Insects and plant diseases threaten fruit production, food security, and farm profitability, yet detecting these problems early is difficult and labor-intensive

The Department of Agriculture National Institute of Food and Agriculture awarded Utah State University $586,000 on January 1, 2026, under the Agriculture and Food Research Initiative (CFDA 10.310) to develop and test an automated pest scouting system for orchards. The project will engineer small aerial drones and ground-based robotic vehicles to move through orchards and collect close-up images inside tree canopies. Computer tools will analyze the collected imagery to identify pests and plant diseases and generate three-dimensional maps showing the spatial distribution of problems within trees and across orchards. The automated system aims to enable faster and more precise pest detection compared to labor-intensive manual scouting, thereby supporting targeted pest management, reducing unnecessary pesticide application, lowering production costs, and improving the long-term sustainability of fruit production. Performance occurs in Logan, Utah, with a period of performance extending from January 1, 2026, through December 31, 2029.

Most orchard pest scouting is done manually, requiring people to walk through fields and visually inspect trees, which is costly, time-consuming, and often misses pests hidden inside dense canopies. When pests are not detected early, growers may suffer yield losses or apply pesticides broadly as a precaution, increasing costs and environmental impacts. Improving how pests are detected is important not only for farmers, but also for consumers and communities that depend on reliable, affordable, and environmentally responsible food production. This project will develop and test an automated pest scouting system that uses small aerial drones and ground-based robotic vehicles to move through orchards and collect close-up images inside tree canopies. Computer tools will analyze these images to identify pests and plant diseases and create three-dimensional maps showing where problems occur within trees and across orchards. By providing faster and more precise pest information, this approach aims to support targeted pest management, reduce unnecessary pesticide use, lower production costs, and improve the long-term sustainability of fruit production systems, benefiting agriculture, the environment, and the broader public.