Aroma differences and labeled vintage discrimination of commercial Chenxiang Tieguanyin from different production years

To characterize sensory differences among commercially available Chenxiang Tieguanyin with different labeled vintages and establish an objective discrimination method, Tieguanyin samples labeled from 5 to 40 years were analyzed using chemometrics and molecular sensory approaches. Amino acids and ester-type catechins decreased significantly with increasing labeled vintage, whereas theabrownin content increased steadily. Volatile profiles remained relatively stable between 10 and 25 years, while aroma characteristics gradually shifted from floral/fruity to aged, woody, and medicinal attributes, accompanied by enhanced mellowness and smoothness. A total of 22 key differential volatiles associated with labeled vintage were identified. Molecular docking and aroma recombination experiments were combined to systematically validate their contribution to the typical aged aroma of Tieguanyin. Among the machine-learning models, the convolutional neural network (CNN) exhibited the best classification performance, achieving 92.86% accuracy. This study provides an effective strategy for quality evaluation and labeled vintage discrimination of Chenxiang Tieguanyin.

Authors

Institutions

Publication Details

Journal
npj Science of Food
Published
2026-07-28
DOI
https://doi.org/10.1038/s41538-026-01025-w
Primary Topic
Fermentation and Sensory Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Aroma differences and labeled vintage discrimination of commercial Chenxiang Tieguanyin from different production years

Yuqiong Guo, Caiyun Tian, Chengzhe Zhou, Shuaibo Shao et al.
npj Science of Food
Fermentation and Sensory Analysis
article

Aroma differences and labeled vintage discrimination of commercial Chenxiang Tieguanyin from different production years

Yuqiong Guo, Caiyun Tian, Chengzhe Zhou, Shuaibo Shao, Zhong Wang, Zhendong Zhang, Anru Zheng, Jiaxin Fang, Zhenhan Rui, Xiaowen Hu, Zhelin Wan
article en

Abstract

To characterize sensory differences among commercially available Chenxiang Tieguanyin with different labeled vintages and establish an objective discrimination method, Tieguanyin samples labeled from 5 to 40 years were analyzed using chemometrics and molecular sensory approaches. Amino acids and ester-type catechins decreased significantly with increasing labeled vintage, whereas theabrownin content increased steadily. Volatile profiles remained relatively stable between 10 and 25 years, while aroma characteristics gradually shifted from floral/fruity to aged, woody, and medicinal attributes, accompanied by enhanced mellowness and smoothness. A total of 22 key differential volatiles associated with labeled vintage were identified. Molecular docking and aroma recombination experiments were combined to systematically validate their contribution to the typical aged aroma of Tieguanyin. Among the machine-learning models, the convolutional neural network (CNN) exhibited the best classification performance, achieving 92.86% accuracy. This study provides an effective strategy for quality evaluation and labeled vintage discrimination of Chenxiang Tieguanyin.

npj Science of Food
Fujian Agriculture and Forestry University (CN)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Fermentation and Sensory Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Aroma differences and labeled vintage discrimination of commercial Chenxiang Tieguanyin from different production years — Yuqiong Guo, Caiyun Tian, et al. · npj Science of Food (2026) | TGRS Research Map | TGRS