Evidence map›Paper›PMID 39606743›Full record

ArticleFood chemistry: X2024

Characterization of the influence of extraction factors on instant Pu-erh tea: Focusing on changes in sensory quality and aroma profile.

Guohe Chen, Yajie Xue, Guangmei Zhu, He Xie, Jing Zhang, Wanling Xiao, Chuyi He, Jianan Huang, Zhonghua Liu, Chao Wang

Abstract read
In one paragraph

Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Guohe ChenKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Yajie XueKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Guangmei ZhuKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
He XieKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Jing ZhangKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Wanling XiaoKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Chuyi HeKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Jianan HuangKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Zhonghua LiuKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.
Chao WangKey Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha 410128, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study is to explore the influence of extraction factors, including extraction temperatures, extraction time, and tea-water ratios, on the sensory quality and aroma characteristics of instant Pu-erh tea (IPET). Sensory evaluation, quantitative descriptive analysis (QDA) and HS-SPME-GC × GC-TOF/MS were utilized for analysis. The result showed that the optimal process condition of IPET was a tea-to-water ratio 1:8, an extraction temperature 75 °C, and an extraction time 60 min. A total of 235 volatile compounds were identified and 65 key odor-active compounds with ROAV>1 in all samples. Based VIP > 1, 19 key differential odor-active compounds were identified, including linalool oxide I, 1-dodecanol, linalool oxide II, etc. Further Pearson correlation analysis of key differential odor-active compounds and aroma characteristics showed that positive correlations between woody and ethyl nonanoate and 1-dodecanol, and between herbal and 1-methylnaphthalene. This research provides theoretical support for the production of high-quality IPET.

Indexed as

HS-SPME-GC × GC-TOF/MSInstant Pu-erh teaKey odor-active compoundsRelative odor activity value

Identifiers

PMID39606743
PMCPMC11599999

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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.