Low-cost Multispectral Acquisition Device Coupled with Machine Learning for Detecting Adulteration of Honey

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dc.contributor.authorBoodnon, Wutthiphong
dc.contributor.authorLunvongsa, Thayanont
dc.contributor.authorSuntisakoonwong, Phanchay
dc.contributor.authorSitorus, Agustami
dc.contributor.authorLapcharoensuk, Ravipat
dc.date.accessioned2026-08-06T10:56:11Z
dc.date.available2026-08-06T10:56:11Z
dc.date.issued2026-07-15
dc.description.abstractHoney is a natural sweetener created by honeybees from the nectar of flowers. Honey's extensive health benefits have led to its widespread use across multiple industries. Honey adulteration with inferior substances undermines its quality, reducing natural nutrients and antioxidants, and diminishing its health benefits. This study aimed to study the possibility of detection of honey adulteration with a low-cost multispectral device coupled with machine learning. The adulterated honey came from deliberate adulteration with cane syrup in the 1 to 90% range. Spectral data was collected for pure honey and the adulterated honey samples at the wavelengths of 610, 680, 730, 760, 810, and 860 nm. The detection models for distinguishing pure and adulterated honey were developed by Linear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), C-Support Vector Machine (C-SVM), and K-Nearest Neighbors (KNN). All models achieved high accuracy between 0.91 and 0.98 and maintained balanced precision and recall metrics. This study serves as a guideline for developing a low-cost portable honey authentication device that is practical for real-world applications.
dc.identifier.citationCurrent Applied Science and Technology, 26(5), 2026
dc.identifier.doi10.55003/cast.2025.265920
dc.identifier.issn25869396
dc.identifier.other2-s2.0-105045498529
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/18266
dc.sourceCurrent Applied Science and Technology
dc.subjectadulteration
dc.subjecthoney
dc.subjectlow-cost multispectral device
dc.subjectmachine learning
dc.titleLow-cost Multispectral Acquisition Device Coupled with Machine Learning for Detecting Adulteration of Honey
dc.typeArticle

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