Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning

Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning

Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of a...

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Bibliographic Details
Main Authors: José Luis P. Calle, Irene Punta-Sánchez, Ana Velasco González-de-Peredo, Ana Ruiz-Rodríguez, Marta Ferreiro-González, Miguel Palma
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Foods
Subjects:
honey
adulteration
machine learning
visible near infrared spectroscopy
support vector machine
random forest
Online Access:https://www.mdpi.com/2304-8158/12/13/2491

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