Evidence map›Paper›PMID 36677425›Full record

ArticleMicroorganisms2023

Distinct Microbiotas Are Associated with Different Production Lines in the Cutting Room of a Swine Slaughterhouse.

Fanie Shedleur-Bourguignon, Tom Duchemin, William P Thériault, Jessie Longpré, Alexandre Thibodeau, Mounia N Hocine, Philippe Fravalo

Open access · goldAbstract read
In one paragraph

Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.4field-weighted citation impact, top 13% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

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  5. Review
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

7 authors at 3 institutions in 2 countries.

Fanie Shedleur-BourguignonNSERC Industrial Research Chair in Meat Safety (CRSV), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.ORCID 0000-0002-3196-5177
Tom DucheminMESuRS Laboratory (Modelling, Epidemiology and Surveillance of Health Risks), Conservatoire National des Arts et Métiers (Cnam), 75003 Paris, France.ORCID 0000-0002-9131-8705
William P ThériaultNSERC Industrial Research Chair in Meat Safety (CRSV), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
Jessie LongpréF. Ménard, Division d'Olymel s.e.c., Ange-Gardien, QC J0E 1E0, Canada.ORCID 0000-0001-6316-078X
Alexandre ThibodeauNSERC Industrial Research Chair in Meat Safety (CRSV), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
Mounia N HocineMESuRS Laboratory (Modelling, Epidemiology and Surveillance of Health Risks), Conservatoire National des Arts et Métiers (Cnam), 75003 Paris, France.
Philippe FravaloLe Conservatoire National des Arts et Métiers (Cnam), 75003 Paris, France.
Conservatoire National des Arts et Métiers · FRNatural Sciences and Engineering Research Council of Canada · CAF. Ménard (Canada) · CA

Funding

Natural Sciences and Engineering Research Council of Canada RDCPJ 520873-17
6 · The paper itself

Abstract

The microorganisms found on fresh, raw meat cuts at a slaughterhouse can influence the meat's safety and spoilage patterns along further stages of processing. However, little is known about the general microbial ecology of the production environment of slaughterhouses. We used 16s rRNA sequencing and diversity analysis to characterize the microbiota heterogeneity on conveyor belt surfaces in the cutting room of a swine slaughterhouse from different production lines (each associated with a particular piece/cut of meat). Variation of the microbiota over a period of time (six visits) was also evaluated. Significant differences of alpha and beta diversity were found between the different visits and between the different production lines. Bacterial genera indicative of each visit and production line were also identified. We then created random forest models that, based on the microbiota of each sample, allowed us to predict with 94% accuracy to which visit a sample belonged and to predict with 88% accuracy from which production line it was taken. Our results suggest a possible influence of meat cut on processing surface microbiotas, which could lead to better prevention, surveillance, and control of microbial contamination of meat during processing.

Indexed as

16S rRNA sequencingcutting roomproduction linesrandom forestswine slaughterhouse

Identifiers

PMID36677425
PMCPMC9862343
OpenAlexW4313499926

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.