Chilean Wines Classification based only on Aroma Information

Abstract

Results of Chilean wine classification based on the aroma information provided by an electronic nose are reported in this paper. The classification scheme consists of two parts; in the first stage, Principal Component Analysis is used as a feature extraction method to reduce the dimensionality of the original information, while in the second stage, Radial Basis Functions Neural Networks is used as pattern recognition technique to perform the classification. This study is aimed to classify wine samples from different years, valleys and vineyards of Chile, into one of the classes Cabernet Sauvignon, Merlot or Carménère.