Investigation of physiological disorder classification in mangosteen fruit using visible and shortwave near-infrared spectroscopy combined with machine learning

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dc.contributor.authorNuttapong Ruttanadech
dc.contributor.authorAbdul Momin
dc.contributor.authorKittisak Phetpan
dc.contributor.authorMontree Chaichanyut
dc.contributor.authorChitwadee Thongphut
dc.contributor.authorThitima Phanomsophon
dc.contributor.authorThatchapol Chungcharoen
dc.date.accessioned2026-05-08T19:19:41Z
dc.date.issued2025-7-15
dc.identifier.doi10.1016/j.postharvbio.2025.113771
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17138
dc.publisherPostharvest Biology and Technology
dc.subjectSpectroscopy and Chemometric Analyses
dc.subjectPhytochemicals and Antioxidant Activities
dc.subjectCoconut Research and Applications
dc.titleInvestigation of physiological disorder classification in mangosteen fruit using visible and shortwave near-infrared spectroscopy combined with machine learning
dc.typeArticle

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