The University of Georgia, Griffin Campus, Griffin, GA

May 12 - 21, 2008

Presented by the University of Georgia and the International Consortium for Agricultural Systems Applications (ICASA).

Rationale:

Today more than ever, increased food production depends on judicious use of resources. In addition, issues such as climate change, climate variability, soil carbon sequestration and the long-term impact on food security and environmental sustainability, have become important. Many weather, soil, genetic and management factors affect the way a crop will respond to irrigation, fertilizer and other management practices. Determining appropriate crop management strategies under these uncertainties has major economic and environmental implications. Computer simulation models of the soil/plant/atmosphere system can make a valuable contribution to both furthering our understanding of the processes that determine crop responses and predicting crop performance, resource use and environmental impacts for different environments and management scenarios. User-oriented simulation models greatly facilitate the task of optimizing crop growth and deriving recommendations concerning crop management. They can also be used to determine the potential impact of climate change on crop production and long-term soil carbon sequestration, or provide management scenarios for adapting to climate variability.

Program Goal and Objectives:

The overall goal of this training program is to familiarize participants with a comprehensive computer model for the simulation of crop growth and yield, soil and plant water, nutrient and carbon dynamics and their application to real work problems.

Specifically the program will focus on:

• Operation of the Windows-based Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 software. (www.icasa.net/dssat/)
• Description of the DSSAT-Cropping System Model, CSM and its modules, such as CROPGRO and CERES, and the science embedded in the models.
• Minimum data requirements and experimental data collection for systems simulation.
• Integration of crop simulation models with data base management and Geographical Information Systems.
• Application of the new DSSAT-CSM model to improve management of cropping systems.