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

Sensors

Teodoro Aguilera¹  Jesús Lozano¹  José A. Paredes¹  Fernando J. Álvarez¹ 

[1] Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain; E-Mails:

关键词: independent component analysis;    partial least squares;    artificial neural networks;    electronic nose;    wine classification;   

DOI  :  10.3390/s120608055

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.