Abstract
Background: Cabernet Sauvignon wine enjoys large market in China, and its adulteration has become a well-known problem and challenge. Objective: This study aims to evaluate the capabilities of multiple techniques, including headspace-solid-phase microextraction-GC-MS (HS-SPME-GC-MS), electronic tongue (E-tongue) spectroscopy, mid-infrared (MIR) spectroscopy, and near-infrared (NIR) spectroscopy, to differentiate this popular imported wine in China. Methods: MIR spectroscopy, NIR spectroscopy, E-tongue spectroscopy, and HS-SPME-GC-MS were used. Multivariate analysis techniques were applied to further explore the instrumental determination data for the wine discrimination. Results: Joint use of MIR and NIR with Grey relational analysis (GRA), E-tongue with principal component analysis (PCA) and hierarchical cluster analysis, and HS-SPME-GC-MS with PCA allowed unanimous differentiation of the wines. Conclusions: The approach described herein offers both ecologically friendly and multiperspective mutual corroboration techniques for Cabernet Sauvignon wine discrimination. The integrative methodology could be used as a reference for wine authentication. Highlights: GRA was first applied to discriminate the wine samples. Mutual corroboration was verified by multivariate statistics combined with MIR, NIR, E-tongue, and SPME-GC/MS. Integrated techniques pointed to a unanimous authentication of the wine samples.
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