Identification of typical wine aromas by means of an electronic nose

Abstract

In the field of electronic noses (e-noses), it is not very usual to find many applications to wine detection. Most of them are related to the discrimination of wines in order to prevent their illegal adulteration and detection of off-odors, but their objective is not the identification of wine aromas. In this paper, an application of an e-nose for the identification of typical aromatic compounds present in white and red wines is shown. The descriptors of these compounds are fruity, floral, herbaceous, vegetative, spicy, smoky, and microbiological, and they are responsible for the usual aromas in wines; concentrations differ from 2-8/spl times/ the threshold concentration humans can smell. Some of the measured aromas are pear, apple, peach, coconut, rose, geranium, cut green grass, mint, vanilla, clove, almond, toast, wood, and butter. Principal component analysis and linear discriminant analysis show that datasets of these groups of compounds are clearly separated, and a comparison among several types of artificial neural networks has been also performed. The results confirm that the system has good performance in the classification of typical red and white wine aromas.