Tractor-Based Real-Time System for Drift Reduction and Deposition Prediction

Precision agriculture based upon high resolution GPS-based systems has had a dramatic impact on the efficiency of crop production in the United States, but comes with the disadvantage of being unable to estimate spray coverage and drift, or make allowances for changes in weather conditions and potentially undesirable ground patterning. The proposed effort seeks to mitigate this disadvantage by developing a real-time dynamic onboard system for the prediction and prevention of undesirable spray drift during ground sprayer operation, through the modification of a predictive model developed by the USDA Forest Service.Combining the spatial accuracy of precision agriculture through onboard or local GPS systems and the inclusion of weather data, with the ability to directly predict, control, and log spray application and drift in real-time using advanced numerical prediction capabilities, would have a dramatic impact on crop production, crop protection, and worker/public safety. Completion of the proposed effort will significantly enhance the ground application of agricultural pesticides and herbicides to crops, ensuring higher mortality of the undesirable insect or crop infestation while reducing off-target drift and the potential chemical exposure that such drift may bring to the agricultural environment, operators, and workers/bystanders.There are an estimated 4.5 million agricultural tractors in the U.S. If only 10% of them are used in crop management and therefore amenable to real-time dynamics onboard operations, the potential market is significant.