• EI
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  • 食品科学与工程领域高质量科技期刊分级目录第一方阵T1
  • DOAJ
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  • 北大核心期刊
  • 中国核心学术期刊RCCSE
  • JST China
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  • 中国精品科技期刊
  • 中国农业核心期刊
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  • 中国科技核心期刊CSTPCD
  • 中国生物医学SinoMed
中国精品科技期刊2020
廖盛美,张清海,陶光灿,等. 基于风险分级技术的中国肉制品质量安全演化规律研究[J]. 食品工业科技,2024,45(17):1−9. doi: 10.13386/j.issn1002-0306.2023090329.
引用本文: 廖盛美,张清海,陶光灿,等. 基于风险分级技术的中国肉制品质量安全演化规律研究[J]. 食品工业科技,2024,45(17):1−9. 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): 1−9. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023090329.
Citation: 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): 1−9. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023090329.

基于风险分级技术的中国肉制品质量安全演化规律研究

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

  • 摘要: 对肉制品中的风险物质进行风险分级,探讨风险物的时空分布规律。采用熵值法计算流通、生产和餐饮环节中风险物的风险大小,并采用二八原则对风险物进行了分类,利用描述性统计方法,对肉制品生产环节进行时空分布规律的研究;通过全局和部分的关联分析,研究了高风险、较高风险物质全国空间分布的特点。生产和流通环节中的高风险物质是N-二甲基亚硝胺、苯并a芘、镉、过氧化值、新红、亚硝酸盐、砷、汞、大肠菌群、菌落总数,餐饮环节中的较高风险物质是菌落总数;2017~2021年肉制品不合格率最高的是2017年,为0.21%,其次是2020年,为0.19%;各地区中不合格率最高的宁夏为0.30%,全国各省肉制品中高及较高风险物合格率只有砷、诱惑红和菌落总数存在全局空间相关性(P<0.05);局部相关分析时,只有砷、敌敌畏、铬、诱惑红和菌落总数存在高-高值聚集或低-低值聚集的现象。通过风险物分级等级及相关时间空间分布特征,提出有针对性的监管意见,对监管计划进行动态调整,为肉制品安全监管提供科学依据。

     

    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.

     

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