Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology

Yellow rust is a worldwide disease that poses serious threat to the safety of wheat production. Numerous studies on near-surface hyperspectral remote sensing at leaf scale have achieved good results for monitoring. The next step monitor field scale, which great significance control. In our study, an unmanned aerial vehicle (UAV) equipped with sensor was used obtain images scale. Vegetation indices (VIs) and texture features (TFs) extracted from UAV-based their combination were establish partial least-squares regression (PLSR)-based monitoring models in different infection periods. addition, we resampled original 1.2 cm spatial resolution resolutions (3 cm, 5 7 10 15 20 cm) evaluate effect accuracy. findings showed VI-based model had highest accuracy (R2 = 0.75) mid-infection period. TF-based could be yellow obtained R2 mid- late-infection periods (0.65 0.82, respectively). VI-TF-based each period outperformed or models. negligible influence accuracy, but significantly influenced Furthermore, optimal using cm. provide reference accurate UAV images.