Rapid Method for the Discrimination of Red Wine Cultivars Based on Mid-Infrared Spectroscopy of Phenolic Wine Extracts

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Abstract
Mid-infrared spectroscopy and UV−vis spectroscopy combined with multivariate data analysis have been applied for the discrimination of Austrian red wines, including the cultivars Cabernet Sauvignon, Merlot, Pinot Noir, Blaufränkisch (Lemberger), St. Laurent, and Zweigelt. Both authentic wines and their phenolic extracts were investigated by attenuated total reflectance (ATR)−mid-infrared spectroscopy. Phenolic extracts were also investigated by UV−vis spectroscopy. The wine extracts were obtained by solid-phase extraction with C-18 columns and elution by methanol containing 0.01% hydrochloric acid. Hierarchical cluster analysis was performed with mid-infrared spectra of both wines and extracts, as well as with UV−vis spectra of the phenolic extracts. Data processing involved vector normalization and derivation of the spectra. Due to varying concentrations of main components including sugar and organic acids, satisfactory classification of untreated wines was not achieved. However, when using mid-infrared spectra of the phenolic extracts, almost complete discrimination of all cultivars investigated was achieved. The use of UV−vis spectroscopy for cultivar discrimination was found to be limited to the authentication of the Burgundy species Pinot Noir. In addition, soft independent modeling of class analogy was applied to the mid-infrared spectra of the extracts. It was possible to establish class models for five different wine cultivars and to classify test samples correctly. Keywords: Wine; polyphenols; anthocyanin; flavonoids; mid-infrared spectroscopy; classification; authentication; cluster analysis; UV−vis spectroscopy; solid-phase extraction; SIMCA; pattern recognition; hierarchical clustering

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