Detection of Fusarium head blight contamination in wheat kernels by multivariate imaging

Multispectral images of dorsal and ventral sides of all kernels were acquired with an in-house imaging system and processed with chemometrical tools, including principal component analysis (PCA) and multiple linear regression (MLR). According to the quantitative PCR (qPCR) results, PCA was able to detect infested kernels and to identify affected areas with kernels. Moreover, regression analysis of the images allowed the degree of contamination for each pixel to be estimated, and thus mapping of contamination for each kernel.