Wednesday, November 15, 2006 - 8:00 AM

Crop Simulation Models and Decision Support Systems.

Gerrit Hoogenboom1, Upendra Singh2, Paul Wilkens3, Jeffrey W. White4, James W. Jones5, Kenneth J. Boote5, and L.T. Hunt6. (1) Univ of Georgia, 1109 Experiment St, Dept Bio & Ag Eng, Griffin, GA 30223-1797, (2) IFDC, PO Box 2040, Muscle Shoals, AL 35662, (3) Intl. Fertilizer Development Ctr., IFDC, PO Box 2040, Muscle Shoals, AL 35662, (4) US Arid Land Agricultural Research Center, 21881 N Cardon Lane, Maricopa, AZ 85239, (5) Univ of Florida, Ag and Biological Engineering Dept, PO Box 110570, Gainesville, FL 32611, (6) Univ of Guelph, Dept of Plant Agronomy, Guelph, ON N1G 2w1, Canada

The first computer simulation models for agricultural systems were developed in the 1970s. These early models simulated potential production for major crops as a function of weather conditions, especially temperature and solar radiation. At a later stage, the water component was added to be able to simulate the soil and plant water balance and the impact of drought stress on growth, development, and yield. This required adding a detailed description of the physical characteristics of the soil surface and individual soil horizons as input to the models, as well as rainfall and irrigation. Further complexity was added by including the dynamic simulation of the soil and plant nitrogen balance. This, again, required additional soil inputs as well as a detailed description of the composition of the various plant components. The main soil processes that are simulated include mineralization and immobilization of crop residue and soil organic matter, nitrification and denitrification, and nitrate and urea movement. The plant processes include nitrogen fixation for grain legumes and nitrogen uptake, nitrogen mobilization and senescence. Many crop simulation models also include genetic parameters and coefficients that correspond to the unique characteristics of each crop and cultivar. All processes are simulated at a daily time step and provide a true integration of the effect of weather and soil conditions and crop management on plant genetics, expressed through plant growth and development. Many models have slowly moved from research applications to decision support tools that can be used for seasonal and tactical decision-making, including the timing and amount of various management strategies, such as irrigation and fertilizer management. With the advancement in automated weather recording and communication and information technologies, these models will be new tools that can be used by decision makers, including growers and producers, to improve and increase crop yield and crop quality.