An electronic tongue based on amperometric detection in a flow injection system (FIA) and a commercial electronic nose have been used to characterize and classify four types of Barbera wines having different denominations of origin and produced in northern Italy in enclosed geographical areas. E-nose and e-tongue data were compared and elaborated together with those of chemical analysis and colour evaluation. All data were treated by multivariate data processing based on principal component analysis (PCA), linear discriminant analysis (LDA) and classification and regression trees (CART) analysis. In the classification of Barbera wines the best results were obtained from LDA applied to electronic nose and electronic tongue data, this analysis giving 100% correct assignation and 98.1% correct prediction.
Characterization and Classification of Italian Barbera Wines by Using an Electronic Nose and an Amperometric Electronic Tongue / S. Buratti, S. Benedetti, M. Scampicchio, E. C. Pangerod. - In: ANALYTICA CHIMICA ACTA. - ISSN 0003-2670. - 525:1(2004), pp. 133-139. [10.1016/j.aca.2004.07.062]
Characterization and Classification of Italian Barbera Wines by Using an Electronic Nose and an Amperometric Electronic Tongue
S. BurattiPrimo
;S. BenedettiSecondo
;M. ScampicchioPenultimo
;
2004
Abstract
An electronic tongue based on amperometric detection in a flow injection system (FIA) and a commercial electronic nose have been used to characterize and classify four types of Barbera wines having different denominations of origin and produced in northern Italy in enclosed geographical areas. E-nose and e-tongue data were compared and elaborated together with those of chemical analysis and colour evaluation. All data were treated by multivariate data processing based on principal component analysis (PCA), linear discriminant analysis (LDA) and classification and regression trees (CART) analysis. In the classification of Barbera wines the best results were obtained from LDA applied to electronic nose and electronic tongue data, this analysis giving 100% correct assignation and 98.1% correct prediction.Pubblicazioni consigliate
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