Xinyu Jin1, Shimin Wu1, Wenjuan Yu2, Xinyi Xu1, Mingquan Huang3, Yongfang Tang4, Zhenyu Yang5. 1. Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Food Science and Technology, 800 Dongchuan Rd, Shanghai, China 200240. 2. Shanghai Jiao Tong University, Bor S. Luh Food Safety Research Center, 800 Dongchuan Rd, Shanghai, China 200240. 3. Beijing Technology and Business University, Beijing Laboratory for Food Quality and Safety, Beijing, China 100048. 4. Shanghai Liquor Quality Inspection Center, 379 Quyang Rd, Shanghai, China 200081. 5. Shanghai Entry-Exit Inspection and Quarantine Bureau, 2001 North Yanggao Rd, Shanghai, China 200131.
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.
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.