Evidence map›Paper›PMID 36203160›Full record

ArticleBMC microbiology2022

The MBS microbial rapid detection system for rapid detection of major pathogenic bacteria in feed: comparison with plate counting method.

Linlin Jiang, Beibei Zhang, Shuitao Liu, Lianqin Zhu, Fenghua Zhu

Abstract read
In one paragraph

Article in BMC microbiology, 2022. 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
–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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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.

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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.

Linlin Jiang *College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, People's Republic of China.
Beibei Zhang *College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, People's Republic of China.
Shuitao Liu *College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, People's Republic of China.
Lianqin Zhu *College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, People's Republic of China. zhulianqin1963@163.com.
Fenghua Zhu *College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, People's Republic of China. zhufenghua1029@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current methods for detecting pathogenic bacteria in feed require high technique and take a long time. The Micro Biological Survey (MBS) rapid detection system is a simple, economical and rapid microbial detection method. The purpose of this experiment was to compare the detection of Escherichia coli (E. coli), Salmonella, Staphylococcus aureus (S. aureus), Listeria monocytogenes (LM), coliform (COLI) and total viable count (TVC) in feed by the MBS rapid microbial detection system and plate counting method (PCM). The results showed that the limit of quantitation, recovery rate and coefficient of variation of the MBS microbial rapid detection system are better than the plate counting method. When detecting the pathogenic bacteria content in artificially contaminated feed, the MBS rapid microbial detection system was positively correlated with the PCM. When the MBS microbial rapid detection system and PCM were used to detect the collected real feed samples, there was no significant difference in the detection results of the two methods in most of the feed samples. In summary, the MBS microbial rapid detection system is the most convenient and rapid detection method and is suitable for promotion and application in production lines.

Indexed as

Escherichia coli O157Listeria monocytogenesStaphylococcal InfectionsColony Count, MicrobialFood MicrobiologyHumansSalmonellaStaphylococcus aureusFeedMBS microbial rapid detection systemPathogenic bacteriaPCM

Identifiers

PMID36203160
PMCPMC9541081

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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.