Evidence map›Paper›PMID 34574128›Full record

ArticleFoods (Basel, Switzerland)2021

Detection of Volatiles from Raw Beef Meat from Different Packaging Systems Using Solid-Phase Microextraction GC-Accurate Mass Spectrometry.

Debarati Bhadury, Yada Nolvachai, Philip J Marriott, Joanne Tanner, Kellie L Tuck

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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.

Debarati BhadurySchool of Chemistry, Monash University, Wellington Rd, Clayton, VIC 3800, Australia.
Yada NolvachaiAustralian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Rd, Clayton, VIC 3800, Australia.
Philip J MarriottAustralian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Rd, Clayton, VIC 3800, Australia.ORCID 0000-0001-5180-1041
Joanne TannerBioresource Processing Research Institute of Australia (BioPRIA), Department of Chemical Engineering, Monash University, Alliance Ln, Clayton, VIC 3800, Australia.ORCID 0000-0002-3318-1237
Kellie L TuckSchool of Chemistry, Monash University, Wellington Rd, Clayton, VIC 3800, Australia.ORCID 0000-0002-9104-3158

Funding

Meat and Livestock Australia N/A
6 · The paper itself

Abstract

The volatile profile of raw beef contains vital information related to meat quality and freshness. This qualitative study examines the effect of packaging system on the formation and release of volatile organic compounds (VOCs) from raw beef over time, relative to the packaging best before date (BBD). The three packaging systems investigated were modified atmospheric packaging, vacuum packaging, and cling-wrapped packaging. Porterhouse steak samples with the same BBD were analysed from 3 days before to 3 days after the BBD. VOCs were detected via preconcentration using solid-phase microextraction combined with gas chromatography-accurate mass quadrupole time-of-flight mass spectrometry. In total, 35 different VOCs were tentatively identified. Interestingly, there was no clear relationship of the VOCs detected between the three packaging systems, with only carbon disulphide and acetoin, both known volatiles of beef, detected in all three. This is the first study to investigate the effects of commercial packaging systems on VOC formation; it provides an understanding of the relationship of VOCs to the BBD that is essential for the development of on-pack freshness and quality sensors.

Indexed as

GC–accQTOFMSheadspacemeat qualityraw beefSPME

Identifiers

PMID34574128
PMCPMC8468586

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Registered trials

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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.