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

Area of Science:

• Analytical Chemistry
• Food Science
• Chemometrics

Background:

• Organic acids are key components influencing wine flavor and quality.
• Accurate classification of wine is important for quality control and authenticity verification.

Purpose of the Study:

• To develop and optimize a capillary electrophoresis (CE) method for determining major organic acids in white wine.
• To utilize multivariate statistical analysis for classifying white wine samples based on their organic acid profiles.

Main Methods:

• Optimization of CE separation for succinic, malic, tartaric, citric, acetic, and lactic acids.
• Use of a specific buffer (180 mM disodium hydrogen phosphate, 0.5 mM CTAB, 10% methanol, pH 7.5) and conditions (10 kV, 25°C).
• Application of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for classification.

Main Results:

• The CE method demonstrated good linearity and precision (RSD < 5.2% for peak area, < 1% for migration time).
• Accurate classification of white wine samples with varying alcohol content was achieved using PCA and LDA.
• Electropherogram regions with significant discriminant potential were identified.

Conclusions:

• The developed CE method is effective for generating characteristic electrophoretic fingerprints of white wines.
• This approach provides a reliable tool for the classification of wine samples based on their organic acid composition.