Evidence map›Paper›PMID 37860145›Full record

ArticleCurrent research in food science2023

Design and development of a rapid meat detection system based on RPA-CRISPR/Cas12a-LFD.

Yaqun Liu, Liyun Lin, Huagui Wei, Qiulan Luo, Peikui Yang, Mouquan Liu, Zhonghe Wang, Xianghui Zou, Hui Zhu, Guangcai Zha and 3 more

Open access · goldAbstract read
In one paragraph

Article in Current research in food science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 12 citations in OpenAlex.

  1. Application of Omics in Donkey Meat Research: A Review.Animals : an open access journal from MDPI · 2025
    Review
  2. 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

13 authors at 2 institutions in 1 country.

Yaqun LiuSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Liyun LinSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Huagui WeiShool of Laboratory Medicine, Youjiang Medical University for Nationalities, Baise, Guangxi, PR China.
Qiulan LuoSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Peikui YangSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Mouquan LiuSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Zhonghe WangSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Xianghui ZouSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Hui ZhuSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Guangcai ZhaSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Junjun SunSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Yuzhong ZhengSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Min LinSchool of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, Guangdong, PR China.
Hanshan Normal University · CNAffiliated Hospital of Youjiang Medical University for Nationalities · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, meat adulteration safety incidents have occurred frequently, triggering widespread attention and discussion. Although there are a variety of meat quality identification methods, conventional assays require high standards for personnel and experimental conditions and are not suitable for on-site testing. Therefore, there is an urgent need for a rapid, sensitive, high specificity and high sensitivity on-site meat detection method. This study is the first to apply RPA combined with CRISPR/Cas12a technology to the field of multiple meat identification. The system developed by parameter optimization can achieve specific detection of chicken, duck, beef, pork and lamb with a minimum target sequence copy number as low as 1 × 10

Indexed as

CRISPR/Cas12aLFDMeat identificationRPA

Identifiers

PMID37860145
PMCPMC10582345
OpenAlexW4387378381

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.