Class modeling techniques in the control of the geographical origin of wines

Abstract Wine samples of four different countries: Hungary, Czech Republic, Romania and South Africa, have been studied within the European project WINES-DB “establishing of a wine data bank for analytical parameters from third countries”. For each country two types of wine samples were collected, during three consecutive years: commercial wines and wines obtained by microvinification according to EC regulation N. 2729/2000. The sampling design was organized to represent both the grape varieties and the official wine regions in the four countries. The 1188 wine samples were analyzed for 58 chemical quantities. Data analysis was performed with special attention to the real problem, namely the control of frauds. Class modeling techniques (UNEQ, SIMCA, MRM) have been applied, to answer to the general question: “Does sample O, stated of class A, really belong to class A?”. Two validation strategies, based on cross validation and on an external, representative, evaluation set, have been used to evaluate carefully the predictive performance of the class models. The results obtained with the four class modeling techniques indicate that for the four countries it is possible to compute models with high efficiency, generally with a reduced number of variables. To obtain efficient models, red and white wines, commercial and microvinification wines, must be considered separately. The validity of the models is ensured by the representativity of the samples, the appropriate application of techniques of Chemometrics and the validation.