Random Forest, Artificial Neural Network, and Support Vector Machine Models for Honey Classification

Random Forest, Artificial Neural Network, and Support Vector Machine Models for Honey Classification

Different separated protein fractions by the electrophoretic method in polyacrylamide gel were used to classify two different types of honeys, Galician honeys and commercial honeys produced and packaged outside of Galicia. Random forest, artificial neural network, and support vector machine models w...

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Bibliographic Details
Main Authors: Cecilia Martinez-Castillo, Gonzalo Astray, Juan Carlos Mejuto, Jesus Simal-Gandara
Format: Article
Language:English
Published: Atlantis Press 2019-10-01
Series:eFood
Subjects:
Food authenticity
honey
Galician honeys
classification models
Online Access:https://www.atlantis-press.com/article/125919278/view
Description
Summary:Different separated protein fractions by the electrophoretic method in polyacrylamide gel were used to classify two different types of honeys, Galician honeys and commercial honeys produced and packaged outside of Galicia. Random forest, artificial neural network, and support vector machine models were tested to differentiate Galician honeys and other commercial honeys produced and packaged outside of Galicia. The results obtained for the best random forest model allowed us to determine the origin of honeys with an accuracy of 95.2%. The random forest model, and the other developed models, could be improved with the inclusion of new data from different commercial honeys.
ISSN:2666-3066

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