Computer Simulation of Agricultural Systems: Challenges and Opportunities

Abstract

Agriculture plays a critical role in our daily life as it provides food for human consumption, feed for livestock and animals, fiber for clothing, and biofuel for energy. At the same time agriculture is the main livelihood for small-holder farmers in developing countries, while in the US the food and farming industry contributes over $1.0 trillion to the gross domestic product. Predicting yield of crops is challenging, as it is affected by plant genetics, local weather and soil conditions, crop management, and pests, diseases, and weeds. However, over the past 50 years sophisticated computer models have been developed that can simulate crop growth and development, and the dynamic interactions of the soil and plant water, nutrient, and carbon balance. The crop models integrate the state-of-the-art of science across multiple disciplines and can be used for both ex-ante and ex-post analysis to evaluate alternate input scenarios. The models have been applied at different temporal and spatial scales, ranging from gene-based modeling, precision agriculture, in-season yield forecasting, soil carbon sequestration, and climate change impact assessment and adaptation for food and nutrition security. This seminar will provide a brief introduction to crop modeling and an overview of some case studies for real-world applications. With access to agricultural and environmental data rapidly increasing and the need for understanding and interpreting big data, it is expected that in the near future dynamic computer simulation models will be an integral component of actionable information for decision makers.

Bio:
Gerrit Hoogenboom has over 30 years of experience in the development and application of dynamic crop simulation models and decision support systems.  He currently coordinates the development of the Decision Support System for Agrotechnology Transfer (DSSAT), a crop modeling system that is being used world-wide by many scientists and others interested in systems analysis and decision support. Applications include gene-based modeling and cultivar selection, climate variability and climate change, water resources management, biofuel, economic and environmental sustainability, and food and nutrition security.