 This study used hyperspectral remote sensing data collected from unmanned aerial vehicles, UAVs, to identify characteristic bands for detecting rice false smut. The authors then optimized these bands to improve the accuracy of the model for predicting the presence of rice false smut. Finally, they identified two specific wavelength ranges, 698 to 800 nanometers and 974 to 997 nanometers, as being most sensitive to the presence of rice false smut. This article was authored by Yanxiang Wang, Min Fengxing, Hong Guozhang, and others.