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

Dan Zou; Xiao-Li Yin; Hui-Wen Gu; Zhi-Xin Peng; Baomiao Ding; Zhenshun Li; Xian-Chun Hu; Wanjun Long; Haiyan Fu; Yuanbin She

doi:10.1016/j.foodchem.2023.137768

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

Food Chem. 2024 Mar 15:436:137768. doi: 10.1016/j.foodchem.2023.137768. Epub 2023 Oct 14.

Authors

Dan Zou¹, Xiao-Li Yin², Hui-Wen Gu¹, Zhi-Xin Peng¹, Baomiao Ding¹, Zhenshun Li¹, Xian-Chun Hu¹, Wanjun Long³, Haiyan Fu⁴, Yuanbin She⁵

Affiliations

¹ College of Life Sciences, College of Chemistry and Environmental Engineering, College of Horticulture and Gardening, Yangtze University, Jingzhou 434025, China.
² College of Life Sciences, College of Chemistry and Environmental Engineering, College of Horticulture and Gardening, Yangtze University, Jingzhou 434025, China. Electronic address: yinxiaoli@yangtzeu.edu.cn.
³ The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan 430074, China.
⁴ The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan 430074, China. Electronic address: fuhaiyan@mail.scuec.edu.cn.
⁵ College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China. Electronic address: sheyb@zjut.edu.cn.

PMID: 37862999
DOI: 10.1016/j.foodchem.2023.137768

Abstract

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.

Keywords: Grade discrimination; Green tea; Metabolomics; UPLC-Triple-TOF/MS.

MeSH terms

Altitude*
Discriminant Analysis
Metabolomics / methods
Principal Component Analysis
Tea*

Substances

Tea