The Role of Crop Systems Simulation in Agriculture and Environment

Authors: BOONE, K - University Of Florida; JONES, J - University Of Florida; HOOGENBOOM, G - University Of Georgia; White, Jeffrey

Submitted to: International Journal of Agricultural and Environmental Information Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/1/2009
Publication Date: 4/1/2010
Citation: Boone, K.J., Jones, J.W., Hoogenboom, G., White, J.W., 2010. The Role of Crop Systems Simulation in Agriculture and Environment. International Journal of Agricultural and Environmental Information Systems 1, 41-54.

Interpretive Summary: A recurring problem in agriculture is how to predict the complex and interacting effects of weather, soils, crop management and other factors for a given farm field. Over the past 30 to 40 years, computer-based simulations of crop systems has evolved from a neophyte science into a robust and increasingly accepted science that is widely applied where predictions of crop performance are required. The simulators contain mathematical equations describing basic flow and conversion processes of carbon, water, and nitrogen in the crop, which thus predict plant growth and variation in water and nutrient levels. This paper reviews how crop systems simulation can serve important future roles in agriculture and environmental management. The most important roles are in five areas: 1) Basic research synthesis and integration, where simulations can summarize our understanding of physiology, genetics, soil characteristics, management, and weather effects, 2) Strategic tools for research planning/policy such as to evaluate strategies for plant breeding or deployment of novel biofuel crops, 3) Applications for management purposes, where crop systems simulations are used to evaluate impacts of climate variability on production, consequences of weather and nutrient management on water use and nutrient use, consequences on economics, water use, and nutrient leaching, 4) Real-time support for decisions on crop management (irrigation, N fertilization, sowing date, projected harvest, yield forecast, pest management), and 5) Education, both in class rooms and extension contexts, to explain how crop systems function and are managed. There is good potential to link crop models to molecular genetics, in effect, modeling from knowledge of genes of different cultivars to phenotypic performance in different environments. There are also continuing needs to improve the crop models for simulating root growth and nutrient uptake, coupling of diseases and pests, fully-coupled energy balance, and response to climate change. The review is especially intended to suggest promising lines of research for researchers who may previously been unaware of the use of crop systems simulation.

Technical Abstract: Over the past 30 to 40 years, simulation of crop systems has advanced from a neophyte science with inadequate computing power into a robust and increasingly accepted science supported by improved software, languages, development tools, and computer capabilities. Crop system simulators contain mathematical equations describing basic flow and conversion processes of carbon, water, and nitrogen that are integrated daily or hourly by the computer program to predict time courses of crop growth, nutrient uptake, and water use, as well as to predict final yield and other plant traits. This paper outlines our vision of how crop systems simulation can serve important future roles in agriculture and environmental management and to prioritize research to better support these roles. The most important roles and uses of crop systems simulation are in five areas: 1) Basic research synthesis and integration, where simulation is used to integrate and synthesize our understanding of physiology, genetics, soil characteristics, management, and weather effects, 2) Strategic tools for research planning/policy such as to evaluate strategies and consequences of genetic improvement, management of resources, or decisions to produce biofuel crops rather than food crops, 3) Applications for management purposes, where simulations are used to evaluate impacts of climate variability on production or consequences of nutrient management on water and nutrient use, 4) Real time decision support to assist in management decisions (irrigation, N fertilization, sowing date, projected harvest, yield forecast, pest management), and 5) Education, both in classroom and extension contexts, to explain how crop systems function and are managed. There is good potential to link crop models to molecular genetics, in effect, modeling from knowledge of genes of different cultivars to phenotypic performance in different environments. There are also continuing needs to improve the crop models for simulating root growth and nutrient uptake, coupling of diseases and pests, fully-coupled energy balance, and response to climate change.