The Development of Machine Learning-Assisted Software for Predicting the Interaction Behaviours of Lactic Acid Bacteria and Listeria monocytogenes.

ABSTRACT: Biopreservation technology has emerged as a promising approach to enhance food safety and extend shelf life by leveraging the antimicrobial properties of beneficial microorganisms. This study aims to develop precise predictive models to characterize the growth and interaction dynamics of lactic acid bacteria (LAB) and Listeria monocytogenes, which serve as bioprotective agents in food systems. Using both traditional and machine learning modelling approaches, we analyzed data from previously published growth curves in broth (BHI) and milk under isothermal conditions (4, 10, and 30 °C). The models evaluated mono-culture conditions for L. monocytogenes and LAB, as well as their competitive interactions in co-culture scenarios. The modified Gompertz model demonstrated the best pe

SUBMITTER: Tarlak F 

PROVIDER: S-EPMC11856248 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature