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Sensors 2012, 12(6), 8055-8072; doi:10.3390/s120608055
Article

Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction

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Received: 10 April 2012 / Revised: 25 May 2012 / Accepted: 5 June 2012 / Published: 11 June 2012
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Abstract

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.
Keywords: independent component analysis; partial least squares; artificial neural networks; electronic nose; wine classification independent component analysis; partial least squares; artificial neural networks; electronic nose; wine classification
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Aguilera, T.; Lozano, J.; Paredes, J.A.; Álvarez, F.J.; Suárez, J.I. Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction. Sensors 2012, 12, 8055-8072.

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