为了探讨非目标指纹图谱技术验证中国葡萄酒原产地的可行性，本研究采用一维核磁共振氢谱（1H NMR）技术快速测定方法，对沙城、昌黎和昌吉三大特色原产地葡萄酒224个进行分析。结果表明，主成分分析（principal component analysis, PCA）结合线性判别分析（linear discriminant analysis, LDA）建立的留一交叉验证模型，实现对沙城、昌黎和昌吉葡萄酒原产地样品准确识别率为92%，73%，68%；为避免PCA/LDA模型出现过拟合现象，采用外部重复双随机交叉验证方法对PCA/LDA模型的有效性进行验证。研究发现葡萄酒1H NMR指纹图谱包含葡萄酒原产地特征信息，通过多变量统计分析技术可以构建非目标1H NMR指纹图谱的中国葡萄酒产地验证技术模型。

This study investigated the feasibility of discriminating Chinese wines from different geographical origins using non-targeted1H NMR fingerprinting, 224 wine samples from three distinctive geographical origins (Shacheng, Changli and Changji) were measured. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) using internal leave one-out cross validation were employed to establish the discrimination model of the three geographical origins. Accurate classification rates for the wine samples of Shacheng, Changli and Changji were 92%, 73%, 68%, respectively. In order to avoid the overfitting, repeated double random cross validation methods was used to verify the validity of the PCA/LDA model. This study suggested that1H NMR fingerprinting of wines contained the geographical origin feature information, the non-targeted1H NMR fingerprinting model for verifying Chinese wines based on their geographical origins could be constructed by multivariate statistical analysis technology.