Monitoring of Wheat Scab Using the Specific Spectral Index from ASD Hyperspectral Dataset

Abstract

It is highly important to accurately monitor wheat scab and provide technical guidance for the crop pests and diseases. In this study, relevant analysis was performed among spectral reflectance, first-derivate data, and the disease severity data through ASD hyperspectral data. Two sensitive spectral wavelength ranges of 450-488 nm and 500-540 nm were selected. Then, a new wheat scab index (WSI) consisting of the two bands was proposed. The inversion models of the scab severities were comparatively built by unitary linear regression and multiple stepwise regression techniques. The results showed that the WSI had a significant linear relationship with severity of disease compared with other commonly used spectral indices. The fitting R2, testing R2, and RMSE were 0.73, 0.70, and 13.41, respectively. The multiple stepwise regression model established using the WSI, SDg/SDb, NBNDVI, and SDg as independent variables was better than the single-variable model. Our results suggest that WSI can be used to provide scientific guidance for monitoring and precise management of wheat scab disease.