Detection of Fusarium Head Blight in Wheat Using NDVI from Multispectral UAS Measurements and Its Correlation with DON Contamination

Fusarium head blight (FHB) is a serious fungal disease of wheat and other small cereal grains, significantly reducing grain yield and producing mycotoxins that affect food safety. There is a need for disease detection technologies to determine the right time to apply fungicides, as FHB infection begins before visible symptoms appear. Using multispectral remote sensing by an unmanned aircraft system (UAS), wheat plants were observed under field conditions infested with FHB and simultaneously protected with fungicides sprayed with four different types of nozzles, as well as corresponding control plots infested with FHB only. The results showed that the levels of deoxynivalenol (DON) differed significantly between the five treatments, indicating that the control had the highest DON concentration as no fungicide treatment was applied. This study revealed that the assessment of the normalized difference vegetation index (NDVI) after FHB infection could be useful for predicting DON accumulation in wheat, as a significant negative correlation between DON and NDVI values was measured 24 days after anthesis. The decreasing NDVI values at the end of the growth cycle were expected due to senescence and yellowing of the wheat spikes and leaves. Therefore, significant differences in the NDVI were observed between three measurement points on the 13th, 24th, and 45th day after anthesis. Additionally, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge index (NDRE) were in significant positive correlation with the NDVI at 24th day after anthesis. The use of appropriate measurement points for the vegetation indices can offer the decisive advantage of enabling the evaluation of very large breeding trials or farmers’ fields where the timing of fungicide application is particularly important.