Modification of CERES-Wheat to accept leaf area index as an input variable

CERES-Wheat is one in a family of crop simulation models used by the Decision Support System for Agrotechnology Transfer (DSSAT). Efforts have been devoted to integrating the DSSAT models with Geographic Information Systems (GIS) to account for spatial variation in soils and climate; however, validation and fine tuning of the models in a GIS environment is a difficult task. The relationship between multispectral data and plant characteristics such as green leaf area index (LAI) has been demonstrated; therefore, multispectral images have the potential to enhance the spatial predictive capability of existing growth models. CERES-Wheat was modified to accept observed LAI at defined times during the season. Initial results indicate that the proposed procedures are only effective when the growth stages of the model are properly predicted and leaf area index observations are available soon after the completion of leaf development. Future efforts will focus on an iterative approach to adjusting the model's parameters.