Geographical origin traceability of Keemun black tea based on its non‐volatile composition combined with chemometrics

化学计量学 茶黄素 主成分分析 红茶 线性判别分析 化学 色谱法 高效液相色谱法 多元统计 食品科学 统计 数学 多酚 生物化学 抗氧化剂
作者
Shimao Fang,Wenjing Huang,Yuming Wei,Tao Meng,Xin Hu,Tiehan Li,Yusef Kianpoor Kalkhajeh,Wei‐Wei Deng,Jingming Ning
出处
期刊:Journal of the Science of Food and Agriculture [Wiley]
卷期号:99 (15): 6937-6943 被引量:46
标识
DOI:10.1002/jsfa.9982
摘要

ABSTRACT BACKGROUND Non‐volatile compounds play a key role in the quality and price of Keemun black tea (KBT). The non‐volatile compounds in KBT samples from different producing areas normally vary greatly. The development of rapid methods for tracing the geographical origin of KBT is useful. In this study, we develop models for the discrimination of KBT's geographical origin based on non‐volatile compounds. RESULTS Seventy‐two KBT samples were collected from five towns in Anhui province to determine 13 KBT compounds by high‐performance liquid chromatography (HPLC). Analysis of variance showed that the content of 13 compounds in KBT indicated significant differences ( P < 0.05) among five towns. Three multivariate statistical models including principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), and linear discriminant analysis (LDA) were built to discriminate origin. Principal component analysis effectively extracted three principal components, namely theaflavins, galloylated catechins, and simple catechins. The high sensitivity (64.5%–99.2%) was achieved of SIMCA model. To establish the discriminant functions, six variables (gallic acid, (+)‐catechin, (−)‐epigallocatechin gallate, theaflavin‐3‐gallate, theaflavin‐3,3′‐di‐gallate, and total theaflavins) were chosen from 13 variables, and LDA was applied. This gave a satisfactory overall correct classification rate (94.4%) and cross‐validation rate (88.9%) for KBT samples. CONCLUSION The results showed that HPLC analysis together with chemometrics is a reliable approach for tracing KBT and guaranteeing its authenticity. © 2019 Society of Chemical Industry
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