Spatial validation of crop models for precision agriculture

Spatial measurements of yield using technological advances like on-the-go y ield monitoring systems have clearly shown large within-field variability i n crop yields suggesting that field yields could be increased or cost decre ased by varying management over space. This study evaluated the utility of the CROPGRO-Soybean simulation model and remote sensing in the interpretati on of a soybean yield map. CROPGRO was executed on areas within the field d efined as reasonably uniform by a Normalized Difference Vegetative Index (N DVI) analysis, The model was able to closely predict the crop yield variabi lity measured within the field when the measured soil type and plant popula tion were used as model inputs, Remote sensing was useful ill finding spati al patterns across the field to target sampling and to provide spatial inpu ts for the model, Results of this study showed that a combination of crop m odel and remote sensing can identify management zones and causes for yield variability, which are prerequisites for zone-specific management prescript ions. (C) 2001 Elsevier Science Ltd. All rights reserved.