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Application of Vis/SNIR hyperspectral imaging in ripeness classification of pear
2017
International Journal of Food Properties
The objective of this research was to create supervised classification models of pear ripeness with the use of hyperspectral imaging system in the visible and short near infrared (425-1000 nm) regions. Spectra and images of 450 pear samples were studied, which were selected from three ripeness stages (unripe, ripe, and overripe). Three classification algorithms-partial least square-discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), and linear discriminant
doi:10.1080/10942912.2017.1354022
fatcat:epiynrxlvvgs3nygbdce2nrpaq