Online detection and quantification of particles of ergot bodies in cereal flour using near-infrared hyperspectral imaging

ABSTRACTThe objective of this study is to assess NIR hyperspectral imaging for the detection of ergot bodies at the particle level in cereal flour. For this study, ground ergot body samples and wheat flour samples as well as mixtures of both from 100 mg/kg to 500,000 mg/kg were analysed. Partial least squares discriminant analysis (PLS-DA) models were developed and applied to spectral images in order to detect the ergot body particles. Ergot was detected in 100% of samples spiked at more than 10,000 mg/kg and no false positives were obtained with non-contaminated samples. A correlation of 0.99 was calculated between the reference values and the values predicted by the PLS-DA model. For the cereal flours containing less than 10,000 mg/kg of ergot, it was possible for some samples spiked as low as 100 mg/kg to detect enough pixels of ergot to conclude that the sample was contaminated. However, some samples were under- or overestimated, which can be explained by the lack of homogeneity in relation to the sam...