A MatLab-Based App to Optimize Food Formulation and Recipes Taking into Account the Impact of pH and Storage Tmperature on Growth, Survival and Inactivation of Foodborne Pathogens

Introduction:  Nowadays, predictive microbiology or the use of recognized mathematical models to describe microbial behavior is commonly used in food research applications. Indeed growth, survival or death of specific microorganisms in food may be evaluated for specific properties of food (water activity and pH) and the storage conditions (temperature, relative humidity and atmosphere). Coroller et al. reported in 2012 a single modelling approach to apprehend food features yielding inactivation, survival and growth of L. monocytogenes that was validated on more than thousand datasets.

Purpose:  This study aims at extending this approach to other pathogenic strains using a MatLab-based app to further improve industrial outreach.

Methods:  Boundaries were determined in BHI broth to quantify growth abilities and destruction upon temperature and pH stress exposure for selected strains, i.e., Listeria monocytogenes SOR100, Salmonella Typhimurium ADQP305, Escherichia coli SOR200 and Pseudomonas aeruginosa ATCC15442. Shortly, growth kinetics and kill-curves were fitted, respectively by Rosso logistic and Weibullian models. Secondary models enabled to quantify the impact of environmental conditions on bacterial behavior, i.e., growth, survival and inactivation. A MatLab-based app was developed to represent the variation of population for given conditions of formulation and storage.

Results:  This app estimates the difference of population (ΔlogN) for given conditions of pH, temperature and storage time. The GUI graphical user interface indicates iso-contour plots which appear in “warm colors” for an increase of population or in “cold colors” for a decrease or death of population. Even though expected, this representation offers the advantage to easily visualize safe combination for food formulation.

Significance:  Taking into account the impact of temperature and pH on microbial behaviour is crucial to ensure food safety throughout shelf life. This app enables visual representation of environmental conditions ensuring death of major pathogens, to further evaluate and optimise food recipe and storage conditions.