long-term use of a winter rye cover crop can improve soil water dynamics without sacrificing cash crop growth.
Estimating European soil organic carbon mitigation potential in a global integrated land use model
NASA Astrophysics Data System (ADS)
Frank, Stefan; Böttcher, Hannes; Schneider, Uwe; Schmid, Erwin; Havlík, Petr
2013-04-01
Several studies have shown the dynamic interaction between soil organic carbon (SOC) sequestration rates, soil management decisions and SOC levels. Management practices such as reduced and no-tillage, improved residue management and crop rotations as well as the conversion of marginal cropland to native vegetation or conversion of cultivated land to permanent grassland offer the potential to increase SOC content. Even though dynamic interactions are widely acknowledged in literature, they have not been implemented in most existing land use decision models. A major obstacle is the high data and computing requirements for an explicit representation of alternative land use sequences since a model has to be able to track all different management decision paths. To our knowledge no study accounted so far for SOC dynamics explicitly in a global integrated land use model. To overcome these conceptual difficulties described above we apply an approach capable of accounting for SOC dynamics in GLOBIOM (Global Biosphere Management Model), a global recursive dynamic partial equilibrium bottom-up model integrating the agricultural, bioenergy and forestry sectors. GLOBIOM represents all major land based sectors and therefore is able to account for direct and indirect effects of land use change as well as leakage effects (e.g. through trade) implicitly. Together with the detailed representation of technologies (e.g. tillage and fertilizer management systems), these characteristics make the model a highly valuable tool for assessing European SOC emissions and mitigation potential. Demand and international trade are represented in this version of the model at the level of 27 EU member states and 23 aggregated world regions outside Europe. Changes in the demand on the one side, and profitability of the different land based activities on the other side, are the major determinants of land use change in GLOBIOM. In this paper we estimate SOC emissions from cropland for the EU until 2050 explicitly considering SOC dynamics due to land use and land management in a global integrated land use model. Moreover, we calculate the EU SOC mitigation potential taking into account leakage effects outside Europe as well as related feed backs from other sectors. In sensitivity analysis, we disaggregate the SOC mitigation potential i.e. we quantify the impact of different management systems and crop rotations to identify most promising mitigation strategies.
Asia’s Indigenous Horticultural Crops: An Introduction
USDA-ARS?s Scientific Manuscript database
Crop diversity is an urgent issue today in horticulture, which is faced with an erosion of crop variability as monoculture systems dominate crop production throughout the world, particularly in Europe and North America. At the same time there is great interest in indigenous horticultural crops aroun...
NASA Astrophysics Data System (ADS)
Ding, Deng
Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form of perennial grasses or corn stover as a more risky enterprise than their current crop production systems, likely because of market and production risks and lock in effects. As a result farmers do not follow a simple farm-profit maximization rule. In the third study, the consequent water quantity and quality change of the potential land use transitions given alternative biofuel crop market scenarios is explored in a case study in the Clear Creek watershed. A computer program is developed to implement the loose-coupling strategy to couple an agent-based land use model with SWAT. The simulation results show that watershed-scale water quantity (water yield and runoff) and quality variables (sediment and nutrient loads) decrease in values as switchgrass price increases. However, negligence of farmers risk aversions towards biofuel crop adoption would cause overestimation of the impacts of switchgrass price on water quantity and quality.
NASA Astrophysics Data System (ADS)
Bydekerke, Lieven; Gilliams, Sven; Gobin, Anne
2015-04-01
There is an urgent need to ensure food supply for a growing global population. To enable a sustainable growth of agricultural production, effective and timely information is required to support decision making and to improve management of agricultural resources. This requires innovative ways and monitoring methods that will not only improve short-term crop production forecasts, but also allow to assess changes in cultivation practices, agricultural areas, agriculture in general and, its impact on the environment. The G20 launched in June 2011 the "GEO Global Agricultural Monitoring initiative (GEOGLAM), requesting the GEO (Group on Earth Observations) Agricultural Community of Practice to implement GEOGLAM with the main objective to improve crop yield forecasts as an input to the Agricultural Market Information System (AMIS), in order to foster stabilisation of markets and increase transparency on agricultural production. In response to this need, the European Commission decided in 2013 to fund an international partnership to contribute to GEOGLAM and its research agenda. The resulting SIGMA project (Stimulating Innovation for Global Monitoring of Agriculture), a partnership of 23 globally distributed expert organisations, focusses on developing datasets and innovative techniques in support of agricultural monitoring and its impact on the environment in support of GEOGLAM. SIGMA has 3 generic objectives which are: (i) develop and test methods to characterise cropland and assess its changes at various scales; (ii) develop and test methods to assess changes in agricultural production levels; and; (iii) study environmental impacts of agriculture. Firstly, multi-scale remote sensing data sets, in combination with field and other ancillary data, will be used to generate an improved (global) agro-ecological zoning map and crop mask. Secondly, a combination of agro-meteorological models, satellite-based information and long-term time series will be explored to assess crop yield gaps and shifts in cultivation. The third research topic entails the development of best practices for assessing the impact of crop land and cropping system change on the environment. In support of the GEO JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative, SIGMA has selected case studies in Ukraine, Russia, Europe, Africa, Latin America and China, coinciding with the JECAM sites in these area, to explore possible methodological synergies and particularities according to different cropping systems. In combination with research conducted at regional and global scale, it is one of the goals to improve the understanding of dynamics, interactions and validity of the developed methods at the various scales. In addition, specific activities will be dedicated to raising awareness and strengthening capacity for what concerns agro-environmental monitoring, data accessibility and interoperability in line with the GEOSS Data-core principles. The SIGMA project will also anticipate on the availability of the SENTINEL satellites for agricultural applications as open-data in the near future. References http://proba-v.vgt.vito.be/ http://www.geoglam-sigma.info/
R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell
2015-01-01
The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi
2014-04-01
Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less
NASA Astrophysics Data System (ADS)
Ssegane, H.; Negri, M. C.
2015-12-01
Current and future demand for food, feed, fiber, and energy require novel approaches to land management, which demands that multifunctional landscapes are created to integrate various ecosystem functions into a sustainable land use. Concurrently, the Intergovernmental Panel on Climate Change (IPCC) predicts an increase of 2 to 4°C over the next 100 years above the preindustrial baseline, beginning as early as 2016 to 2035 over all seasons in the North America. This climate change is projected to further strain water resources currently stressed by anthropogenic activities. Therefore, placement of bioenergy crops on strategically selected sub-field areas in an agricultural landscape has the potential to increase the environmental and economic sustainability if location and choice of the crops result in minimal disruption of current food production systems and therefore cause minimal indirect land use change. This study identified sub-field marginal areas in an agricultural watershed using soil-based environmental sustainability criteria and a crop productivity index. Future landscape patterns (FLPs) were developed by allocating bioenergy crops (switchgrass: Panicum virgatum or shrub willows: Salix spp.) to these marginal areas (20% of the watershed). SWAT hydrologic model and dynamically downscaled climatic projection were used to asses impact of climate change on extreme flow conditions, total annual production of commodity and bioenergy crops, and water quality under current and future landscape patterns for the mid-21st century (2045-2055) and late 21st century (2085-2095) climatic projections. The frequency of flood and drought conditions was projected to increase while the corresponding durations to decrease. Sediment yields were projected to increase by 85% to 170% while FLPs would mitigate this increase by 26% to 32%.
Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.
2014-01-01
Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.
Virtual Sensors for Designing Irrigation Controllers in Greenhouses
Sánchez, Jorge Antonio; Rodríguez, Francisco; Guzmán, José Luis; Arahal, Manuel R
2012-01-01
Monitoring the greenhouse transpiration for control purposes is currently a difficult task. The absence of affordable sensors that provide continuous transpiration measurements motivates the use of estimators. In the case of tomato crops, the availability of estimators allows the design of automatic fertirrigation (irrigation + fertilization) schemes in greenhouses, minimizing the dispensed water while fulfilling crop needs. This paper shows how system identification techniques can be applied to obtain nonlinear virtual sensors for estimating transpiration. The greenhouse used for this study is equipped with a microlysimeter, which allows one to continuously sample the transpiration values. While the microlysimeter is an advantageous piece of equipment for research, it is also expensive and requires maintenance. This paper presents the design and development of a virtual sensor to model the crop transpiration, hence avoiding the use of this kind of expensive sensor. The resulting virtual sensor is obtained by dynamical system identification techniques based on regressors taken from variables typically found in a greenhouse, such as global radiation and vapor pressure deficit. The virtual sensor is thus based on empirical data. In this paper, some effort has been made to eliminate some problems associated with grey-box models: advance phenomenon and overestimation. The results are tested with real data and compared with other approaches. Better results are obtained with the use of nonlinear Black-box virtual sensors. This sensor is based on global radiation and vapor pressure deficit (VPD) measurements. Predictive results for the three models are developed for comparative purposes. PMID:23202208
Development and implementation of a GEOGLAM Crop Monitor web interface
NASA Astrophysics Data System (ADS)
Oliva, P.; Sanchez, A.; Humber, M. L.; Becker-Reshef, I.; Justice, C. J.; McGaughey, K.; Barker, B.
2016-12-01
Beginning in September 2013, the GEOGLAM Crop Monitor activity has provided earth observation (EO) data to a network of partners and collected crop assessments on a subnational basis through a web interface known as the Crop Assessment Tool. Based on the collection of monthly crop assessments, a monthly crop condition bulletin is published in the Agricultural Market Information System (AMIS) Market Monitor report. This workflow has been successfully applied to food security applications through the Early Warning Crop Monitor activity. However, a lack of timely and accurate information on crop conditions and prospects at the national scale is a critical issue in the majority of southern and eastern African countries and some South American countries. Such information is necessary for informed and prompt decision making in the face of emergencies, food insecurity and planning requirements for agricultural markets. This project addresses these needs through the development of relevant, user-friendly remote sensing monitor systems, collaborative internet technology, and collaboration with national and regional agricultural monitoring networks. By building on current projects and relationships established through the various GEOGLAM Crop Monitor activities, this project aims to ultimately provide EO-informed crop condition maps and charts designed for economics and policy oriented audiences, thereby providing quick and easy to understand products on crop conditions as the season progresses. Integrating these data and assessments vertically throughout the system provides a basis for regional sharing and collaboration in food security applications.
NASA Astrophysics Data System (ADS)
Chinnayakanahalli, K.; Adam, J. C.; Stockle, C.; Nelson, R.; Brady, M.; Rajagopalan, K.; Barber, M. E.; Dinesh, S.; Malek, K.; Yorgey, G.; Kruger, C.; Marsh, T.; Yoder, J.
2011-12-01
For better management and decision making in the face of climate change, earth system models must explicitly account for natural resource and agricultural management activities. Including crop system, water management, and economic models into an earth system modeling framework can help in answering questions related to the impacts of climate change on irrigation water and crop productivity, how agricultural producers can adapt to anticipated climate change, and how agricultural practices can mitigate climate change. Herein we describe the coupling of the Variability Infiltration Capacity (VIC) land surface model, which solves the water and energy balances of the hydrologic cycle at regional scales, with a crop-growth model, CropSyst. This new model, VIC-CropSyst, is the land surface model that will be used in a new regional-scale model development project focused on the Pacific Northwest, termed BioEarth. Here we describe the VIC-CropSyst coupling process and its application over the Columbia River basin (CRB) using agricultural-specific land cover information. The Washington State Department of Agriculture (WSDA) and U. S. Department of Agriculture (USDA) cropland data layers were used to identify agricultural land use patterns, in which both irrigated and dry land crops were simulated. The VIC-CropSyst model was applied over the CRB for the historical period of 1976 - 2006 to establish a baseline for surface water availability, irrigation demand, and crop production. The model was then applied under future (2030s) climate change scenarios derived from statistically-downscaled Global Circulation Models output under two emission scenarios (A1B and B1). Differences between simulated future and historical irrigation demand, irrigation water availability, and crop production were used in an economics model to identify the most economically-viable future cropping pattern. The economics model was run under varying scenarios of regional growth, trade, water pricing, and water capacity providing a spectrum of possible future cropping patterns. The resulting cropping patterns were then used in VIC-CropSyst to quantify the impacts of climate change, economic, and water management scenarios on crop production, and water resources availability. This modeling framework provides opportunities to study the interactions between human activities and complex natural processes and is a valuable tool for inclusion in an earth system model with the goal of informing land use and water management.
Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX
NASA Astrophysics Data System (ADS)
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho
2017-05-01
Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.
Tillage as a tool to manage crop residue: impact on sugar beet production.
NASA Astrophysics Data System (ADS)
Hiel, Marie-Pierre; Chélin, Marie; Degrune, Florine; Parvin, Nargish; Bodson, Bernard
2015-04-01
Crop residues and plant cover represent a pool of organic matter that can be used either to restore organic matter in soils, and therefore maintain soil fertility, or that can be valorized outside of the field (e.g. energy production). However, it is crucial that the exportation of residues is not done to the detriment of the system sustainability. Three long term experiments have been settled in the loamy region in Belgium. All of them are designed to study the effect of residues management by several tillage systems (conventional plowing versus reduced tillage) on the whole soil-water-plant system. SOLRESIDUS is a field experiment where we study the impact of crop residue management while in SOLCOUVERT and SOLCOUVERT-BIS, we study the impact of cover crop management. SOLRESIDUS was started in 2008. In this field, four contrasted crop residues managements are tested in order to contrast as much as possible the responses from the soil-water plant system. Two practices characterize the four modalities: soil tillage (ploughing at 25 cm depth or reduce tillage at 10 cm max) and residue management (exportation or restitution). SOLCOUVERT and SOLCOUVERT-BIS were started in 2012 and 2013 respectively. In those fields cover crop management is also diverse: destruction of the cover crop by winter ploughing, spring ploughing, strip tillage (with a chemical destruction if needed) or shallow tillage (with a decompaction before cover crop sowing). Although although the overall project aims at studying the impact of management on the whole soil-water-plant system, here we will only present the results concerning crop production (sugar beet) in SOLCOUVERT experiments. The presented data will include germination rate, crop development (biomass quantification and BBCH stages) weeds population, disease occurrence, pest occurrences, nitrogen uptake by plants, quality and quantity of harvested products.
V. Hernandez-Santana; X. Zhou; M.J. Helmers; H. Asbjornsen; R. Kolka; M. Tomer
2013-01-01
Intensively managed annual cropping systems have produced high crop yields but have often produced significant ecosystem services alteration, in particular hydrologic regulation loss. Reconversion of annual agricultural systems to perennial vegetation can lead to hydrologic function restoration, but its effect is still not well understood. Therefore, our objective was...
Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui
2016-01-01
Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697
Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui
2016-01-01
Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.
Regenerative Life Support Systems Test Bed performance - Lettuce crop characterization
NASA Technical Reports Server (NTRS)
Barta, Daniel J.; Edeen, Marybeth A.; Eckhardt, Bradley D.
1992-01-01
System performance in terms of human life support requirements was evaluated for two crops of lettuce (Lactuca sative cv. Waldmann's Green) grown in the Regenerative Life Support Systems Test Bed. Each crop, grown in separate pots under identical environmental and cultural conditions, was irrigated with half-strength Hoagland's nutrient solution, with the frequency of irrigation being increased as the crop aged over the 30-day crop tests. Averaging over both crop tests, the test bed met the requirements of 2.1 person-days of oxygen production, 2.4 person-days of CO2 removal, and 129 person-days of potential potable water production. Gains in the mass of water and O2 produced and CO2 removed could be achieved by optimizing environmental conditions to increase plant growth rate and by optimizing cultural management methods.
USDA-ARS?s Scientific Manuscript database
Many soil-inhabiting fungi are capable of surviving the dynamic soil microenvironment through the formation of resilient resting structures, such as thick-walled spores, melanized hyphae, and sclerotia. Verticillium dahliae is a soil-inhabiting, economically significant plant pathogenic fungus that ...
Salmonella spp. dynamics in wild blueberry, Vaccinium angustifolium Aiton
USDA-ARS?s Scientific Manuscript database
A six-year field study was conducted in the two major wild, or lowbush, blueberry growing regions in Maine, Midcoast and Downeast. This study used data from two cropping cycles (four years) to model the dynamics of Salmonella spp. prevalence in wild blueberry fields (Vaccinium angustifolium Aiton). ...
Flowering dynamics and pollinator visitation of oilseed echium (Echium plantagineum)
USDA-ARS?s Scientific Manuscript database
Echium (Echium plantagineum L.) is an alternative oilseed crop in summer-wet temperate regions that provides floral resources to pollinators. Its seed oil is rich in omega-3 fatty acids, such as stearidonic acid, which is desired highly by the cosmetic industry. We examined flowering dynamics, polli...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ye, Qing; Yang, Xiaoguang; Dai, Shuwei
Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.
[Impacts of climate change on food production in Gansu: A review].
Yang, Feng-ke; He, Bao-lin; Gao, Shi-ming
2015-03-01
The climate of Gansu turned to be overall warming-drying and partly warming-wetting since 1986. In contrast to that of 1960, the average annual temperature had raised by 1.1°C with the average annual precipitation decreased by 28 mm correspondingly, which made the arid region expanded southward by 50 km in 2010. Climate warming increased the growth period effective accumulated temperature of main food grain crops and lengthened the crop growth period. It changed crop maturity, crop disposition, cropping system and generally increased the cultivatable area and planting altitude above the sea level of major crops and expanded northward the multiple cropping system, which further resulted in expansion of autumn grain crop sown area, shrink of summer grain crop sown area, and replacement of strong winter early maturing varieties by weak winter middle late maturing varieties. It benefited the crop yield by increasing the use efficiency of photo-thermal resources. Warming-wetting climate increased the climate productivity of oasis crop while warming-drying weather decreased the climate productivity of rainfed crops, which were mostly determined by the precipitation regimes and water conditions. Any advanced technique that can increase precipitation use ratio and water use efficiency as well as improve and promote soil quality and fertility should be regarded as an effective countermeasure to increase food grain production under climate change in Gsansu. So, selecting and breeding new crop varieties with the characteristics of strong resistance, weak winter, middle-late mature and high water use efficiency, establishing new planting structure and cropping system that suitable to the precipitation and temperature features of changed climate, are the development direction of food grain production in Gansu to cope with the climate change.
NASA Astrophysics Data System (ADS)
Manfron, Giacinto; Delmotte, Sylvestre; Busetto, Lorenzo; Hossard, Laure; Ranghetti, Luigi; Brivio, Pietro Alessandro; Boschetti, Mirco
2017-05-01
Crop simulation models are commonly used to forecast the performance of cropping systems under different hypotheses of change. Their use on a regional scale is generally constrained, however, by a lack of information on the spatial and temporal variability of environment-related input variables (e.g., soil) and agricultural practices (e.g., sowing dates) that influence crop yields. Satellite remote sensing data can shed light on such variability by providing timely information on crop dynamics and conditions over large areas. This paper proposes a method for analyzing time series of MODIS satellite data in order to estimate the inter-annual variability of winter wheat sowing dates. A rule-based method was developed to automatically identify a reliable sample of winter wheat field time series, and to infer the corresponding sowing dates. The method was designed for a case study in the Camargue region (France), where winter wheat is characterized by vernalization, as in other temperate regions. The detection criteria were chosen on the grounds of agronomic expertise and by analyzing high-confidence time-series vegetation index profiles for winter wheat. This automatic method identified the target crop on more than 56% (four-year average) of the cultivated areas, with low commission errors (11%). It also captured the seasonal variability in sowing dates with errors of ±8 and ±16 days in 46% and 66% of cases, respectively. Extending the analysis to the years 2002-2012 showed that sowing in the Camargue was usually done on or around November 1st (±4 days). Comparing inter-annual sowing date variability with the main local agro-climatic drivers showed that the type of preceding crop and the weather conditions during the summer season before the wheat sowing had a prominent role in influencing winter wheat sowing dates.
Tracing crop-specific sediment sources in agricultural catchments
NASA Astrophysics Data System (ADS)
Blake, William H.; Ficken, Katherine J.; Taylor, Philip; Russell, Mark A.; Walling, Desmond E.
2012-02-01
A Compound Specific Stable Isotope (CSSI) sediment tracing approach is evaluated for the first time in an agricultural catchment setting against established geochemical fingerprinting techniques. The work demonstrates that novel CSSI techniques have the potential to provide important support for soil resource management policies and inform sediment risk assessment for the protection of aquatic habitats and water resources. Analysis of soil material from a range of crop covers in a mixed land-use agricultural catchment shows that the carbon CSSI signatures of particle-reactive fatty acids label surface agricultural soil with distinct crop-specific signatures, thus permitting sediment eroded from each land-cover to be tracked downstream. High resolution sediment sampling during a storm event and analysis for CSSI and conventional geochemical fingerprints elucidated temporal patterns of sediment mobilisation under different crop regimes and the specific contribution that each crop type makes to downstream sediment load. Pasture sources (65% of the catchment area) dominated the sediment load but areal yield (0.13 ± 0.02 t ha - 1 ) was considerably less than that for winter wheat (0.44 ± 0.15 t ha - 1 ). While temporal patterns in crop response matched runoff and erosion response predictions based on plot-scale rainfall simulation experiments, comparison of biomarker and geochemical fingerprinting data indicated that the latter overestimated cultivated land inputs to catchment sediment yield due to inability to discriminate temporary pasture (in rotation) from cultivated land. This discrepancy, however, presents an opportunity since combination of the two datasets revealed the extremely localised nature of erosion from permanent pasture fields in this system (estimated at up to 0.5 t ha - 1 ). The novel use of CSSI and geochemical tracers in tandem provided unique insights into sediment source dynamics that could not have been derived from each method alone. Research into CSSI signature development (plant and soil processes) and the influence of cultivation regimes are required to support future development of this new tool.
H.D. Stevenson; D.J. Robison; F.W. Cubbage; J.P. Mueller; M.G. Burton; M.H. Gocke
2013-01-01
Alley cropping may prove useful in the Southeast United States, providing multiple products and income streams, as well as affording sustainable land use alternatives to conventional farming. An alley-cropping system may be a good alternative in agriculture because of the benefits provided by trees to crops and soils, as well as the income generated from wood products...
The benefits of herbicide-resistant crops.
Green, Jerry M
2012-10-01
Since 1996, genetically modified herbicide-resistant crops, primarily glyphosate-resistant soybean, corn, cotton and canola, have helped to revolutionize weed management and have become an important tool in crop production practices. Glyphosate-resistant crops have enabled the implementation of weed management practices that have improved yield and profitability while better protecting the environment. Growers have recognized their benefits and have made glyphosate-resistant crops the most rapidly adopted technology in the history of agriculture. Weed management systems with glyphosate-resistant crops have often relied on glyphosate alone, have been easy to use and have been effective, economical and more environmentally friendly than the systems they have replaced. Glyphosate has worked extremely well in controlling weeds in glyphosate-resistant crops for more than a decade, but some key weeds have evolved resistance, and using glyphosate alone has proved unsustainable. Now, growers need to renew their weed management practices and use glyphosate with other cultural, mechanical and herbicide options in integrated systems. New multiple-herbicide-resistant crops with resistance to glyphosate and other herbicides will expand the utility of existing herbicide technologies and will be an important component of future weed management systems that help to sustain the current benefits of high-efficiency and high-production agriculture. Copyright © 2012 Society of Chemical Industry.
Williams, Alwyn; Jordan, Nicholas R; Smith, Richard G; Hunter, Mitchell C; Kammerer, Melanie; Kane, Daniel A; Koide, Roger T; Davis, Adam S
2018-05-31
Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.
Suppression of soilborne diseases of soybean with cover crops
USDA-ARS?s Scientific Manuscript database
Cover crops can foster the development of disease suppressive soils, and it has become common to use cover crops to manage soilborne diseases in high value crops. There is increasing interest in incorporating cover crops into agronomic systems in the Midwestern US for improving soil health. However,...
USDA-ARS?s Scientific Manuscript database
Cropping systems incorporating soil health management practices, such as longer rotations, disease-suppressive crops, reduced tillage, and/or organic amendments can substantially affect soil microbial communities, and potentially reduce soilborne potato diseases and increase productivity, but long-t...
Crop species diversity changes in the United States: 1978-2012
USDA-ARS?s Scientific Manuscript database
Anecdotal accounts regarding reduced US cropping system diversity have raised concerns about negative impacts of increasingly homogeneous cropping systems. However, formal analyses to document such changes are lacking. Using US Agriculture Census data, which is collected on 5-year intervals, we qua...
The impact of fall cover crops on soil nitrate and corn growth
USDA-ARS?s Scientific Manuscript database
Incorporating cover crops into current production systems can have many beneficial impacts on the current cropping system including decreasing erosion, improving water infiltration, increasing soil organic matter and biological activity but in water limited areas caution should be utilized. A fiel...
Opportunities and challenges for harvest weed seed control in global cropping systems.
Walsh, Michael J; Broster, John C; Schwartz-Lazaro, Lauren M; Norsworthy, Jason K; Davis, Adam S; Tidemann, Breanne D; Beckie, Hugh J; Lyon, Drew J; Soni, Neeta; Neve, Paul; Bagavathiannan, Muthukumar V
2017-11-28
The opportunity to target weed seeds during grain harvest was established many decades ago following the introduction of mechanical harvesting and the recognition of high weed-seed retention levels at crop maturity; however, this opportunity remained largely neglected until more recently. The introduction and adoption of harvest weed seed control (HWSC) systems in Australia has been in response to widespread occurrence of herbicide-resistant weed populations. With diminishing herbicide resources and the need to maintain highly productive reduced tillage and stubble-retention practices, growers began to develop systems that targeted weed seeds during crop harvest. Research and development efforts over the past two decades have established the efficacy of HWSC systems in Australian cropping systems, where widespread adoption is now occurring. With similarly dramatic herbicide resistance issues now present across many of the world's cropping regions, it is timely for HWSC systems to be considered for inclusion in weed-management programs in these areas. This review describes HWSC systems and establishing the potential for this approach to weed control in several cropping regions. As observed in Australia, the inclusion of HWSC systems can reduce weed populations substantially reducing the potential for weed adaptation and resistance evolution. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
Spectral variations of canopy reflectance in support of precision agriculture
NASA Astrophysics Data System (ADS)
Kancheva, Rumiana; Georgiev, Georgi; Borisova, Denitsa; Nikolov, Hristo
2014-05-01
Agricultural monitoring is an important and continuously spreading activity in remote sensing and applied Earth observations. It supplies precise, reliable and valuable information on current crop condition and growth processes. In agriculture, the timing of seasonal cycles of crop activity is important for species classification and evaluation of crop development, growing conditions and potential yield. The correct interpretation of remotely sensed data, however, and the increasing demand for data reliability require ground-truth knowledge of the seasonal spectral behavior of different species and their relation to crop vigor. For this reason, we performed ground-based study of the seasonal response of winter wheat reflectance patterns to crop growth patterns. The goal was to quantify crop seasonality by establishing empirical relationships between plant biophysical and spectral properties in main ontogenetic periods. Phenology and agro-specific relationships allow assessing crop condition during different portions of the growth cycle and thus effectively tracking plant development, and finally make yield predictions. The applicability of a number of vegetation indices (VIs) for monitoring crop seasonal dynamics, its health condition, and yield potential was examined. Special emphasis we put on narrow-band indices as the availability of data from hyperspectral imagers is unavoidable future. The temporal behavior of vegetation indices revealed increased sensitivity to crop growth. The derived spectral-biophysical relationships allowed extraction of quantitative information about crop variables and yield at different stages of the phenological development. Relating plant spectral and biophysical variables in a phenology-based manner allows crop monitoring, that is crop diagnosis and predictions to be performed multiple times during plant ontogenesis. During active vegetative periods spectral data was highly indicative of plant growth trends and yield potential. The VIs values contributed to reliable yield prediction and showed very good correspondence with the estimates from biophysical models. For dates before full maturity most of the examined VIs proved to be meaningful statistical predictors of crop state-indicative biophysical variables. High correlations were obtained for canopy cover fraction, LAI, and biomass. Sensitivity to red, near-infrared and green reflectance showed both vigorous and stressed plants. As crops attained advanced growth stages, decreased sensitivity of VIs and weaker correlations with bioparameters were observed, yet still significant in a statistical sense. The results highlight the capability of the presented approach to track the dynamics of crop growth from multitemporal spectral data, and illustrate the prediction accuracy of the spectral models. The results are useful in assessing the efficiency of various spectral band ratios and other vegetation indices often used in remote sensing studies of natural and agricultural vegetation. They suggest that the used algorithm for data processing is particularly suitable for airborne cropland monitoring and could be expanded to sites at farm or municipality scale. The results reported are from pilot study carried out on a plot located in one of the established polygons for experimental crop monitoring. In the mentioned research GIS database is established for supporting the experiments and modelling process. Recommendations on good farming practices for medium sized farms for monitoring stress conditions such as drought and overfertilizing are developed.
NASA Technical Reports Server (NTRS)
Carpenter, L. (Editor)
1980-01-01
Accomplishments and future plans are described for the following areas: (1) geology - geobotanical indicators and geopotential data; (2) modeling magnetic fields; (3) modeling the structure, composition, and evolution of the Earth's crust; (4) global and regional motions of the Earth's crust and earthquake occurrence; (5) modeling geopotential from satellite tracking data; (6) modeling the Earth's gravity field; (7) global Earth dynamics; (8) sea surface topography, ocean dynamics; and geophysical interpretation; (9) land cover and land use; (10) physical and remote sensing attributes important in detecting, measuring, and monitoring agricultural crops; (11) prelaunch studies using LANDSAT D; (12) the multispectral linear array; (13) the aircraft linear array pushbroom radiometer; and (14) the spaceborne laser ranging system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gelfand, Ilya; Shcherbak, Iurii; Millar, Neville
Differences in soil nitrous oxide (N 2O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N 2O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn–soybean–wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N 2O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N 2O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30–80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop 9 management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N 2O-N ha -1 yr -1 and were best predicted by IPCC Tier 1 and DEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil NOmore » $$-\\atop{3}$$ pools (r 2 = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N 2O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes.« less
NASA Astrophysics Data System (ADS)
Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian
Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.
Simulating the effects of climate and agricultural management practices on global crop yield
NASA Astrophysics Data System (ADS)
Deryng, D.; Sacks, W. J.; Barford, C. C.; Ramankutty, N.
2011-06-01
Climate change is expected to significantly impact global food production, and it is important to understand the potential geographic distribution of yield losses and the means to alleviate them. This study presents a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) that integrates, in addition to climate, the effect of planting dates and cultivar choices, irrigation, and fertilizer application on crop yield for maize, soybean, and spring wheat. PEGASUS combines carbon dynamics for crops with a surface energy and soil water balance model. It also benefits from the recent development of a suite of global data sets and analyses that serve as model inputs or as calibration data. These include data on crop planting and harvesting dates, crop-specific irrigated areas, a global analysis of yield gaps, and harvested area and yield of major crops. Model results for present-day climate and farm management compare reasonably well with global data. Simulated planting and harvesting dates are within the range of crop calendar observations in more than 75% of the total crop-harvested areas. Correlation of simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop-harvested area, of 0.81 for maize, 0.66 for soybean, and 0.45 for spring wheat. We found that changes in temperature and precipitation as predicted by global climate models for the 2050s lead to a global yield reduction if planting and harvesting dates remain unchanged. However, adapting planting dates and cultivar choices increases yield in temperate regions and avoids 7-18% of global losses.
Performance of the CELSS Antarctic Analog Project (CAAP) crop production system.
Bubenheim, D L; Schlick, G; Wilson, D; Bates, M
2003-01-01
Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515 g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.
Performance of the CELSS Antarctic Analog Project (CAAP) crop production system
NASA Astrophysics Data System (ADS)
Bubenheim, D. L.; Schlick, G.; Wilson, D.; Bates, M.
Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility.
Performance of the CELSS Antarctic Analog Project (CAAP) crop production system
NASA Technical Reports Server (NTRS)
Bubenheim, D. L.; Schlick, G.; Wilson, D.; Bates, M.
2003-01-01
Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515 g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.
Managing manure nutrients through multi-crop forage production.
Newton, G L; Bernard, J K; Hubbard, R K; Allison, J R; Lowrance, R R; Gascho, G J; Gates, R N; Vellidis, G
2003-06-01
Concentrated sources of dairy manure represent significant water pollution potential. The southern United States may be more vulnerable to water quality problems than some other regions because of climate, typical farm size, and cropping practices. Dairy manure can be an effective source of plant nutrients and large quantities of nutrients can be recycled through forage production, especially when multi-cropping systems are utilized. Linking forage production with manure utilization is an environmentally sound approach for addressing both of these problems. Review of two triple-crop systems revealed greater N and P recoveries for a corn silage-bermudagrass hay-rye haylage system, whereas forage yields and quality were greater for a corn silage-corn silage-rye haylage system, when manure was applied at rates to supply N. Nutrient uptake was lower than application during the autumn-winter period, and bermudagrass utilized more of the remaining excess than a second crop of corn silage. Economic comparison of these systems suggests that the added value of the two corn silage crop system was not enough to off-set its increased production cost. Therefore, the system that included bermudagrass demonstrated both environmental and economic advantages. Review of the N and P uptake and calculated crop value of various single, double, and triple crop forage systems indicated that the per hectare economic value as well as the N and P uptakes tended to follow DM yields, and grasses tended to out-perform broadleaf forages. Taken across all systems, systems that included bermudagrass tended to have some of the highest economic values and uptakes of N and P. Manure applied at rates to supply N results in application of excess P, and production will not supply adequate quantities of forage to meet the herd's needs. Systems that lower manure application and supply supplemental N to produce all necessary forage under manure application will likely be less economically attractive due to additional costs of moving manure further and, applying it to greater land areas, but will be environmentally necessary in most cases. Intensive forage systems can produce acceptable to high quality forage, protect the environment, and be economically attractive. The optimal manure-forage system will depend on the farm characteristics and specific local conditions. Buffers and nutrient sinks can protect streams and water bodies from migrating nutrients and should be included as a part of crop production systems.
USDA-ARS?s Scientific Manuscript database
Depleted soil quality, decreased water availability, and increased weed competition constrain spring wheat production in the northern Great Plains. Integrated crop management systems are necessary for improved crop productivity. We conducted a field experiment from 2004-2010 comparing productivity...
Soil Quality in a Pecan Agroforestry System is Improved with Intercropped Kura Clover
USDA-ARS?s Scientific Manuscript database
Intercropping alleys of agroforestry systems provides an income source until the tree crop produces harvestable yields. However, cultivation of annual crops decreases soil organic matter and increases soil erosion, especially on sloping landscapes. Perennial crops maintain a continuous soil cover, m...
Alternative cropping systems for sugarcane
USDA-ARS?s Scientific Manuscript database
Planting cover crops during the fallow period prior to planting sugarcane has the potential to influence not only the following sugarcane crop, but the economics of the production system as a whole. Research was conducted at the USDA, ARS, Sugarcane Research Unit at Houma, LA to determine the impac...