食品科学 ›› 2019, Vol. 40 ›› Issue (10): 214-219.doi: 10.7506/spkx1002-6630-20180604-028

• 成分分析 • 上一篇    下一篇

青砖茶茶汤滋味成分分析及品质评价模型建立

王胜鹏,龚自明*,郑鹏程,刘盼盼,高士伟,滕 靖,王雪萍,叶 飞,郑 琳,桂安辉   

  1. 湖北省农业科学院果树茶叶研究所,湖北 武汉 430064
  • 出版日期:2019-05-25 发布日期:2019-05-31
  • 基金资助:
    国家现代茶产业技术体系建设专项(CARS-23);湖北省重大科技创新计划项目(2014ABA023);湖北省农业科技创新中心创新团队项目(2016-620-000-001-032);国家自然科学基金青年科学基金项目(31400586)

Qingzhuan Brick Tea Infusion: Analysis of Taste Components and Establishment of Quality Evaluation Model

WANG Shengpeng, GONG Ziming*, ZHENG Pengcheng, LIU Panpan, GAO Shiwei, TENG Jing, WANG Xueping, YE Fei, ZHENG Lin, GUI Anhui   

  1. Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China
  • Online:2019-05-25 Published:2019-05-31

摘要: 以不同厂家生产的青砖茶为研究对象,在对茶汤滋味进行感官审评后,测定内含成分含量,利用主成分分析法和相关系数法筛选代表性内含成分,最后结合主成分回归法和逐步回归法建立茶汤滋味品质评价回归方程,并用未知样品检验回归方程预测效果。结果表明,筛选出5 个与茶汤滋味品质密切相关的内含成分(P<0.05),按照对茶汤滋味的贡献大小,依次为表没食子儿茶素没食子酸酯、儿茶素总量、茶多酚、表儿茶素没食子酸酯和表没食子儿茶素;以逐步回归方法建立的茶汤滋味品质评价方程预测结果最佳(校正集决定系数0.973 5,交互验证均方根误差0.380 7;验证集决定系数0.968 1,预测均方根误差0.400 0);以逐步回归方程对未知样品的预测结果最佳(验证集决定系数0.974 6,预测均方根误差0.391 5)。结果表明,应用化学计量学方法建立拟合方程实现对青砖茶茶汤滋味品质的准确、可靠预测,为青砖茶茶汤滋味品质评价提供一种新的参考方法。

关键词: 青砖茶, 茶汤, 回归方程, 主成分分析, 相关系数

Abstract: In the present experiment, Qingzhuan tea samples from different manufacturers were used. Taste sensory evaluation of the tea infusions was carried out, followed by chemical measurement. Then, representative chemical components were selected by principal component analysis (PCA) and the correlation coefficient method. Finally, a regression equation for taste quality evaluation of tea infusion was established by principal component regression (PCR) or stepwise regression (SR), and the predictive performance of the regression equation was tested by applying it to unknown samples. The results showed that five components were found to be closely related to the taste quality of tea infusion (P < 0.05), whose contributions to the taste of tea infusion were in the descending order of EGCG, total catechins, tea polyphenols, ECG and EGC. The SR model was better than the PCR model, and the correlation coefficient of calibration (Rc 2 ), root mean square error of cross-validation (RMSECV), correlation coefficient of prediction (Rp 2) and root mean square error of prediction (RMSEP) of the SR model were 0.973 5, 0.380 7, 0.968 1 and 0.400 0, respectively. The SR model showed better predictive performance for the unknown samples (Rp 2 = 0.974 6, and RMSEP = 0.391 5). The results showed that the chemometric model was able to predict the taste quality of Qingzhuan brick tea accurately and reliably and could provide a new method for evaluating the taste quality of Qingzhuan tea infusion.

Key words: Qingzhuan tea, tea infusion, regression equation, principal component analysis, correlation coefficient

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