From genome to crop: integration through simulation modeling

Crop models use mathematical equations to simulate growth, development and yield as a function of weather, soil conditions and crop management. Such models integrate scientific knowledge from diverse agronomic disciplines, ranging from plant breeding to soil physics. Most crop models use one or more cultivar-specific parameters to identify differences in performance among cultivars. Until recently, however, there was little relation between cultivar-specific parameters and genotypes. The GeneGro model simulates the impact of seven genes on physiological processes in common bean (Phaseolus vulgaris L.), specifying cultivar differences through the presence or absence of the seven genes. The model was based on the bean model BEANGRO. GeneGro has now been incorporated into the cropping system model (CSM), which can simulate growth and development for more than 20 different crops, although the CSM-GeneGro version is currently implemented only for common bean and soybean [Glycine max (L.) Merr.]. Gene-based models can provide a well-structured linkage between functional genomics and crop physiology, especially as more genes are identified and their functions are clarified. Incorporating genetic information strengthens underlying physiological assumptions of the model, improving its utility for research in crop improvement, crop management, global change, and other fields. We first briefly review issues related to development of gene-based models, ranging from modeling approaches to data management. The CSM-GeneGro model is then used to show how specific genes can simulate both yield levels and yield variability for three locations in the USA. The model is also used to examine how single genes can affect crop response to global change. Gene-based modeling approaches could significantly enhance our ability to predict how global change will impact agricultural production, but modelers and physiologists will have to be proactive in accessing information and tools being developed in the plant genomics community. (C) 2004 Elsevier B.V. All rights reserved.