The University of Georgia
Griffin Campus, Griffin, Georgia

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Highlights and CSM/DSSAT
General Information
Registration and Contacts
Faculty and Co-Sponsors

May 20-25, 2013

Presented by a joint training program of the DSSAT Foundation, Washington State University, the University of Florida, the University of Georgia and International Fertilizer Development Center (IFDC).

• DSSAT Version 4.6 for Windows
  
• Receive the DSSAT Software and the book Understanding Options for Agricultural Production

For more information, download the brochure (pdf).

Rationale:
Today more than ever, increased crop production depends on judicious use of resources. In addition, issues such as climate change, climate variability, soil carbon sequestration, biofuels,long-term food security and environmental sustainability have become important issues. 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 change and 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  world problems.

Specifically the program will focus on:

• Operation of the Windows-based Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.6 software. (www.DSSAT.net)
  
• 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 DSSAT-CSM model to improve management of cropping systems.