Development of a rapid and affordable machine learning-based screening technique for honey adulteration using UV-visible absorption spectr

Honey, a high-value food product, is a common target of food fraud through adulteration with low-cost sweeteners and ingredients. Up to 87% of all local honey products sold in the Philippines are adulterated with as much as 100% substitution. Adulterated honey, typically sold at a low price, potenti...

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Bibliografische gegevens

Hoofdauteur:	Sabacan, Ethan Josiah T. (Auteur)
Andere auteurs:	Dumelod, Benelyn D. (adviser.)
Formaat:	Thesis
Taal:	English
Onderwerpen:	Chemometrics. Authentication. UV-Vis spectrometry. Philippine honey. Food adulteration. Machine learning. Honey adulteration. Discriminant model.
Online toegang:	Available for University of the Philippines Diliman via Digital Archives. Click here to access.