Typification of alcoholic distillates by multivariate techniques using data from chromatographic analyses

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Abstract
Multivariate chemometric techniques were used to classify alcoholic distillates and to develop a typification model for Galician liquors, on the basis of percentage data obtained from nine chromatographic peaks. By using the Bayesian model, the probability of a genuine Galician liquor being rejected is 0.11 and that of a false one being accepted is practically nil. Partial least squares was used as a modelling method, taking the liquor category as response variable. This method enables a confidence interval (95%) to be constructed that does not include any of the other distillates.

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