Estimation model of winter wheat disease based on meteorological factors and spectral information

Abstract Wheat scab (WS, Fusarium head blight), one of the most severe diseases of winter wheat in Yangtze-Huaihe river region, whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and achieve the purpose of reducing yield loss. In the present study, remote sensing monitoring on WS was conducted in 4 counties in Yangtze-Huaihe river region. Sensitive factors of WS were selected to establish the remote sensing estimation model of winter wheat scab index (WSI) based on interactions between spectral information and meteorological factors. The results showed that: 1) Correlations between the daily average temperature (DAT) and daily average relative humidity (DAH) at different time scales and WSI were significant. 2) There were positive linear correlations between winter wheat biomass, leaf area index (LAI), leaf chlorophyll content (LCC) and WSI. 3) NDVI (normalized difference vegetation index), RVI (ratio vegetation index) and DVI (difference vegetation index) which had a good correlation with LAI, biomass and LCC, respectively, and could be used to replace them in modeling. 4) The estimated values of the model were consistent with the measured values (RMSE = 5.3%, estimation accuracy = 90.46%). Estimation results showed that the model could efficiently estimate WS in Yangtze-Huaihe river region.