利用顶空 GC/MS 结合化学计量分析鉴定红茶的地理来源。
Use of headspace GC/MS combined with chemometric analysis to identify the geographic origins of black tea.
机构信息
State Key Laboratory of Tea Plant Biology and Utilization School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China.
College of Life Science and Health, Wuhan University of Science and Technology, Wuhan, China.
出版信息
Food Chem. 2021 Oct 30;360:130033. doi: 10.1016/j.foodchem.2021.130033. Epub 2021 May 9.
Some black teas demand high market prices. Black tea samples (306) collected from 10 geographic origins, including China (Guxi, Likou, Jinzipai, Guichi, Dongzhi, Changning, Wuyishan, Shaowu), India (Darjeeling), and Sri Lanka (Kandy), were analyzed using headspace volatilization followed by GC/MS (HS-GC/MS). Forty-eight volatile compounds were identified. The aroma compounds were mainly identified as alcohols, aldehydes, ketones, and esters. Analysis of either full-spectrum data or 22 tea compounds shared among the samples with k-Nearest Neighbor (k-NN) and Random Forest (RF) models discriminated all origins at 100% using KNN and 95% with RF using either data set. The discrimination rates using 2 key aroma compounds (linalool and geraniol) by k-NN were 100% for nine origins, with the rate for Guxi area at 89%, because 3 samples were classified to Jinzipai. The findings support the use of HS-GC/MS combined with chemometrics as a tool to identify the origin of black tea.
一些红茶的市场价格很高。从包括中国（古西、立口、金紫牌、贵池、东至、长宁、武夷山、邵武）、印度（大吉岭）和斯里兰卡（康提）在内的 10 个地理产地采集了 306 个红茶样本，使用顶空挥发后结合 GC/MS（HS-GC/MS）进行分析。鉴定出了 48 种挥发性化合物。香气化合物主要鉴定为醇类、醛类、酮类和酯类。使用全谱数据或 k-最近邻（k-NN）和随机森林（RF）模型对 22 种样品共有的茶化合物进行分析，k-NN 模型使用数据集可将所有产地的区分率达到 100%，RF 模型可达到 95%。使用 k-NN 对 2 种关键香气化合物（芳樟醇和香叶醇）进行区分时，对 9 个产地的区分率为 100%，古西地区的区分率为 89%，因为有 3 个样本被归类为金紫牌。研究结果支持使用 HS-GC/MS 结合化学计量学作为一种识别红茶产地的工具。
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