Evidence map›Paper›PMID 39594103›Full record

ArticleFoods (Basel, Switzerland)2024

Classification and Identification of Foodborne Bacteria in Beef by Utilising Surface-Enhanced Raman Spectroscopy Coupled with Chemometric Methods.

Huixin Zuo, Yingying Sun, Mingming Huang, Stephanie Marie Fowler, Jing Liu, Yimin Zhang, Yanwei Mao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Foods (Basel, Switzerland), 2024. 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

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.

  1. Review
  2. Recent Advancements in the SERS-Based Detection ofSensors (Basel, Switzerland) · 2026
    Review
  3. Advances in methods for rapid detection of Staphylococcus aureus and methicillin-resistant S. aureus.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
    Review
  4. Article
  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.

Huixin ZuoCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Yingying SunCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Mingming HuangCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Stephanie Marie FowlerNSW Department of Primary Industries, Centre for Red Meat and Sheep Development, P.O. Box 129, Cowra, NSW 2794, Australia.
Jing LiuCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Yimin ZhangCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Yanwei MaoCollege of Food Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.

Funding

a special intergovernmental project for international cooperation in Science, Technology, and Innovation 2019YFE0103800China Agriculture Research System of MOF and MARA CARS-37special fund for innovation team of modern Agricultural Industrial Technology system in Shan-dong Province SDAIT-09-09
6 · The paper itself

Abstract

The detection and classification of foodborne pathogenic bacteria is crucial for food safety monitoring, consequently requiring rapid, accurate and sensitive methods. In this study, the surface-enhanced Raman spectroscopy (SERS) technique coupled with chemometrics methods was used to detect and classify six kinds of foodborne pathogenic bacteria, including

Indexed as

bacterial typingchemometricsclassification identificationfoodborne pathogenic bacteriasilver nanoparticlessurface-enhanced Raman spectroscopy

Identifiers

PMID39594103
PMCPMC11593597

What OpenQuestion holds

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LicenceCC BY
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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.