JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 41 Issue 3
June 2026
Article Contents
ZOU Hua, PAN Yuan, QIANG Haiqing, et al. Geographical origin identification of Chinese Cabernet Sauvignon red wines based on HPLC-DAD three-dimensional chromatographic fingerprinting[J]. Journal of Light Industry, 2026, 41(3): 10-18. doi: 10.12187/2026.03.002
Citation: ZOU Hua, PAN Yuan, QIANG Haiqing, et al. Geographical origin identification of Chinese Cabernet Sauvignon red wines based on HPLC-DAD three-dimensional chromatographic fingerprinting[J]. Journal of Light Industry, 2026, 41(3): 10-18. doi: 10.12187/2026.03.002 shu

Geographical origin identification of Chinese Cabernet Sauvignon red wines based on HPLC-DAD three-dimensional chromatographic fingerprinting

  • 【Objective】 This study aimed to advance the authenticity identification and origin traceability techniques of wines. 【Methods】 The three-dimensional chromatographic fingerprints of 45 Cabernet Sauvignon red wines from three famous producing regions in China (Qinhuangdao, Yinchuan, and Turpan) were acquired using high-performance liquid chromatography with diode array detection (HPLC-DAD). The data were then resolved by multivariate curve resolution-alternating least squares (MCR-ALS). Based on the relative concentrations of the resolved components, three machine learning algorithms—principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and support vector machine (SVM)—were applied to discriminate the geographical origins of the red wines. 【Results】 A total of 56 resolved components were obtained by MCR-ALS analysis of the three-dimensional chromatographic fingerprints. PCA score plots showed a tendency of the wines to cluster according to their geographical origins. Both PLS-DA and SVM models achieved good classification performance, with 100% recognition accuracy for both the training and prediction sets. Furthermore, a VIP-PLS-DA model based on 22 differential variables enabled accurate discrimination of the geographical origins of the wines with 100%. 【Conclusion】 The HPLC-DAD three-dimensional chromatographic fingerprinting technique combined with machine learning algorithms can establish a stable and reliable recognition model, and is expected to provide objective and accurate identification of three geographical origins of Chinese Cabernet Sauvignon red wines.
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