{"title":"提高乳制品安全的预测建模和风险评估策略:综述","authors":"Prachi Pahariya, Awani Shrivastav, Tridib Kumar Goswami, Ruplal Choudhary","doi":"10.1002/fsh3.12084","DOIUrl":null,"url":null,"abstract":"<p>The dairy industry is a crucial part of the food sector, encompassing a wide range of raw, pre-processed, and post-processed dairy products. The concern about delivering safe dairy products is increasing due to the rise in pathogenic outbreaks associated with the dairy industry. To mitigate the risks associated with dairy products, risk assessment (RA) and predictive modeling play vital roles. This review article provides a comprehensive analysis of RA and predictive modeling in managing these risks. Risk assessment offers a structured approach to evaluate public health risks through hazard identification, hazard characterization, exposure assessment, and risk characterization. Predictive modeling complements RA by using scientific and mathematical methods to anticipate microbial behavior under various conditions, aiding in the prevention of contamination throughout the dairy supply chain. This article emphasizes the application of these tools in real-world scenarios to improve the accuracy of food safety predictions. In conclusion, integrating risk assessment with predictive modeling is essential for mitigating contamination risks and ensuring the safety and quality of dairy products. While significant advancements have been made, future research should focus on enhancing model precision through robust data sets and advanced machine learning, leading to more effective strategies that protect public health.</p>","PeriodicalId":100546,"journal":{"name":"Food Safety and Health","volume":"3 2","pages":"172-187"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fsh3.12084","citationCount":"0","resultStr":"{\"title\":\"Predictive modeling and risk assessment strategies for enhancing dairy product safety: A comprehensive review\",\"authors\":\"Prachi Pahariya, Awani Shrivastav, Tridib Kumar Goswami, Ruplal Choudhary\",\"doi\":\"10.1002/fsh3.12084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The dairy industry is a crucial part of the food sector, encompassing a wide range of raw, pre-processed, and post-processed dairy products. The concern about delivering safe dairy products is increasing due to the rise in pathogenic outbreaks associated with the dairy industry. To mitigate the risks associated with dairy products, risk assessment (RA) and predictive modeling play vital roles. This review article provides a comprehensive analysis of RA and predictive modeling in managing these risks. Risk assessment offers a structured approach to evaluate public health risks through hazard identification, hazard characterization, exposure assessment, and risk characterization. Predictive modeling complements RA by using scientific and mathematical methods to anticipate microbial behavior under various conditions, aiding in the prevention of contamination throughout the dairy supply chain. This article emphasizes the application of these tools in real-world scenarios to improve the accuracy of food safety predictions. In conclusion, integrating risk assessment with predictive modeling is essential for mitigating contamination risks and ensuring the safety and quality of dairy products. While significant advancements have been made, future research should focus on enhancing model precision through robust data sets and advanced machine learning, leading to more effective strategies that protect public health.</p>\",\"PeriodicalId\":100546,\"journal\":{\"name\":\"Food Safety and Health\",\"volume\":\"3 2\",\"pages\":\"172-187\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fsh3.12084\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Food Safety and Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/fsh3.12084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Safety and Health","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/fsh3.12084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive modeling and risk assessment strategies for enhancing dairy product safety: A comprehensive review
The dairy industry is a crucial part of the food sector, encompassing a wide range of raw, pre-processed, and post-processed dairy products. The concern about delivering safe dairy products is increasing due to the rise in pathogenic outbreaks associated with the dairy industry. To mitigate the risks associated with dairy products, risk assessment (RA) and predictive modeling play vital roles. This review article provides a comprehensive analysis of RA and predictive modeling in managing these risks. Risk assessment offers a structured approach to evaluate public health risks through hazard identification, hazard characterization, exposure assessment, and risk characterization. Predictive modeling complements RA by using scientific and mathematical methods to anticipate microbial behavior under various conditions, aiding in the prevention of contamination throughout the dairy supply chain. This article emphasizes the application of these tools in real-world scenarios to improve the accuracy of food safety predictions. In conclusion, integrating risk assessment with predictive modeling is essential for mitigating contamination risks and ensuring the safety and quality of dairy products. While significant advancements have been made, future research should focus on enhancing model precision through robust data sets and advanced machine learning, leading to more effective strategies that protect public health.