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Summary To realise accurate and nondestructive detection on moisture content of maize seed based on visible/near‐infrared (Vis/ NIR ) and near‐infrared ( NIR ) hyperspectral imaging technology, the hyperspectral images on two sides (embryo and endosperm sides) of each maize seed of four varieties were collected. The effects of average spectra extraction regions, that is centroid region and whole seed region, and different spectral preprocessing methods, were investigated. Uninformative variable elimination ( UVE ) was used to extract the feature wavelengths, and the partial least squares regression ( PLSR ) prediction models were established. The results showed that extracting the average spectra from the centroid region did better than from the whole seed region, and S‐G smoothing was prior to other preprocessing methods. The PLSR models established with NIR spectra had better performance than that with Vis/ NIR spectra. The model developed for a single variety was superior to that for all varieties together.
Zhang et al. (Wed,) studied this question.