Mathematical modeling for the prediction of biofilm formation and removal in the food industry as strategy to control microbiological resistance

Abstract

The formation of biofilms in the food industry poses significant economic, social, and public health challenges. Concurrently, mathematical models have emerged as promising tools for investigating microbial contamination and biofilm dynamics. This study evaluates the application of these models, highlighting their ability to identify critical parameters influencing microbial adhesion and to develop strategies for disrupting biofilm formation. Furthermore, it explores how mathematical modeling can address current limitations in food safety, discussing practical challenges such as the complexity of biological systems and the necessity for experimental validation of proposed models. In this context, the review assesses both the potential and the challenges associated with employing mathematical models for microbial control in food processing, examining the specifics of existing models. Additionally, it underscores the need for a comprehensive understanding of biofilm formation mechanisms and control techniques to fully leverage the benefits of these models. The findings demonstrate that mathematical modeling is a viable, innovative, and promising approach for optimizing biofilm prevention and control strategies in the food industry. To achieve more effective biofilm management and ensure consumer food safety, future research should focus on applying these models to various real-world scenarios.

Keywords: Bacterial adhesion; Food safety; Mathematical models; Microorganisms.