Development of a precision sprayer for site-specific weed management

A machine-vision-system-guided precision sprayer was developed and tested. The long-term objectives of this project were to develop new technologies t o estimate weed density and size in real time, realize site-specific weed c ontrol, and effectively reduce herbicide application amounts for corn and s oybean fields. This research integrated a real-time machine-vision sensing system with an automatic herbicide sprayer to create an intelligent sensing and spraying system. Multiple video images were used to cover the target a rea. To increase the accuracy, each individual spray nozzle was controlled separately. Instead of trying to identify each individual plant in the fiel d, weed infestation zones (0.254 m x 0.34 m) were detected. The integrated system was tested to evaluate the effectiveness and performance under varyi ng field conditions. With the current system design, and using 0.5% weed co verage as the control zone threshold, herbicide savings of 48% could be rea lized.