Evidence map›Paper›PMID 39319635›Full record

ArticlePest management science2025

Rapid and equipment-free identification of papaya mealybug Paracoccus marginatus based on RPA-CRISPR/Cas12a.

Yan-Ting Chen, Meng-Zhu Shi, Yan Chen, Jian-Wei Zhao, Xiu-Juan Yang, Jian-Wei Fu, Nicolas Desneux, Jian-Yu Li

Abstract read
In one paragraph

Article in Pest management science, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. A Species-SpecificBiology · 2026
    Article
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

8 authors.

Yan-Ting ChenFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.ORCID https://orcid.org/0000-0002-2840-4141
Meng-Zhu ShiFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Yan ChenFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Jian-Wei ZhaoFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Xiu-Juan YangFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Jian-Wei FuInstitute of Quality Standards and Testing Technology for Agro-Products, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Nicolas DesneuxUniversité Côte d'Azur, French National Research Institute for Agriculture, Food & Environment, CNRS, UMR ISA, Nice, France.
Jian-Yu LiFujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, China.ORCID https://orcid.org/0000-0002-6525-8251

Funding

'5511' Collaborative Innovation Project XTCXGC2021011'5511' Collaborative Innovation Project XTCXGC2021017Basic Scientific Research for Public Welfare Research Institutes of Fujian Province 2023R1022001China Scholarship CouncilNational Key Research and Development Program of China 2021YFC2600400Project of Fujian Academy of Agricultural Sciences YCZX202406Project of Fujian Academy of Agricultural Sciences ZYTS2023010
6 · The paper itself

Abstract

backgroundParacoccus marginatus has invaded many countries, spreading rapidly and causing significant economic losses to crops. Accurate detection during the monitoring process is critical to prevent its expansion into new areas, therefore it is necessary to develop efficient and reliable detection methods. Traditional detection methods are time-consuming and instrument-dependent owing to the morphological similarities and small sizes of P. marginatus and other mealybugs, therefore establishing an efficient, rapid, and sensitive method for field detection in resource-limited settings is critical.

resultsA sensitive and rapid detection system was developed to detect P. marginatus using recombinase polymerase amplification (RPA) combined with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a. The RPA-CRISPR/Cas12a assay distinguished P. marginatus from 10 other mealybugs. The entire process can be completed in approximately an hour, and the identification results can be determined by the naked eye using lateral flow strips or a portable mini-UV torch. A method was developed to extract DNA from P. marginatus within 5 min. This method was combined with the RPA-CRISPR/Cas12a assay to achieve rapid and simple detection. In addition, two portable thermos cups with temperature displays were used to maintain the reagents and assay reactions in the field.

conclusionThis assay represents the first application of portable and easily available items (mini-UV torch and thermos cup) based on the combination of RPA and CRISPR/Cas12a for rapid pest detection. This method is rapid, highly specific, and instrument-flexible, allowing for the early monitoring of P. marginatus in the field. This study provides guidance for the development of suitable management strategies. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Indexed as

CRISPR-Cas SystemsAnimalsCaricaNucleic Acid Amplification TechniquesParacoccusRecombinasesRecombinasesCRISPR/Cas12afluorescence visualizationlateral flow strippapaya mealybugrecombinase polymerase amplification (RPA)

Identifiers

PMID39319635
PMCPMC11632207

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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.