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During the ageing period wine spirits are changing their color, chemical composition and sensory characteristics. These changes should be simply monitored. The aim of this study was to develop partial least squares regression (PLS) models for higher alcohols and phenols in wine spirits as well as to show the feasibility of the NIR spectroscopy combined with chemometric tools to dis­tin­guish wine spirits and brandies with different ageing degree. To get the refe­rence values, the usual methods for the analysis of spirits drinks were used. Ethanol, esters, acids, methanol and higher alcohols were studied. Wine spirits and bran­dies phenol composition was determined by liquid chro­matography. Principal component analysis (PCA) was used to classify the wine spirits and brandies according to their phenolic and higher alcohols compo­sition. Moreover, the Partial least squares regression (PLS regression) was used to calibrate and predict expected contents of higher alcohols and phenols in the wine spirits. Success of the classification of samples by ageing based on indi­vidual alcohols was 93.8 %, while success of the classification based on indi­vidual phenols raised to 100 %. This efficiency of the prediction was evaluated by use of linear discriminator analysis (LDA).

Identification of phenolic and alcoholic compounds in wine spirits and their classification by use of multivariate analysis