Our group has received USDA funding over the years to deploy UAV-based hyperspectral imaging to enhance the detection and management of wheat diseases like bacterial leaf streak (BLS), leaf rust, stem rust, and fusarium head blight (FHB). The project has provided fundamental insights into disease progressions by incorporating historical data and conducting drone missions across several nurseries in Kansas and Minnesota (Rosemount, Crookston, and Saint Paul), which has provided strategies and patterns for effective management of these diseases. This corresponds to an increase in the frequency of data collection by 67% between 2023 and 2024, a commitment of the project to strong temporal-spatial coverage. The study identifies critical spectral regions that are highly essential in detecting disease-induced physiological changes. The application of advanced machine learning techniques and the use of multi-year datasets in this research yield high-accuracy disease quantification that can enable early intervention.
These historical analyses, together with the advanced imaging, help breeders and researchers find, advance, and further develop disease-resistant wheat varieties that will serve to push the boundaries of sustainable agriculture. The integration of UAV imaging with satellite data will close the scale gap between localized, high-resolution assessments and broader regional-scale monitoring. This is a scalable, multi-year framework that remodels precision agriculture, optimizes resource allocation, enhances disease resilience, and secures future food production systems.
