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Comparison analysis of antioxidant activity in Chinese red wines and its application in varietal discrimination
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Zhi-Xin PENG1, Meng-Jie LI2, Ya-Kun GU3, Xiao-Li YIN2, Hui-Wen GU2, *
Journal of Food Safety & Quality | 2026, 17(11) : 51 - 58
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Journal of Food Safety & Quality | 2026, 17(11): 51-58
• Highlight: Academic Paper Achievements of the 28th Annual Conference of the China Association for Science and Technology •
Comparison analysis of antioxidant activity in Chinese red wines and its application in varietal discrimination
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Zhi-Xin PENG1, Meng-Jie LI2, Ya-Kun GU3, Xiao-Li YIN2, Hui-Wen GU2, *
Affiliations
  • 1.College of Food Science and Technology, Wuhan University of Bioengineering, Wuhan 430415, China
  • 2.College of Life Sciences/College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434023, China
  • 3.College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
doi: 10.19812/j.cnki.jfsq11-5956/ts.20251203007
Outline
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Objective

To establish a rapid model for varietal discrimination of Chinese red wines by leveraging the differences in antioxidant activity among different varieties.

Methods

The total phenolic content, total flavonoid content, cupric ion reducing antioxidant capacity, 1,1-diphenyl-2-picryl-hydrazyl radical scavenging capacity and 2,2’-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) ammonium salt radical cation scavenging capacity of different varieties of Chinese red wines (Pinot Noir, Merlot, Cabernet Gernischt and Cabernet Sauvignon) were determined and compared. Meanwhile, principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) and support vector machine (SVM) algorithms were combined to establish a varietal identification model for Chinese red wines.

Results

Comparative analysis revealed that the order of antioxidant activity of the 4 varieties was: Cabernet Sauvignon>Merlot>Cabernet Gernischt>Pinot Noir. On this basis, the constructed PCA (R2Xcum=0.819) and OPLS-DA (R2Xcum=0.952, R2Ycum=0.424, Q2cum=0.387) models effectively characterized the data features and intergroup differences. The SVM varietal identification model achieved a cross-validation accuracy of 94.40%, with 100.00% accuracy in the training set and 96.26% accuracy in the test set.

Conclusion

Based on the variety-specific antioxidant activity differences of Chinese red wines, combined with multivariate statistical methods and machine learning algorithms, rapid and accurate discrimination of Chinese red wine varieties can be effectively achieved.

Chinese red wine  /  antioxidant activity  /  principal component analysis  /  orthogonal partial least squares-discriminant analysis  /  support vector machine  /  varietal identification
彭芷芯, 李梦杰, 谷亚坤, 尹小丽, 谷惠文. 国产红葡萄酒抗氧化活性比较分析及其在品种鉴别中的应用. 食品安全质量检测学报, 2026 , 17 (11) : 51 -58 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20251203007
Zhi-Xin PENG, Meng-Jie LI, Ya-Kun GU, Xiao-Li YIN, Hui-Wen GU. Comparison analysis of antioxidant activity in Chinese red wines and its application in varietal discrimination[J]. Journal of Food Safety & Quality, 2026 , 17 (11) : 51 -58 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20251203007
Year 2026 volume 17 Issue 11
7
1
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Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20251203007
  • Receive Date:2025-12-03
  • Online Date:2026-11-05
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  • Received:2025-12-03
Funding
Affiliations
    1.College of Food Science and Technology, Wuhan University of Bioengineering, Wuhan 430415, China
    2.College of Life Sciences/College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434023, China
    3.College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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