Site-specific modeling of corn yield in the SE coastal plain

When site-specific agriculture became technologically feasible, existing cr op models made computer simulation a natural choice for predicting yield un der various combinations of soil, weather, and management. However, modelin g for site-specific farming may require both greater accuracy and sensitivi ty to more parameters than current models allow. The objective of this pape r was to evaluate the DSSAT V3.5 corn model, CERES-Maize, for sensitivity t o parameters important to site-specific farming. The model was unexpectedly insensitive to inputs for soil type, depth to clay, nitrogen, and plant po pulation, suggesting areas for attention. Although it was appropriately sen sitive to rainfall, indicating sensitivity to soil water content is general ly correct, there are known problems with the curve number procedure that c alculates runoff. The runoff routine needs improvement, and a separate rout ine may be needed to accommodate within-field redistribution of runoff. The model also responded to maximum air temperature, but since crop temperatur e varies more than air temperature, perhaps crop temperature should be calc ulated from air temperature and water stress. Model. accuracy issues aside, accommodating spatial inputs and model runs requires enhanced interfaces. These and other suggested enhancements to the model would improve its appli cability for site-specific agriculture. (C) 2000 Published by Elsevier Scie nce Ltd. All rights reserved.