Prescription maps for spatially variable herbicide application in no-till corn

Weed maps for fields of no-till corn (Zea mays L.) were prepared from image analysis of digitized low-altitude aerial photographs. These weed maps were imported into a Geographic Information System (GIS) and divided into independent subunits for spatially variable herbicide prescription. A decision model was designed for pre-plant and post-emergence weed control recommendations. Each subunit of the field weed map was submitted to this decision model to determine the optimum herbicide mix and application rate. The resulting prescription maps would be used to control a field sprayer and to apply the appropriate herbicide combination to each weedy area. Results indicate that herbicide use would have been reduced by more than 40% with this approach. This demonstrates a means to significantly reduce herbicide usage in crop production without sacrificing weed control or crop yield.