CHANG Rui, MA Mengjun, LUO Liyong, YU Xia, DAI Lifeng, ZENG Liang
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.
