1a.Objectives (from AD-416)
The overall objective of this project is to develop integrated crop simulators for resource management. The specific objectives include the development of modular simulators for major U.S. crops, and evaluation of environmental impacts of global climate change, water quality issues, sustainable agriculture, precision farming, etc. Research areas where knowledge gaps about plant and soil processes limit the accuracy of model predictions.

1b.Approach (from AD-416)
Develop a suite of process level crop simulation models for wheat, potatoes, corn, rice, peanut, cotton, and soybean; and integrate these with models for weeds, diseases, and insects. There are many crop models available; however to date there is no comprehensive crop management system developed for major crops grown in the United States. The selected crops are important to the U.S. economy; in addition they represent a wide range of plant types: C3 and C4, grain root and fiber, legume, and non-legume. From such a suite of models it should be possible to assemble modules capable of simulating many other crops with appropriate parameter changes and additional rate equations to fill up the gaps. The existing models for weeds, diseases, and insects will be further developed and integrated with crop models. In instances where mechanistic models to describe some processes do not exist, or are inadequate, new models of those processes will be developed. Where suitable data are not available, we will conduct experiments to generate needed data.

3.Progress Report
This project was replaced by 1275-61660-005-00D and 1275-61660-006-00D; see these projects for additional progress related to this project

Over the five year period of this project we have conducted growth chamber and field experiments to quantify the interacting effects of CO2, temperature, water stress, and nitrogen application on growth, development, and yield of corn and potato. Using these research results we have developed algorithms and sub-models for photosynthesis, nitrogen uptake from soil, light interception, leaf expansion, carbon partitioning, development rates, and yield for corn and potato. The effects of water stress and CO2 concentration were also included in the sub-models. These sub-models have been combined with a comprehensive two-dimensional model of soil processes (2DSOIL) to complete new mechanistic models of corn and potato. The effects of environmental variables like light, temperature, CO2, etc on the growth, development, and quality of several other economically important crops were also studied. These studies included quantifying the effects of nitrogen and CO2 on cotton, determining optimum growth temperatures for eastern gamma grass, the interactive effects of CO2, temperature, and UV-B radiation on soybean pollen germination, and nitrogen effects on sorghum growth and development. The effects of future climate change (increased CO2 and temperature) and the interaction with nitrogen on cotton production was assessed using the simulation model GOSSYM. Data from farmers' fields, University of Maryland at Wye Research Center, and Beltsville Agricultural Research Center research plots were collected to test and further parameterize the models. Evaluation of corn model simulations versus independent growth chamber data indicates that the model behaves correctly. Data from experiments with nitrogen and water in potato in Washington State are being archived to calibrate and validate the potato model for several cultivars. We further conducted research with respect to operation of the growth chambers. These studies included quantification of light interception in the growth chambers, evaluation of systems to measure water uptake and transpiration, measurement of leakage rates of CO2, and evaluation of the sources of variability in plant data collected from growth chambers. The goal of this work is to provide strong experimental evidence to support the validity of research results from outdoor, sun-lit growth chambers. We also carried out field studies to quantify the spatial variability of potato yield to nitrogen application. Other studies included modification of the interface for our crop models (GUICS–Graphical User Interface for Crop Simulators) to be able to calculate soil hydraulic properties from soil texture, carry out multiyear simulations and addition of the new simulation models to the interface.