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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

2018 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 documents progress for year three of the bridge project (8042-61660-009-00D) "Development and Application of Mechanistic Process-Driven Crop Models for Assessing Effects and Adapting Agriculture to Climate Changes." This project is encompassed within National Program 216, Agricultural Systems Competitiveness and Sustainability. During this term a new 5-year project plan was written and submitted for peer-review in addition to the research summarized below. A North Carolina State University graduate student was embedded with ACSL for a 60-day period and worked on analysis of soil water content data collected as part of a collaborative project with NC State and an additional USDA-ARS Laboratory. Five visiting scholars from international locations have also participated with our experimental and modeling programs. Six experiments linked to Objective 1 were conducted on corn, potato, soybean, and strawberry. In addition to providing data used to drive the modeling and decision-support methods in Objectives 2 and 3, these studies investigated linkages between multiple crop production factors and the associated physiological and metabolic pathway components that lead to increased water-use and nitrogen-use efficiencies. Results from these studies can facilitate grower decisions with regards to selecting ideal cultivars, development of fertilizer management guidelines, and identify traits for breeders to improve nitrogen use efficiency and heat tolerance. These studies are therefore directly relevant to the USDA-ARS Grand Challenge focused on increasing food availability and lowering environmental impacts. Corn experiments evaluated the extent to which drier atmospheric conditions and soil water contents influence growth rates and the expression of certain biochemical signals in response to drought. Drought tolerance mechanisms were identified that could be used as traits for crop breeders, and for testing and improving agricultural decision support models. A separate experiment with high air temperatures and varying nitrogen fertilizer showed that nitrogen uptake, growth rate, and yield were related to genetic regulators that influence metabolic activity and facilitate nitrogen movement. For potato, differences among cultivars in response to warmer temperatures and higher atmospheric carbon dioxide (CO2) levels were observed. Variation in carbon allocation between above- and below-ground organs were to cultivar maturity class and may be important when identifying cultivars best-suited for different production locations. In soybean, interactions among air temperature and CO2 influenced the extent to which phosphorus deficiency affected yields. The timing during the crop growth cycle (e.g. vegetative or reproductive stages) in which changes in climate factors or fertilizer deficiencies occur was critical. These results are useful to researchers and farmers to understand the dynamics of phosphorus fertilization in soybean and climate interactions. Two publications were delivered from this research. Collaborative efforts with strawberry continued at the behest of the National Program Leader. A previously developed mathematical model provided growers with optimal temperature thresholds for repeat-fruiting strawberry yields in Mid-Atlantic conditions when using raised-bed systems covered by plastic tunnels. Additional field data was collected to validate the model and identify spectral properties of plastic films that can be used to optimize the thermal environment. Substantial progress was made in addressing model knowledge gaps and user interface development in Objective 2. Code to simulate water runoff and ponding in 2DSOIL was added and tested against observed data. A greenhouse study was carried out to obtain leaf size distribution data in corn as a function of drought. The information will be incorporated into the MAIZSIM model. Data from an experiment investigating nitrogen effects on leaf growth and kernel number/weight were also analyzed and input files for MAIZSIM developed. The data are being used to improve simulation of corn yield and development under nitrogen stress. The SPUDSIM potato model was evaluated under historical and future production conditions in Maine and Maryland utilizing field data collected in 2011 and 2012. Initial results indicated the model can be utilized with confidence at different production locations with minimal calibration data. Work was also conducted in consultation with stakeholders for rice growers in the U.S. Southeast regarding the potential for a ratoon crop. Ratooning can increase annual yields with just a modest addition of resources. A manuscript was submitted on this topic. Substantial progress was made towards the development of a new user-friendly decision support system using ARS crop and soil models. The interface will facilitate studies of crop production anywhere in the world, including evaluation of cover cropping rotations, resource use-efficiencies, and soil health in U.S. production systems. In Objective 3, a series of research projects were either completed or initiated. International AgMIP projects involving inter-comparisons of corn and potato models were completed ahead of schedule. Nitrogen dynamics, ET and water balances (including run-off) were tested in this project. The results improved confidence in the predictions of crop models for food security studies and identified areas of needed improvement. We continue to initiate and lead potato and corn AgMIP projects to further identify the stability of model predictions at multiple production locations. A separate project on the potential of using land re-distribution approaches for minimizing yield losses under short- and long-term climate changes within the U.S. northeastern seaboard region was completed. A manuscript was submitted.

1. Decision support developed to predict and minimize impact of rain events. The urbanization of agricultural and forested lands can result in increased flooding incidents in developed areas. Assessments of the status of current storm water systems need to be done to ensure that existing infrastructure can keep up with hydrologic changes. ARS researchers at Beltsville, Maryland, used models and weather data to determine peak runoff of precipitation to streams in the Chesapeake Bay watershed and the area of the watershed contributing to flow. The results showed that as urbanization progresses, peak flows of floods increase. Changes in precipitation variability and amounts over time due to climate change also contribute to higher peak floods and a greater incidence in flooding. This research is useful to urban and rural planners and research scientists.

2. Sampling for early Phosphorus and Potassium is best for soybean. Rapid/early detection of nutrient stress in soybean is an important component of in-season crop management to minimize crop losses. The traditional approach is to sample upper leaves to determine nutrient status, but the question of when the optimal time to sample the leaves during the crop life cycle still needs to be identified. We found that relationships between nutrient status (phosphorus and potassium levels) and seed yield were best established when leaves were sampled earlier in the season (within 4 to 5 weeks after planting). These relationships were less significant if leaf samples were taken later in the growing season, likely due to remobilization of leaf nutrients as the plant ages. The results can improve management of fertilizers in the field and lend towards more efficient sampling dates.

Review Publications
Condori, B., Fleisher, D.H., Lewers, K.S. 2017. Relationship of strawberry yield factors with microclimate under open and covered raised-bed production. Transactions of the ASABE. 60(5):511-1525.
Clancy, K., Bonanno, A., Canning, P., Cleary, R., Conrad, Z., Fleisher, D.H., Gomez, M., Griffin, T., Lee, R., Kane, D., Palmer, A., Park, K., Peters, C., Tichenor, N. 2017. Using a market basket to explore regional food systems. Journal of Agriculture, Food Systems, and Community Development. 7(4):163-178.
Kang, K., Lee, J.H., Chun, J.A., Timlin, D.J. 2018. Impact of altered land use on urban hydrology and strategic management practices on flooding problems. Russian Meteorology and Hydrology. 43:197-202.
Singh, S.K., Reddy, V., Sicher Jr, R.C. 2018. Seasonal critical concentration and relationships of uppermost fully expanded leaf phosphorus and potassium status with biomass and yield traits at maturity in soybean. Journal of Plant Nutrition and Soil Science.
Wang, Q., Chun, J.A., Fleisher, D.H., Reddy, V., Timlin, D.J., Resop, J. 2017. Parameter estimation of the Farquhar-von Caemmerer-Berry biochemical model from photosynthetic carbon dioxide response curves. Sustainability. 9:1288.
Lewers, K.S., Fleisher, D.H., Daughtry, C.S. 2017. Low tunnels as a strawberry breeding tool and season-extending production system. International Journal of Fruit Science.
Singh, S., Reddy, V. 2018. Co-regulation of photosynthetic processes under potassium deficiency across CO2 levels in soybean: mechanisms of limitations and adaptations. Photosynthesis Research.
Timlin, D.J., Naidu, T.C., Fleisher, D.H., Reddy, V. 2017. Quantitative effects of phosphorus on maize canopy photosynthesis and biomass. Crop Science.