Research on the Evolutionary Patterns of Quality and Safety of Meat Product in China Based on Risk Ranking Technology

LIAO Shengmei; ZHANG Qinghai; TAO Guangcan; HU Kang

doi:10.13386/j.issn1002-0306.2023090329

Volume 45 Issue 17

Aug. 2024

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Science and Technology of Food Industry > 2024 > 45(17): 232-240. > DOI: 10.13386/j.issn1002-0306.2023090329

LIAO Shengmei, ZHANG Qinghai, TAO Guangcan, et al. Research on the Evolutionary Patterns of Quality and Safety of Meat Product in China Based on Risk Ranking Technology[J]. Science and Technology of Food Industry, 2024, 45(17): 232−240. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023090329.

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Research on the Evolutionary Patterns of Quality and Safety of Meat Product in China Based on Risk Ranking Technology

LIAO Shengmei^{1, 2,},
ZHANG Qinghai¹,
TAO Guangcan^{1, 2, ,},
HU Kang³

1.
School of Public Health, Guizhou Medical University, Guiyang 561113, China
2.
College of Food Science and Engineering, Guiyang University, Guiyang 550005, China
3.
National Institutes for Food and Drug Control, Beijing 102629, China

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Received Date: October 08, 2023
Available Online: July 01, 2024

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Abstract

Abstract

This study conducted risk ranking for risk substances present in meat products, exploring the temporal and spatial distribution patterns of these risk items. The entropy weight method was used to calculate the risk values of different risk substances in circulation, production and catering links, and the risk substances were ranked by the 80-20 principle. The descriptive statistical method was used to explore the temporal and spatial distribution patterns of meat product production links. Through global and local correlation analysis, the characteristics of the spatial distribution of high-risk and relatively high-risk substances nationwide were studied. The high-risk substances in the production and circulation links were N-dimethylnitrosamine, benzo[a]pyrene, cadmium, peroxide value, new red, nitrite, arsenic, mercury, coliforms, and total bacteria number, while the relatively high-risk substances in the catering link was the total bacteria number. The highest meat product unqualified rate was 0.21% in 2017, followed by 0.19% in 2020. In various regions, the highest unqualified rate was in Ningxia, at 0.30%. For meat products from all provinces nationwide, the qualified rates for high and relatively high-risk substances only exhibited global spatial correlation for arsenic, allura red, and total bacterial count (P<0.05). In local correlation analysis, only arsenic, dichlorvos, chromium, allura red, and total bacteria number, exhibited high-high or low-low value clustering phenomena. Through the classification of risk substances and their associated temporal and spatial distribution characteristics targeted regulatory suggestions are proposed, opinions and regulatory plans are dynamically adjusted, providing a scientific basis for meat product safety supervision.
- meat products,
- entropy weight method,
- risk ranking,
- spatial correlation,
- evolution pattern

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