Evidence map›Paper›PMID 38893413›Full record

ArticleMolecules (Basel, Switzerland)2024

Characterization of Key Odor-Active Compounds in Draft Beers for the Chinese Market Using Molecular Sensory Science Approaches.

Yu Zhang, Sinuo Li, Qi Meng, Huanlu Song, Xiaojun Wang

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 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

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

5 authors.

Yu ZhangLaboratory of Molecular Sensory Science, School of Food and Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.
Sinuo LiLaboratory of Molecular Sensory Science, School of Food and Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.
Qi MengLaboratory of Molecular Sensory Science, School of Food and Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.
Huanlu SongLaboratory of Molecular Sensory Science, School of Food and Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.ORCID 0000-0001-8513-3299
Xiaojun WangCollege of Food Science and Technology, Yunnan Agricultural University, Kunming 650201, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Beer is a popular alcoholic beverage worldwide. However, limited research has been conducted on identifying key odor-active components in lager-type draft beers for the Chinese market. Therefore, this study aims to elucidate the odor characteristics of the four most popular draft beer brands through a sensory evaluation and an electronic nose. Subsequently, the four draft beers were analyzed through solid-phase microextraction and liquid-liquid extraction using a two-dimensional comprehensive gas chromatography-olfactometry-mass spectrometry analysis (GC×GC-O-MS). Fifty-five volatile odor compounds were detected through GC×GC-O-MS. Through an Aroma Extract Dilution Analysis, 22 key odor-active compounds with flavor dilution factors ≥ 16 were identified, with 11 compounds having odor activity values > one. An electronic nose analysis revealed significant disparities in the odor characteristics of the four samples, enabling their distinct identification. These findings help us to better understand the flavor characteristics of draft beer and the stylistic differences between different brands of products and provide a theoretical basis for objectively evaluating the quality differences between different brands of draft beer.

Indexed as

BeerGas Chromatography-Mass SpectrometryOdorantsVolatile Organic CompoundsChinaElectronic NoseFlavoring AgentsHumansLiquid-Liquid ExtractionOlfactometrySolid Phase MicroextractionFlavoring AgentsVolatile Organic Compoundsaroma extraction dilution analysisdraft beerelectronic noseodor-active compoundsensory evaluationtwo-dimensional comprehensive gas chromatography–olfactometry–mass spectrometry analysis

Identifiers

PMID38893413
PMCPMC11173443

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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.