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    Home > Food News > Food Articles > Conference report-Professor Dong Qingli-A meta-analysis of the risk of typical pathogenic bacteria in meat

    Conference report-Professor Dong Qingli-A meta-analysis of the risk of typical pathogenic bacteria in meat

    • Last Update: 2021-10-09
    • Source: Internet
    • Author: User
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    Editor in charge: Food Science


    Professor Dong Qingli

    Institute of Food Quality and Safety, University of Shanghai for Science and Technology

    Doctor of Engineering in Food Science, is currently a professor and doctoral supervisor at the University of Shanghai for Science and Technology, and a visiting scholar from the Institute of Food Research (IFR) of the United Kingdom.


    Title

    Meta-analysis of the risk of typical pathogenic bacteria in meat

    Summary

    Meta-analysis is a statistical analysis method widely used in medical fields such as evidence-based nursing.


    Generally, it collects a large number of research results on a specific scientific issue and analyzes to achieve the purpose of integration
    .
    After years of development and evolution, the application field of Meta analysis has become more and more extensive, and it has significant advantages in systematic and quantitative statistical comprehensive analysis and comprehensive evaluation of multiple independent research results with the same research purpose
    .
    Our research group has applied this method to the Listeria monocytogenes contamination in meat products in China, the Salmonella spp.
    contamination in poultry in China , and the Salmonella enteritidis monophasic in the early stage .
    Variation resistance, Staphylococcus aureus contamination in cooked meat products in China, Staphylococcus aureus drug resistance and methicillin-resistant Staphylococcus aureus contamination in domestic foods, 3 species in China’s food The diarrheal Escherichia coli ( Escherichia coli ) pollution situation has been systematically studied, which provides important data support for the risk identification of microbial quantitative risk assessment
    .


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