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Review | Publishing Language: Chinese | Open Access

Progress in Application of Machine Learning in Meat Microbial Safety

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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Abstract

Meat is nutritious and highly susceptible to contamination by foodborne pathogens, spoilage bacteria and other harmful microorganisms, so that its food safety is of great concern. In recent years, machine learning methods have been extensively employed in the field of food safety. In this paper, we review the application of machine learning methods from two perspectives: detection and predictive modeling of harmful microorganisms in meat. This review also analyzes the limitations of machine learning methods at the present stage, and provides an outlook on their prospects in meat microbial safety.

CLC number: TS201.3 Document code: A Article ID: 1001-8123(2022)11-0036-06

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Meat Research
Pages 36-41

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Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

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Cite this article:
LIN Z, DONG Q. Progress in Application of Machine Learning in Meat Microbial Safety. Meat Research, 2022, 36(11): 36-41. https://doi.org/10.7506/rlyj1001-8123-20221009-134

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Received: 09 October 2022
Published: 30 November 2022
© China Meat Research Center 2022.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).