Evidence map›Paper›PMID 41683046›Full record

ArticleFoods (Basel, Switzerland)2026

Chemical Drivers of Flavor Variation Across Cultivars and Grades of Fujian White Tea Revealed by Integrated Volatile and Non-Volatile Metabolomics.

Fuli Zong, Zi Yang, Linping Xiao, Yan Tong, Lan Shen, Zhijie Dong, Jianwei Zhou, Huan Cheng, Wenjun Wang, Donghong Liu

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Fuli ZongCollege of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory of Agro-Food Resources and High-Value Utilization, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, China.
Zi YangInstitute of Food Science, HongSheng Beverage Group Co., Ltd., Hangzhou 311200, China.ORCID 0009-0005-8342-577X
Linping XiaoInstitute of Food Science, HongSheng Beverage Group Co., Ltd., Hangzhou 311200, China.
Yan TongInstitute of Food Science, HongSheng Beverage Group Co., Ltd., Hangzhou 311200, China.
Lan ShenInstitute of Food Science, HongSheng Beverage Group Co., Ltd., Hangzhou 311200, China.
Zhijie DongInstitute of Food Science, HongSheng Beverage Group Co., Ltd., Hangzhou 311200, China.
Jianwei ZhouFuture Food Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China.
Huan ChengCollege of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory of Agro-Food Resources and High-Value Utilization, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-1192-3228
Wenjun WangCollege of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory of Agro-Food Resources and High-Value Utilization, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, China.
Donghong LiuCollege of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory of Agro-Food Resources and High-Value Utilization, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, China.

Funding

The "Pioneer" and "Leading Goose" R&D Program of Zhejiang Province 2024C01248 (SD2)
6 · The paper itself

Abstract

Grade and cultivar are the important factors influencing white tea quality, but their relative metabolic contributions are not fully understood. Twelve white tea samples representing four major Fujian cultivars across three grades were analyzed using UHPLC-MS-based non-volatile metabolomics, HS-SPME-GC-MS volatile profiling, and sensory correlation analysis. In total, 47 non-volatile and 21 volatile markers were associated with grade differences, while 44 non-volatile and 26 volatile markers were linked to cultivar differences. Catechins and amino acids declined as grade decreased, whereas flavonol glycosides and gallic acid increased, accompanied by stronger astringency and reduced umami and sweetness. Aroma profiles showed a similar trend, with higher-grade teas dominated by floral notes and lower-grade teas exhibiting more herbal characteristics. Dimeric catechins, oxylipins, and aroma glycosides varied among cultivars. Volatile profiles separated the cultivars into two aroma groups: Fuding Dabai and Fuding Dahao showed more floral-fruity aromas, whereas Fuan Dabai and Zhenghe Dabai exhibited stronger herbal and aged aromas. Odor activity value analysis showed that linalool, geraniol, and (

Indexed as

cultivargrademetabolomicsnon-volatile metabolitesvolatile compoundswhite tea

Identifiers

PMID41683046
PMCPMC12896726

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.