Evidence map›Paper›PMID 31817626›Full record

ArticleMolecules (Basel, Switzerland)2019

Suppressive Interaction Approach for Masking Stale Note of Instant Ripened Pu-Erh Tea Products.

Ting Zhang, Hui Ni, Xu-Jian Qiu, Ting Li, Liang-Zhen Zhang, Li-Jun Li, Ze-Dong Jiang, Qing-Biao Li, Feng Chen, Fu-Ping Zheng

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

10 authors.

Ting ZhangBeijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Beijing 100048, China.ORCID 0000-0002-6813-633X
Hui NiBeijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Beijing 100048, China.
Xu-Jian QiuCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.
Ting LiCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.
Liang-Zhen ZhangCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.
Li-Jun LiCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.
Ze-Dong JiangCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.ORCID 0000-0001-7579-3680
Qing-Biao LiCollege of Food and Biological Engineering, Jimei University, Xiamen 361021, China.
Feng ChenBeijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Beijing 100048, China.
Fu-Ping ZhengBeijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Beijing 100048, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The unpleasant stale note is a negative factor hindering the consumption of instant ripened Pu-erh tea products. This study focused on investigating volatile chemicals in instant ripened Pu-erh tea that could mask the stale note via sensory evaluation, gas chromatography-mass spectrometry (GC-MS), and gas chromatography-olfactometry (GC-O) analyses. GC-MS and GC-O analyses showed that linalool, linalool oxides,

Indexed as

Acyclic MonoterpenesAnisolesCyclohexanolsGas Chromatography-Mass SpectrometryPlant ExtractsTeaTriphenylmethyl CompoundsAcyclic MonoterpenesanisoleAnisolesCyclohexanolslinaloollinalool oxidePlant ExtractsTeaTriphenylmethyl Compoundsinstant ripened Pu-erh teamaskingsensory evaluationstale notesuppressive interaction

Identifiers

PMID31817626
PMCPMC6943613

What OpenQuestion holds

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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.