Characterising volatiles in tea (Camellia sinensis). Part II: Untargeted and targeted approaches to multivariate analysis

文献类型： 外文期刊

第一作者： Lau, Hazel

作者： Lau, Hazel;Liu, Shao Quan;Xu, Yong Quan;Tan, Lay Peng;Zhang, Wen Lin;Lassabliere, Benjamin;Sun, Jingcan;Yu, Bin

作者机构：

关键词： Tea; Volatile; HS-SPME; SAFE; Multivariate statistics

期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：4.952； 五年影响因子：5.383 ）

ISSN： 0023-6438

年卷期： 2018 年 94 卷

页码：

收录情况： SCI

摘要： Using headspace-solid phase microextraction (HS-SPME) and solvent-assisted flavour evaporation (SAFE), the volatiles in five common types of teas (white, green, oolong, black and pu-erh teas) were extracted for GC-MS/FID analysis, and the major compounds in each tea were identified. Subsequently, untargeted and targeted approaches were used in principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) for further data interpretation. Confidence levels using the targeted approach were generally higher for sample classification. Therefore, this study offers a better methodology to improve the existing knowledge of tea volatiles.

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