1. A Risk Assessment Method of Chemical Contaminants in Meat Products Based on Improved Matter-Element Extension Model
- Author
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DOU Haifeng, CHEN Yi, WU Caixia, GUO Wei, ZHANG Feng
- Subjects
risk assessment ,matter-element extension model ,best-worst method ,meat products ,chemical contaminants ,Food processing and manufacture ,TP368-456 - Abstract
It is of great importance to accurately assess the safety risk of chemical contaminants in meat products as one of the causes of food safety problems, which could provide a basis for food safety supervision. Considering the advantages and disadvantages of the existing risk assessment methods, a risk assessment method of chemical contaminants in meat products based on the improved matter-element extension model was proposed, which takes into account the maximum limit of each contaminant and the statistical distribution pattern of sampling results, and selects the detection rate, failure rate, failure degree, mean contents and coefficient of variation of contaminants as risk evaluation indexes. In addition, the weight of each evaluation index was determined by introducing the best-worst method, and the risk level of each contaminant was determined from the asymmetric closeness calculated based on the improved matter-element extension model. Moreover, a case study was conducted with the sampling results of five food additives and four heavy metal elements in meat products in a certain province of China in 2018, and a comparative experiment was conducted with the commonly used Nemerow index evaluation method. The results of both methods showed basically identical rank order of the nine chemical contaminants, and the results of the method developed in this study were distributed at level I–V, while those of the Nemerow index method were concentrated at level III–V. Our method can effectively highlight the difference in the risk of different contaminants, and the results from it comply more with reality, which provide a scientific basis for the development of pollutant sampling plans and the optimization of detection resources.
- Published
- 2023
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