Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
The aim of this work is to propose an alternative way for wine classiﬁcation and prediction based on an electronic nose (e-nose) combined with Independent Component Analysis (ICA) as a dimensionality reduction technique, Partial Least Squares (PLS) to predict sensorial descriptors and Artiﬁcial Neural Networks (ANNs) for classiﬁcation purpose. A total of 26 wines from different regions, varieties and elaboration processes have been analyzed with an e-nose and tasted by a sensory panel. Successful results have been obtained in most cases for prediction and classiﬁcation.
Paredes, J. A.,
Alvarez, F. J.,
& Suárez, J. I.
(2012). Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction. Sensors, 12 (6), 8055-8072.
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