SHORT COMMUNICATION STRUCTURE MODELLING AND DISCRIMINATION OF CATALAN WHITE WINES

Cluster analysis has been applied to characterize the group structures of four sets of Catalan white wines(Conca de Barberà),Camp de Tarragona,Terra Alta and Ribera-Falset)on the basis of eleven classicaloenological parameters and seven micro and trace metallic constituents considered to be relativelyinsensitive to cultural practices.In spite of the vintage variation and the lack of a clear varietaldifferentiation among the wines,each region could be individually characterized.The application ofsupervised pattern recognition methods has allowed regional assignment of unknown samples with aprediction rate higher than 95%.Several metal ions(such as calcium,strontium, zinc and magnesium)and a few classical parameters(such as ethanol content and the sum of malic and lactic acid contents)have been found to be relevant for a correct classification.ALLOC and KNN classification methodscombined with LDA have been proven useful with the present data set,although their performance wasnot superior to that of LDA and SIMCA.

SHORT COMMUNICATION STRUCTURE MODELLING AND DISCRIMINATION OF CATALAN WHITE WINES