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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Research Project #428181

Research Project: Development and Application of Mechanistic Process-Driven Crop Models for Assessing Effects and Adapting Agriculture to Climate Changes

Location: Adaptive Cropping Systems Laboratory

2017 Annual Report

Objective 1: Characterize responses of potato and soybean to the interacting effects of temperature and CO2. Objective 2: Improve mechanistic models for corn, potato, cotton and soybean to better account for growth and development responses to environment, genotype, and nutrient factors, and enable simulations of multi-year cropping rotations. Objective 3: Estimate the sensitivity of regional food production to climate change and contribute to international model intercomparison efforts.

Mechanistic models for soybean (GLYCIM), cotton (GOSSYM), corn (MAIZSIM), and potato (SPUDSIM), have been developed in previous projects by this group. The proposed research will broaden the capabilities of the corn and potato models by utilizing data from experiments carried out in unique, state-of-the-art sun-lit growth chambers and field plots. Short and long term experiments will be employed to test hypotheses and develop algorithms for plant processes to be used in the computer models. Data collected by collaborators will be used to test and evaluate the models. A simple Rye model will be developed to simulate a cover crop during the fall-winter season. A computer graphical user interface will be developed using components from the existing software program, GUICS, to allow a user to simulate long term crop rotations over multiple growing seasons. Advanced data management capabilities will be added to the interface to help with interpretation and management of input and output data. Tools for weather generation and estimation of soil hydraulic properties will be added to the interface to provide a wide range of environmental conditions for assessment. All crop models will be used within the new interface to assess the environmental and economic impacts of climate change on carbon sequestration, and nitrogen and water balances for relevant production systems.

Progress Report
The research efforts summarized here represent the second year of a three year bridging project set to terminate on August 1, 2018. Substantial progress was made on all three research objectives, all of which are encompassed within National Program 216, Agricultural Systems Competitiveness and Sustainability. Experimental work was conducted in controlled environment facilities to study response of economically important crops to genetic, environment, and management factors. Experiments addressed knowledge gaps in the literature and provided information for building and improving crop models. Maize studies were conducted to evaluate environmental factors on growth and development. Responses to evaporative demand, as defined by vapor pressure deficit (VPD), were of particular interest because of water resource limitations facing agricultural production. Unique sets of data regarding maize growth and leaf area expansion rates were collected. These responses were associated with differences in plant physiological processes and gene expression. This effort addresses components of Objective 1. Experimental work was also conducted with soybean, cotton, and potato. Soybean experiments tested environment x management effects on seed yield, specifically the interactions with potassium or phosphorus deficiency under ambient and elevated atmospheric carbon dioxide concentrations (CO2) as well as high and low air temperatures. Cotton and potato studies were designed to evaluate genetic x environment factors during production. The cotton work identified nine varieties that exhibited reduced transpiration rates during soil drying periods at mid-day. Potato studies evaluated the yield and growth responses of two previously untested cultivars with respect to temperature and elevated CO2. Data addresses components of Objective 1 and will feed into efforts in Objective 2. Methods to facilitate simulations with crop modeling programs were developed and utilized in food security and model inter-comparison studies. The number of input files needed to run the models was reduced nearly 50% by consolidating and eliminating redundant input variables. Computer scripts now automate the process of converting experimental data into the formats needed to run and operate the SPUDSIM, MAIZSIM, and 2DSOIL crop and soil models. Soil nitrogen dynamics and methods to account for water runoff were implemented in the 2DSOIL program and allow for more realistic assessment of agricultural resource use. The efforts address the research outlined in Objective 2. Adaptive Cropping Systems Laboratory (ACSL) continues to provide leadership to the international model inter-comparison efforts for potato and maize within the Agricultural Model Inter-Comparison and Improvement Project (AgMIP). The first phase of research was successfully completed and evaluated the differences among multiple models for the same crop using common datasets. A new international group has been assembled and is working on additional comparison studies with potato. Maize model responses to water and CO2 from a two-year free air carbon dioxide enrichment experiment were also evaluated involving 21 crop models. Models reproduced the absence of yield response to elevated CO2 under well-watered conditions, and the impact of water deficit at ambient CO2 concentration. However under water deficit in one of the two years, the models captured only thirty percent of the carbon dioxide effect on grain yield. Models with a more detailed description of leaf processes performed better. The need for model improvement with respect to simulating water use and its impact on soil water status during the kernel-set phase were recommended. Efforts have been published for both crops and directly address Objective 3. Computer simulation models of plant and soil processes are useful research and assessment tools and documentation standards were developed for the software. These models are scientific products and represent long periods of research and development. They are also subject to change as our scientific knowledge of physical systems improves. ARS scientists at Beltsville, Maryland and Fort Collins, Colorado developed guidelines to document computer code that will insure that the code can be reused by developers and other users, therefore insuring that the knowledge embedded in the model will be more readily available. This documentation is useful to scientists and other developers who write or use computer code in their work and addresses Objective 2. Collaborative efforts among ARS scientists at the behest of the National Program Leader to evaluate strawberry production systems in the Mid-Atlantic region continue with very encouraging results. Higher yields, extended growing seasons, disease suppression, and higher berry quality was achieved via the use of low-tunnel covers above raised-bed systems. Micro-climate data was acquired from these studies and used to develop mathematical models to improve management and design of these systems. These efforts address Objectives 1 and 3. Geospatial modeling simulations in the Northeastern seaboard region were completed. Prior research used crop models for potato and maize to simulate yield, water and nitrogen use at the sub-county scale to explore potential production and land-use scenarios. We incorporated a wheat model into the simulation platform and modelled potential production of winter wheat. A manuscript was submitted regarding land use under future climate conditions using these data. These efforts address Objective 3. A new hydrologic model was developed to predict water runoff from agricultural fields. There is a need for a simulation modeling framework that can utilize the explosion of hydrologic, remotely sensed and environmental data that are becoming more widely available. We developed a flexible and easily extendable hydrologic model called STORE DHM that can generate information on water runoff from agricultural fields from a rainstorm. The model can be easily modified to be used for more complex simulations of water dynamics as affected by rainfall and soil management. The model can be a useful tool for water resources managers and scientists and addresses Objective 2.

1. Leaf compounds in soybean help alleviate phosphorus stress. Soybean plants under phosphorus stress are negatively affected by high levels of sunlight. Leaf pigments like chlorophyll and carotenoids capture solar energy that is used for photosynthesis. ARS researchers at Beltsville, Maryland, showed that under phosphorus deficient management conditions, the leaf carotenoid content needed to maintain soybean photosynthetic capacity changes when exposed to high light at different plant phosphorus contents and atmospheric carbon dioxide concentrations. This knowledge is useful to researchers and breeders interested in improving the photosynthetic potential in crops under phosphorus-limited growing conditions.

2. Elevated atmospheric carbon dioxide concentration was more beneficial to soybean grown under low versus high temperature stress. There is an optimal range of temperatures above and below which soybean yields decline. Climate forecasts include increases in atmospheric carbon dioxide concentration (CO2) which may enhance crop growth. However, the extent of this enrichment depends on air temperature. Results of an experiment conducted at low, optimum, and high temperatures under different CO2 levels show that elevated CO2 compensated for some temperature stress effects on photosynthesis. Elevated CO2 also helped minimize seed yield loss, but only at the low temperature. Results are useful to growers and to the scientific community with respect to land-use planning for soybean under changing environmental conditions. These results also address regional and global food security concerns.

3. Higher strawberry yields in low-tunnel production systems may revitalize the Mid-Atlantic berry industry. Strawberry production in the Mid-Atlantic region is limited to a short 5-week harvest period during the season. The fresh berry market would benefit by adoption of repeat-fruiting cultivars, but improved production systems need to be developed. A collaborative research effort among scientists in Beltsville, Maryland, tested and evaluated low-tunnel raised-bed production systems. Results showed that repeat-fruiting cultivars could be successfully grown over several months. Yields and berry quality were higher under covered, versus non-covered, beds. Warmer temperatures (air, crown, and soil) which extended the growing season were the primary reason, but light quality was also better underneath the tunnels. The production system benefits breeders and growers by providing an environment suitable for generating economically viable berry yields over multiple months. The data is also used for mathematical model development to improve design and management of these systems.

Review Publications
Singh, S.K., Reddy, V., Fleisher, D.H., Timlin, D.J. 2016. Relationship between photosynthetic pigments and chlorophyll fluorescence in soybean under varying phosphorus nutrition at ambient and elevated CO2. Photosynthetica. 55:421-433.
Singh, S.K., Barnaby, J.Y., Reddy, V., Sicher Jr, R.C. 2016. Varying response of the concentration and content of soybean seed mineral elements, carbohydrates, organic acids, amino acids, protein, and oil to phosphorus starvation and CO2 enrichment. Frontiers in Plant Science. 7(1967):1-13. doi: 10.3389/fpls.2016-01967.
Xu, G., Singh, S., Reddy, V., Barnaby, J.Y., Sicher Jr, R.C., Li, T. 2016. Soybean grown under elevated CO2 benefits the most at low temperature than at high temperature stress: varying response of photosynthetic limitations, leaf metabolites, growth, and seed yield. Journal of Plant Physiology. 205:20-32. doi: 10.1016j.jplph.2016.08.003.
Xu, G., Singh, S., Barnaby, J.Y., Buyer, J.S., Reddy, V., Sicher Jr, R.C. 2016. Effects of growth temperature and carbon dioxide enrichment on soybean seed components at different stages of development. Plant Physiology and Biochemistry. 108: 313-322.
Timlin, D.J., David, O., Green, T.R., Fleisher, D.H., Kim, S., Ahuja, L.R. 2016. Proposed standards for peer-reviewed publication of computer code. Agronomy Journal. 108:1-5. doi: 10.2134/agronj2015-0481
Fleisher, D.H., Condori, B., Quiroz, R., Alva, A.K., Asseng, S., Barreda, C., Bindi, M., Boote, K.J., Ferrise, R., Franke, A.C., Govindakrishnan, P.M., Harahagazwe, D., Hoogenboom, G., Kumar, S.N., Merante, P., Nendel, C., Olesen, J., Parker, P., Raes, D., Raymundo, R.M., Ruane, A.C., Stockle, C., Supit, I., Vanuytrecht, E., Wolf, J., Woli, P. 2016. A potato model intercomparison across varying climates and productivity levels. Global Change Biology. 23(3):1258-1281.
Durand, J., Delusca, K., Boote, K., Lizaso, J., Manderscheid, R., Weigel, H., Ruane, A., Rosenzweig, C., Jones, J., Ahuja, L.R., Anapalli, S.S., Basso, B., Baron, C., Bertuzzi, P., Biernath, C., Deryng, D., Ewert, F., Gaiser, T., Gayler, S., Heinlein, F., Kersebaum, K.C., Kim, S., Muller, C., Nendel, C., Olioso, A., Priesack, E., Villegas, J.R., Ripoche, D., Rotter, E.R., Seidel, S.I., Srivastava, A., Tao, F., Timlin, D.J., Twine, T., Wang, E., Webber, H., Zhao, Z. 2017. How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?. European Journal of Agronomy. DOI 10.1016/j.eja.2017.01.002. ISSN 116-0301.
Singh, S.K., Reddy, V. 2017. Potassium starvation limits soybean growth more than the photosynthetic processes across CO2 levels. Frontiers in Plant Science. 8:1-16.