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The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Analytical algorithms based on Raman spectroscopy are proposed for the determination of amylopectin and amylose concentrations in polished white rice, and applied to characterize and compare linear and branched polysaccharide structures in nine different types of Japanese rice. A selected algorithm used symmetric bending vibrations of the COC glycosidic linkage from a relatively narrow spectral zone between 830 and 895 cm -1 . It specifically compared the intensity of Raman signals from two types of bending common to both starch components (C1-O-C5 and C1-O-C4 at 868 and 855 cm -1 , respectively) and that at the branch point peculiar to amylopectin (C1-O-C6 at 844 cm -1 ). Raman data were confronted with data collected by conventional amylose-iodine colorimetry method. Consistency was found between Raman and colorimetric methods over the entire series of tested rice cultivars, thus validating the newly proposed spectroscopic algorithm. The amylose content of the tested rice species broadly varied between 1.2 and 20.4%. The proposed Raman algorithm allows fast and nondestructive determination of amylose content in rice with minimal sample preparation. These characteristics might be key in the development of portable Raman devices capable to promptly screen polysaccharides in different rice cultivars with respect to their interannual and plantation-related fluctuations., (Copyright © 2021 Elsevier Ltd. All rights reserved.)