Location: Adaptive Cropping Systems Laboratory2013 Annual Report
1a. Objectives (from AD-416):
The overall objective is to refine and improve existing simulation models for corn and potato by developing new, and improving existing functional relationships between physiological processes and nutrients in the soil and plant tissues. Results of this research will be used to address existing knowledge gaps in the models. The modified models will be evaluated by testing simulated responses at plant component and whole plant levels. The specific sub-objectives are to improve simulation of the above- and below-ground potato and corn processes in the areas of: (1) water and nutrient stress effects on growth, development, morphology, and yield, and (2) response of root growth and activity (water and nutrient uptake) to soil nutrients (N, P and K), and water. The model and new components will be evaluated using experimental data. The potato and corn models, along with a rye cover crop model and existing models for soybean and corn, will then be used for assessment of the environmental consequences of agricultural management practices on carbon sequestration and nutrient balances. These practices include fertilizer applications, rotations, and cover crops.
1b. Approach (from AD-416):
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.
3. Progress Report:
Two SPAR (outdoor growth chambers–Soil Plant Atmosphere Research) experiments were conducted to evaluate response of two potato varieties to drought and elevated CO2 levels. The first year of a two year experiment in the SPAR chambers was carried out to assess and quantify the effects of high temperature on grain filling in corn. Collaborative work continued with University of Maryland and the ARS Genetic Improvement for Fruits and Vegetable Lab (GIFVL) on obtaining new potato varietal growth and yield data from field-sites. Greenhouse and field studies were undertaken to model response of a horticultural crop (strawberry) production in low-tunnels for the purpose of extending the growing season in MD in collaboration with ARS GIFVL. The USDA-ARS potato model SPUDSIM was modified to improve simulation of nitrogen and water-stress effects on stomatal conductance, photosynthesis, leaf expansion, and root growth. SPUDSIM was linked with a new diffusive root growth schema and simulations of above and below ground plant growth at different levels of water-stress were evaluated against previously collected experimental data. Geospatial databases for soils, climate, management, land-use and land-cover, and statistical yield data were completed for a 13-state region including New England and several Mid-Atlantic states. An automated tool called GAMCAF (Geospatial Agricultural Management and Crop Assessment Framework) was developed to link geospatial data with USDA-ARS crop models for corn and potato. Baseline production, using current land-use data, was simulated for potato and corn across the entire region and limitations to production including water management, planting dates, and biophysical factors (e.g. soil characteristics, climate) were evaluated. We collaborated with U.S. and international simulation modeling groups to compare simulations among different maize models. The study investigated the comparative simulated responses of maize to CO2, temperature, and drought using 30 years of weather data. Further details are in the annual report for the sibling project 1245-61660-006-10S. The maize model was also tested against data from a drought experiment in Colorado with four years of data and showed a realistic response to water stress without calibration. This work was done with collaboration from ARS scientists in Ft. Collins, CO. Two experiments were conducted in indoor environmental growth chambers to evaluate the interactive effect of phosphorus and CO2 on soybean growth and physiology. A third controlled environment study is in progress to study soybean response to potassium nutrition under current and projected CO2 concentrations. Further details can be found in the sibling report 1245-61660-006-03S. A one-year project funded by the NRCS (Natural Resources Conservation Service) was begun to develop cover crop scenarios to be used in the model APEX (Agricultural Productivity Extender). The objective is to assess cover crop impacts on nitrogen movement to ground and surface waters in the Chesapeake Bay watershed. This work is in collaboration with the Environmental Management & Byproduct Utilization Lab.
Resop, J.P., Fleisher, D.H., Wang, Q., Timlin, D.J., Reddy, V. 2012. Combining explanatory crop models with geospatial data for regional analyses of crop yield using field-scale modeling units. Computers and Electronics in Agriculture. 89(1):51-61.