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, Switzerland), 2012)
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.