Exploring the limit of detection on early implicit bruised 'Korla' fragrant pears using hyperspectral imaging features and spectral variables

This work aimed to compare the discrimination ability and detection of limit on the different early implicit bruised pears based on visible and short-wave near-infrared (400-1000 nm) hyperspectral imaging (Vis-SWNIRHSI) features and spectral information. The changes of physical characteristics were much more sensitive than chemical parameters for bruised pears while the postharvest storage. The pear bruising changes can be addressed to the spectral variations at 416-486 nm, 516-646 nm, 939-954 nm, and 973 nm. The partial least squares discrimination models (PLS-DA) based on selected HSI spectral variables can satisfactorily identify the bruised pear area about 63.32 +/- 9.02 mm2, with the discrimination accuracy of 90%, but not available of using imaging features. Further, PLS-DA models based on the fusion of selected HSI spectral variables and imaging features reached the discrimination rate of 98.8% between bruised and non-bruised pears, and provided the discrimination rate of 95% to successfully identify the early bruised pears with bruise area of 72.18 +/- 7.32 mm2 after 1 day of storage. Consequently, the combination of hyperspectral imaging features and spectral variables had the best ability to detect early implicit bruised 'Korla' fragrant pears during postharvest storage.

Automated summary

This study aimed to compare the discrimination ability and detection limit of visible and short-wave near-infrared hyperspectral imaging features and spectral information on early implicit bruised pears. Physical characteristics were more sensitive than chemical parameters for bruised pears during postharvest storage. The changes in spectral variations at specific wavelengths could explain the bruising changes in pears. Discrimination models based on selected spectral variables could effectively identify bruised pear areas, and the combination of imaging features and spectral variables achieved higher discrimination rates.