Evidence map›Paper›PMID 42459384›Full record

ArticleFrontiers in plant science2026

Metabolomics-based elucidation of the chemical basis under-lying seasonal variations in sensory quality of Goldsands Black Tea.

Jialin Chen, Binghong Liu, Jiaxin Li, Yixin Chen, Yide Zhou, Hui Meng, Xindong Tan, Peng Zheng, Binmei Sun, Hongbo Zhao and 1 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 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

11 authors.

Jialin Chen *Country College of Horticulture, South China Agricultural University, Guangzhou, China.
Binghong Liu *Country College of Horticulture, South China Agricultural University, Guangzhou, China.
Jiaxin Li *Country College of Horticulture, South China Agricultural University, Guangzhou, China.
Yixin ChenCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Yide ZhouCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Hui MengCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Xindong TanCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Peng ZhengCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Binmei SunCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Hongbo ZhaoCountry College of Horticulture, South China Agricultural University, Guangzhou, China.
Shaoqun LiuCountry College of Horticulture, South China Agricultural University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Goldsands Black Tea (GBT), a premium black tea from northern Guangdong, exhibits seasonal sensory variations with unclear chemical basis. This study integrated sensory evaluation, volatile and untargeted metabolomics to characterize the flavor profiles of spring, summer, and autumn GBTs. Spring tea achieved the highest sensory score, characterized by sweet aroma and fresh, mellow taste; autumn tea presented complex floral-fruity notes; summer tea showed pronounced astringency. Volatile metabolomics identified 66 compounds, with nine showing significant seasonal differences. Five compounds-geraniol, methyl salicylate, linalool, (

Indexed as

flavor chemistryGoldsands Teaseasonal variationsensory qualityuntargeted metabolomicsvolatile metabolomics

Identifiers

PMID42459384
PMCPMC13369139

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.