Advancing microbial food safety and hazard analysis through predictive mathematical modeling

Kumar, Vikram; Ahire, Jayesh J.; Taneja, Neetu Kumra

doi:10.1016/j.microb.2024.100049

Cited by 8 publications

References 61 publications

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Predictive modeling and risk assessment strategies for enhancing dairy product safety: A comprehensive review

Pahariya,

Shrivastav,

Goswami

et al. 2025

Food Safety and Health

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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.

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