Evidence map›Paper›PMID 39123541›Full record

ArticleFoods (Basel, Switzerland)2024

The Light-Intensity-Affected Aroma Components of Green Tea during Leaf Spreading.

Youyue He, Shujing Liu, Yuzhong Kang, Rajiv Periakaruppan, Jing Zhuang, Yuhua Wang, Xuan Chen, Xinqiu Liu, Xinghui Li

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

9 authors.

Youyue HeCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.
Shujing LiuCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.
Yuzhong KangCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.
Rajiv PeriakaruppanDepartment of Biotechnology, PSG College of Arts & Science, Coimbatore 641 014, India.ORCID 0000-0002-5792-818X
Jing ZhuangCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-6960-5217
Yuhua WangCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.
Xuan ChenCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-5553-3638
Xinqiu LiuCollege of Humanities and Social Development, Nanjing Agricultural University, Nanjing 210095, China.
Xinghui LiCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.

Funding

the development of new products from summer and autumn tea in Wen County 2023-X.QKJ-09the improvement project of efficient production technology capacity in Wen County's character-istic industries 22CX8NA034the integrative innovation and demonstration of technology for improving quality and efficiency in the tea industry of Shandong Province 2021TZXD009the national key research and development program of China 2022YFD1601804the research and demonstration program of key technologies for the construction of Gansu's characteristic tea industry chain 2023--X.QKJ--02the research and demonstration project of key technologies of tea garden photovoltaic power generation HNKJ22-H135
6 · The paper itself

Abstract

Leaf spreading is a key processing step that affects the aroma formation of green tea. The effects of a single-light wavelength on the aroma and taste of tea have been extensively studied. Less attention has been paid to the effect of different complex light intensities on the formation of green tea's volatile aroma during leaf spreading. The current study was designed to evaluate how leaf spreading under different complex light intensities relates to the quality of green tea. Using headspace solid-phase micro-extraction and gas chromatography-mass spectrometry (HS-SPME/GC-MS), volatile flavor compounds in green tea were analyzed during leaf spreading in five different light conditions. Multivariate statistical analysis and odor activity values (OAVs) were used to classify these samples and identify key odors. Eight distinct groups, including ninety volatile compounds, were detected. The most prevalent volatile compounds found in green tea samples were hydrocarbons and alcohols, which accounted for 29% and 22% of the total volatile compounds, respectively. Fourteen volatile compounds (OAV > 1) were identified as key active differential odorants. The chestnut-like aroma in green tea was mostly derived from 3-methyl-butanal and linalool, which were significantly accumulated in medium-intensity light (ML).

Indexed as

green tealeaf spreadinglight intensityodor activity valuesensory qualityvolatile substance

Identifiers

PMID39123541
PMCPMC11311319

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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.