Engineering modeling frameworks for microbial food safety at various scales.

Area of Science:

• Interdisciplinary food science, microbiology, physics, and engineering.
• Mathematical modeling of microbial food safety.

Background:

• Growing interest in mechanistic microbial process models.
• Need for a unifying framework for diverse modeling approaches.

Purpose of the Study:

• To propose a general framework for microbial food safety modeling.
• To synthesize literature across disciplines for a cohesive approach.

Main Methods:

• A four-level framework: sub-cellular, microbial population, food, and human population scales.
• Integration of mechanistic and empirical models, including predictive microbiology.
• Emphasis on fundamental processes like microbial growth, death, attachment, migration, communication, and food process physics (heat/moisture transfer).

Main Results:

• The framework integrates diverse models from traditional predictive microbiology to individual-based and cellular automata models.
• Quantitative details provided for coupling and integrating models across scales.
• Guidelines for combining sub-processes and physical phenomena into multiphysics models.

Conclusions:

• The proposed framework offers a roadmap for predictive food safety at various scales.
• This synthesis aims to drive novel research and educational approaches in microbial food safety modeling.