Insight into the effect of cultivar and altitude on the identification of EnshiYulu tea grade in untargeted metabolomics analysis

被引:14
作者
Zou, Dan [1 ]
Yin, Xiao-Li [1 ]
Gu, Hui-Wen [1 ]
Peng, Zhi-Xin [1 ]
Ding, Baomiao [1 ]
Li, Zhenshun [1 ]
Hu, Xian-Chun [1 ]
Long, Wanjun [2 ]
Fu, Haiyan [2 ]
She, Yuanbin [3 ]
机构
[1] Yangtze Univ, Coll Life Sci, Coll Chem & Environm Engn, Coll Hort & Gardening, Jingzhou 434025, Peoples R China
[2] South Cent Univ Nationalities, Modernizat Engn Technol Res Ctr Ethn Minor Med Hub, Sch Pharmaceut Sci, Wuhan 430074, Peoples R China
[3] Zhejiang Univ Technol, Coll Chem Engn, Hangzhou 310014, Peoples R China
基金
中国国家自然科学基金;
关键词
Green tea; UPLC-Triple-TOF/MS; Metabolomics; Grade discrimination; GREEN TEA; QUALITY;
D O I
10.1016/j.foodchem.2023.137768
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
The accurate identification of tea grade is crucial to the quality control of tea. However, existing methods lack sufficient generalization ability in identifying tea grades due to the effect of temporal and spatial factors. In this study, we analyzed the effect of cultivar and altitude on EnshiYulu (ESYL) tea grades and established a robust model to evaluate their quality. Principal component analysis (PCA) revealed that differences in variety and elevation can mask grade differences. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) was used for grade identification of samples from different altitudes. For ESYL tea samples above and below 800 m altitude, 75 and 35 grade differentiated metabolites were discovered, with 14 common differentiated metabolites. Based on reconstructed OPLS-DA models, the grades of multi-altitude sources ESYL were discriminated with a rate > 85%. These results demonstrate the potential of a grade discrimination model based on common differential metabolites, which exhibits generalization ability.
引用
收藏
页数:9
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