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 Ne...

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Detalles Bibliográficos
Autores principales: Aguilera, Teodoro, Lozano, Jesús, Paredes, José A., Álvarez, Fernando J., Suárez, José I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436016/
https://www.ncbi.nlm.nih.gov/pubmed/22969387
http://dx.doi.org/10.3390/s120608055
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author Aguilera, Teodoro
Lozano, Jesús
Paredes, José A.
Álvarez, Fernando J.
Suárez, José I.
author_facet Aguilera, Teodoro
Lozano, Jesús
Paredes, José A.
Álvarez, Fernando J.
Suárez, José I.
author_sort Aguilera, Teodoro
collection PubMed
description 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.
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spelling pubmed-34360162012-09-11 Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction Aguilera, Teodoro Lozano, Jesús Paredes, José A. Álvarez, Fernando J. Suárez, José I. Sensors (Basel) Article 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. Molecular Diversity Preservation International (MDPI) 2012-06-11 /pmc/articles/PMC3436016/ /pubmed/22969387 http://dx.doi.org/10.3390/s120608055 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Aguilera, Teodoro
Lozano, Jesús
Paredes, José A.
Álvarez, Fernando J.
Suárez, José I.
Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title_full Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title_fullStr Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title_full_unstemmed Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title_short Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction
title_sort electronic nose based on independent component analysis combined with partial least squares and artificial neural networks for wine prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436016/
https://www.ncbi.nlm.nih.gov/pubmed/22969387
http://dx.doi.org/10.3390/s120608055
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