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Quantitative microbiological risk assessment in food industry: Theory and practical application
Jeanne-Marie Membré1, Géraldine Boué1
1SECALIM, INRA, Oniris, Université Bretagne Loire, 44307 Nantes, France.
Food Research International (Ottawa, Ont.)
|March 28, 2018
Summary
Quantitative Microbiological Risk Assessment (MRA) provides a framework for industrial food safety. This method models microbial load changes to evaluate risk reduction strategies and optimize processes for public health and food quality.
Area of Science:
- Food Science
- Microbiology
- Risk Assessment
- Industrial Processes
Background:
- Quantitative Microbiological Risk Assessment (MRA) is crucial for evaluating public health risks from biological hazards in food.
- Industrial implementation of MRA allows for the comparison of different risk reduction measures and operational settings.
Purpose of the Study:
- To provide scientific background and practical guidance for developing quantitative Microbiological Risk Assessment (MRA) in an industrial setting.
- To guide risk assessors and modelers in applying MRA for both food safety and food quality applications.
Main Methods:
- Development of a probabilistic model involving defining model structure, establishing mathematical equations for microbial load changes, and collecting data.
- Utilizing simulation procedures to obtain model outputs, followed by interpretation and communication to stakeholders.
- Employing 'what-if' scenarios for enhanced analysis and decision-making.
Main Results:
- MRA methodology can be applied to diverse industrial contexts, including process optimization for food safety and shelf-life determination for food quality.
- Case studies illustrate the application of MRA in foie gras (safety) and brioche (quality) production.
- The endpoint of MRA differs based on application, focusing on human health for safety and food portion for quality.
Conclusions:
- MRA is a versatile tool for industrial food safety and quality management.
- The structured approach to MRA development ensures robust and interpretable results.
- Effective communication of MRA outputs is essential for stakeholder engagement and decision-making.
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