Development of a Method for Detecting Responses of Different Oat Cultivars to Fusarium Head Blight Infection in Greenhouse Conditions Using Hyperspectral Image Analysis

Hyperspectral (HS) analysis was used to measure the dynamics of Fusarium head blight (FHB) disease severity on panicles of three oat cultivars, ‘Husky’, ‘Ivory’, and ‘Lelde’, under greenhouse conditions. Inoculation with Fusarium spp. spore material was conducted (i) on the seeds and (ii) plants at the mid-flowering stage (BBCH 65). Disease development on oat panicles was assessed visually, and imaged with an HS camera from the end of the flowering stage (BBCH 69) to the early–middle ripe stage (BBCH 83–85). To verify that FHB symptoms were caused by Fusarium spp. pathogens, a microbiological test was performed. At the end of the trial, mycotoxin analysis of the kernels was conducted. The collected HS data from diseased and control plant panicles were used to estimate the head blight index (HBI). A Python-based software was developed to assess HBI at the pixel level. Both visual assessment and HS analysis confirmed statistically significant differences in disease severity between all treatment options. The highest disease severity results were obtained in the last disease assessment run (BBCH 83–85) for the inoculated head treatment. Microbiological test results confirmed that FHB symptoms in oat kernels were mostly caused by F. sporotrichioides. The correlation coefficient between the visually assessed FHB disease severity results and HS analysis results was 0.969. The correlation coefficient between T-2/HT-2 mycotoxins and HS disease severity results was 0.971, which suggests the potential for using HS analysis in field monitoring for mycotoxin content detection.