Article ID Journal Published Year Pages File Type
1180817 Chemometrics and Intelligent Laboratory Systems 2006 8 Pages PDF
Abstract

Two chemometric class-modeling techniques (SIMCA and UNEQ) have been used to authenticate the origin of CDO wine samples from Italy. While SIMCA modeling was performed using all variables, UNEQ requires a preliminary variable selection, leading to 4 variables only (Cu, Zn, antocyans and SO2) being included in the models. Both techniques provided highly sensitive and specific category models and resulted also in a very reliable classification of samples (only one or two samples misclassified in SIMCA and UNEQ, respectively). A further investigation on the stability of the models with respect to the wine production year was carried out, showing that while SIMCA models failed to classify most of the samples produced in years different from those used in the modeling phase, quite all of the same samples were accepted by the corresponding UNEQ models. However, when SIMCA modeling was repeated using only the same 4 variables than UNEQ, comparable results were obtained, suggesting an effect of the choice of the experimental variables in the classification outcomes.

Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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