Location: Adaptive Cropping Systems Laboratory
Project Number: 8042-61660-007-00-D
Project Type: In-House Appropriated
Start Date: Mar 1, 2014
End Date: Apr 27, 2015
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 especially with respect to carbon, water, and temperature interactions. The modified models will be evaluated by testing simulated responses at plant component and whole plant levels. 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. The specific sub-objectives are 1) to improve simulation of the above- and below-ground potato and corn processes in the areas of: (a) water and nutrient stress effects on growth, development, morphology, and yield, (b) response of root growth and activity (water and nutrient uptake) to soil nutrients (N, P and K), and, c) evaluate the new model components using experimental data; and, 2) intercompare crop and economic models and foster improvements in these models to increase their capability to utilize data from climate scenarios as part of AgMIP.
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.