基于抗氧化活性指标的国产红葡萄酒产地识别

Geographical origin identification of Chinese red wines based on antioxidant activity indexes

中文关键词:  国产红葡萄酒  抗氧化活性  产地识别  支持向量机  化学计量学

英文关键词:Chinese red wine  antioxidant activity  geographical origin identification  support vector machine  chemometrics

中文摘要:

      目的 对比分析不同产地葡萄酒抗氧化活性的差异, 以此实现葡萄酒产地的判别。方法 以新疆吐鲁番、宁夏银川和河北秦皇岛的红葡萄酒为研究对象, 采用理化检测方法比较不同产地葡萄酒抗氧化活性的差异, 并利用主成分分析(principal component analysis, PCA)、正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis, OPLS-DA)和支持向量机(support vector machine, SVM)建立葡萄酒的产地识别模型。结果 在对葡萄酒酒样抗氧化活性指标测定中, 不同产地酒样表现的抗氧化能力依次为: 新疆吐鲁番>宁夏银川>河北秦皇岛。基于以上述抗氧化活性指标数据进行PCA分析发现, 不同产地葡萄酒样本大致可以各自聚集成类, 并且前两个主成分的累计方差解释率可达89.6%, 基本可以反应总体数据信息; 进一步通过OPLS-DA和SVM建立产地识别模型, 以其中8个不同产地的葡萄酒样本作为测试集进行外部验证, 结果发现两个模型的识别准确率均可达87.5%, 表现出较好的产地识别能力。结论 根据抗氧化活性的差异性可以实现国产红葡萄酒的产地识别。

英文摘要:

      Objective To compare and analyze the differences of antioxidant activities of Chinese red wines from different origins, so as to achieve their geographical origins identification. Methods Taking the red wines of Turpan of Xinjiang, Yinchuan of Ningxia and Qinhuangdao of Hebei as the research objects, the differences of antioxidant activities of Chinese red wines from different regions were compared by physicochemical detection methods, and predictive models were established to distinguish the geographical origins of them by principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) and support vector machine (SVM). Results In the determination of antioxidant activity indexes in wine samples, the antioxidant capacities of red wine samples from different origins were ranked as follows: Xinjiang Turpan>Ningxia Yinchuan>Hebei Qinhuangdao. Based on the above antioxidant activity indexes data, PCA analysis showed that the red wine samples from different origins could be clustered into categories, and the total variance rate explained by the first two principal components was up to 89.6%, which could basically reflect the overall data information. Furthermore, OPLS-DA and SVM models were established to predict the origins of red wines, and 8 wine samples from different origins were used as the test set for external validation. The results showed that the recognition accuracy of both models could reach 87.5%, showing good ability for geographical origins identification. Conclusion The geographical origins of Chinese red wines can be identified according to the differences of antioxidant activity.