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ORIGINAL RESEARCH article

Front. Plant Sci.

Sec. Plant Metabolism and Chemodiversity

Volume 16 - 2025 | doi: 10.3389/fpls.2025.1701011

This article is part of the Research TopicSecondary Metabolites in Beverage Plant: Metabolism, Function, and RegulationView all 7 articles

Determining the influence of tree age on tea quality-related metabolites in Camellia tachangensis var. remotiserrata by integrating metabolomic and transcriptomic analyses

Provisionally accepted
Zhuorong  ShiZhuorong Shi1Yu  CaiYu Cai2Ying  TianYing Tian1,3Yuting  ZhangYuting Zhang1Junhao  ShaoJunhao Shao1Jianfeng  LiuJianfeng Liu1Qingwei  ZhangQingwei Zhang1*
  • 1Southwest University, Chongqing, China
  • 2Chongqing Haotian Eco-Agri Tech Co., Ltd., Chongqing, China
  • 3Langzhong Bureau of Agriculture, Nanchong, China

The final, formatted version of the article will be published soon.

While tea tree age is generally considered to influence the quality of black tea, the relationship between tree age and tea quality is unclear. We examine relationships between tree age and key metabolite contents related to tea quality in new leaves of the wild arbor-type tea Camellia tachangensis var. remotiserrata. We report tree age to directly affect metabolic divergence in leaves in spring. Compared with 10-y-old trees, the leaves of 80-and 800-y-old trees have higher flavonoid contents; total soluble sugar, polyphenol, and total amino acid contents are largely unaffected by tree age, but levels of specific amino acids (e.g., theanine, glutamate, and isoleucine) decline in older trees. Metabolome analysis reveals 202 of 1041 identified compounds (primarily flavonoids, phenolic acids, organic acids, tannins, lignans, and coumarins) to exhibit significant age-dependent changes. With increased tree age, common sugar compounds (e.g., glucose, maltose) and certain lipids (e.g., 1-alpha-linolenoyl-glycerol) contents increase in leaves. Levels of relatively abundant phenolic acids (e.g., ferulic acid-4-O-glucoside, p-coumaric acid-4-O-glucoside) and flavonoids (e.g., luteolin-3'-O-glucoside, apigenin-4'-O-glucoside) decrease, while catechin content increases significantly, particularly epigallocatechin gallate derivatives. These metabolic changes align with flavor profiles of tea harvested from different tree ages: infusions from older trees are significantly less bitter and astringent and present apparent sweet and umami characteristics. Transcriptome analysis reveals overall gene expression profiles to vary with tree age, especially for genes involved in secondary metabolite biosynthesis. Focusing on the phenylpropanoid biosynthetic pathway, the expression of the genes PAL, C4H, and LAR is significantly upregulated with increased tree age, and that of flavanone 3-hydroxylase and F3GT is downregulated. Conjoint analysis of metabolome and transcriptome data reveals expression patterns of specific enzyme-encoding genes to correlate with changes in phenolic acid, flavonoid, and tannin compounds. Transcription factors (e.g., MYB, ERF, NAC) are closely associated with changes in these compounds. These results improve our understanding of relationships between tree age and tea quality. A limitation of this study is that sampling was confined to the spring season of 2023. To more definitively prove that tree age influences tea quality, sampling across different years and a broader range of conditions is essential.

Keywords: Black tea quality, Tree age, Metabolome, Phenylpropanoid metabolic pathway, Transcriptional factor

Received: 08 Sep 2025; Accepted: 15 Oct 2025.

Copyright: © 2025 Shi, Cai, Tian, Zhang, Shao, Liu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Qingwei Zhang, qwzhang18@swu.edu.cn

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