基于生化成分构建不同地区黑茶分类模型

Construction of a model for classifying dark teas from different areas based on biochemical components

为实现不同地区黑茶的区分鉴别,对供试4个地区共55个黑茶样本的主要生化成分进行检测,并结合多元统计方法构建分类模型。单因素方差分析结果表明,云南熟普的茶多酚、总黄酮、游离氨基酸、咖啡碱、茶黄素、茶褐素、草酸含量显著高于其他地区,但表儿茶素没食子酸酯、表没食子儿茶素没食子酸酯含量显著低于其他地区;云南熟普的儿茶素组分以简单儿茶素为主,而其他地区的儿茶素组分以酯型儿茶素为主。主成分和系统聚类分析结果表明,云南熟普聚为一类,与其他地区黑茶品质差异明显。Fisher判别分析对不同地区黑茶的分类效果最好,其原始分类正确率为100.0%,交叉验证正确分类率为97.7%,外部验证正确分类率为91.7%;影响判别结果的主要物质为茶褐素、表儿茶素没食子酸酯、表没食子儿茶素、黄酮、儿茶素、表没食子儿茶素没食子酸酯和表儿茶素。

With the purpose of distinguishing and identifying dark teas from different areas,the main biochemical components of 55 dark tea samples from four regions were measured,followed by constructing a classification model based on multivariate statistical analysis methods. The results of single factor analysis of variance showed that the contents of tea polyphenols,flavonoids,free amino acids,caffeine,theaflavin,theabrownin,and oxalic acid in Yunnan ripened Pu′er tea were significantly higher than the others,but its contents of epicatechin gallate,epigallocatechin gallate were significantly lower. Moreover,the composition of catechin in Yunnan ripened Pu′er tea was mainly non-galloylated catechins while others were mainly galloylated catechins. Furthermore,the results of principal component analysis and hierarchical cluster analysis could effectively distinguish dark teas from Yunnan province from those of other areas. In addition,Fisher discriminant analysis had the best classifying effect,as its accuracy rate for original classification was 100.0%,and its correct classification rates for cross validation and external validation were 97.7% and 91.7%,respectively. In addition,the main compounds that affected the classification results were theabrownin,epicatechin gallate,epigallocatechin,flavonoids,catechin,epigallocatechin gallate,and epicatechin.