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绿茶是我国六大茶类之一,产地分布广,品质差异性大。目前,对茶叶产地的鉴别主要依赖感官审评,缺乏量化的评价指标,评价结果存在着不确定性。本研究对6个省份绿茶主要化学成分进行主成分分析,提取主要成分因子,应用贝叶斯(Bayes)判别结合聚类分析对不同产地绿茶进行鉴别。结果表明,Bayes判别对6个地区27个样品能达100%的正确判别,同时聚类分析结果与原始样品基本相同,为绿茶产地的鉴别提供具体量化模型。
Green tea is one of China’s six major teas, producing a wide distribution and quality differences. At present, the identification of the origin of tea relies mainly on the sensory evaluation, the lack of quantitative evaluation index, the evaluation of the results there is uncertainty. In this study, the main chemical components of green tea in six provinces were analyzed by principal component analysis, the main component factors were extracted, and Bayes discriminant analysis combined with cluster analysis was used to identify green tea from different areas. The results show that Bayes discriminant can correctly determine 100% of 27 samples in six regions, and the results of cluster analysis are basically the same as the original samples, providing a specific quantitative model for the identification of green tea origin.