Differentiation and identification of white wine varieties by using electropherogram fingerprints obtained with CE

Abstract

This article reports a method for determining organic acids by CE in order to obtain a characteristic fingerprint with a view to classifying white wine samples with the aid of multivariate statistics. The proposed method was optimized for the determination of the most abundant organic acids in wine (viz. succinic, malic, tartaric, citric, acetic and lactic). The acids were separated in a running buffer consisting of 180 mM disodium hydrogen phosphate, 0.5 mM CTAB and 10% methanol, adjusted to pH 7.5. The applied voltage was 10 kV and the working temperature 25 degrees C. The precision of the method was assessed by replicate analysis of a wine sample; the resulting RSD was less than 5.2% in peak area and less than 1% in migration time for all organic acids. Calibration curves exhibited good linearity throughout the studied concentration range for all acids. Principal component analysis and linear discriminant analysis allowed accurate classification of wine samples with variable alcohol contents from their electrophoretic fingerprints. The discriminant potential of various electropherogram regions was examined. Based on the results, the proposed method is an effective choice for classifying wine samples.