Understanding processing, maturity and harvest period effects to authenticate early-spring Longjing tea using stable isotopes and chemometric analyses

文献类型： 外文期刊

第一作者： Xia, Wei

作者： Xia, Wei;Li, Zuguang;Xia, Wei;Liu, Zhi;Nie, Jing;Li, Chunlin;Shao, Shengzhi;Zhang, Yongzhi;Rogers, Karyne M.;Yuan, Yuwei;Yu, ChongChong;Xia, Wei;Liu, Zhi;Nie, Jing;Li, Chunlin;Shao, Shengzhi;Zhang, Yongzhi;Rogers, Karyne M.;Yuan, Yuwei;Rogers, Karyne M.

作者机构：

关键词： Early-spring Longjing tea; Stable isotopes; Drying method; Leaf maturity; Harvest period

期刊名称：FOOD CONTROL （ 影响因子：6.652； 五年影响因子：6.498 ）

ISSN： 0956-7135

年卷期： 2021 年 124 卷

页码：

收录情况： SCI

摘要： Low-yielding early-spring (ES) Longjing tea is popular with Chinese consumers and commands a high price due to its scarcity, but it has a heightened risk of substitution with lower value tea products from later harvest periods due to similarities in appearance. In this study, tea samples from different harvest periods were analyzed using stable isotope analyses (613C, 615N, 62H, and 618O) to distinguish effects from different tea drying processes, leaf maturity and harvest period. Our results showed there were no significant differences among all stable isotopes for different tea drying processes (p 0.05). 613C values showed little difference among different maturity tea leaves over the entire spring period (p > 0.05). 615N values of mature leaves were found to be 0.4 parts per thousand higher than young leaves in early spring. 62H and 618O values of different maturity leaves had different fractionation ratios (RM/Y) of 1.17 and 1.14 in early spring and late spring, respectively (p < 0.05). Generally, tea stable isotopes showed seasonal enrichment in early spring, then depletion in late spring. 618O values were significantly correlated to air humidity, light intensity and precipitation (0.53 < r < 0.92), and 613C and 62H values were negatively correlated with air temperature and air humility, respectively (0.57 < r < 0.74). A supervised chemometric model (orthogonal partial least squares discriminant analysis, OPLS-DA) was used to classify the ES and late-spring (LS) Longjing tea, and the discriminant accuracy of the training set was 95 %, while the test set and blind set showed a good accuracy of 100 % and 83.3 %, respectively. Result showed that this new method was a feasible technique to protect ES Longjing tea, and also provides evidence that tea harvest periods can be predicted by using stable isotopes and chemometric analyses.

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