Thermal inactivation kinetics of seven genera of vegetative bacterial pathogens common to the food chain are similar after adjusting for effects of water activity, sugar content and pH

J Hein M Van Lieverloo,Mounia Bijlaart,Marjon H.J Wells-Bennik,Heidy M.W Den Besten,Marcel H Zwietering

doi:10.1016/j.mran.2021.100174

J Hein M Van Lieverloo, Mounia Bijlaart + Show 3 more

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https://doi.org/10.1016/j.mran.2021.100174

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Abstract

A predictive model was made for the logarithm of the thermal decimal reduction time (logD) of Salmonella enterica (D = time to 90% reduction by inactivation). The model was fitted with multiple linear regression from 521 logD-values reported in literature for laboratory media and foods highly varying in water activity and pH. The single regression model with temperature as the only variable had a high residual standard error (RSE) of 0.883 logD and no predictive value (fraction of variance explained (R2) < 0.001). Adding water activity, sugar content and pH as predictors resulted in a model with a lower RSE of 0.458 logD and an adjusted R2 of 0.73. The model was validated by comparing 985 predicted with observed logD for S. enterica from other publications. The model was subsequently validated with 1498 published logD-values for inactivation of vegetative cells of nine other pathogenic bacteria genera (mainly Listeria monocytogenes, Escherichia coli, Clostridium perfringens, Cronobacter spp., Staphylococcus aureus, Yersinia enterocolitica) in or on a variety of laboratory media, meat, fish, dairy, nuts, fruits and vegetables. Regression analyses for validation with the 985 logD of S. enterica and 2483 logD of all genera show deviations from the expected slope of 1 (both 0.81) and the expected intercept of 0 (0.04 and 0.19 logD respectively). However, only 0.7% and 2% respectively of the new logD (expected: 0.5%) were observed above the 99% prediction interval of the original S. enterica model based on 521 logD. The findings suggest that i) the variability of thermal resistance of strains within species is larger than between genera and species; ii) one generic predictive model, also accounting for variability, suffices for designing the thermal inactivation of a variety of vegetative pathogenic bacteria in many food types.

Highlights

Thermal inactivation processes – e.g., pasteurization and sterilization – aim at safeguarding microbial safety and limiting spoilage of products and materials that may otherwise cause infections, intoxications or spoilage by micro-organisms
A predictive model for thermal inactivation of vegetative bacteria was based on data from experiments in a number of different foods and media with just S. enterica
The model, validated with data from a large variety of genera, species and strains, heated in a variety of foods and media reported in literature, predicts the inactivation of vegetative bacteria of other genera and their species surprisingly well

Summary

Introduction

Thermal inactivation processes – e.g., pasteurization and sterilization – aim at safeguarding microbial safety and limiting spoilage of products and materials (food, pharmaceuticals, cosmetics) that may otherwise cause infections, intoxications or spoilage by micro-organisms. The de signs of thermal inactivation processes are generally optimized to ensure safety and shelf life of products, while maintaining taste and nutritional value. The heat inactivation of various strains in a variety of food products and laboratory media has been studied, resulting in many published D- and z-values for various conditions (e.g. ICMSF, 1996; Doyle and Mazzotta, 2000; Doyle et al, 2001, Van Asselt and Zwietering, 2006). Factors reported to have an influence on the heat resistance of a pathogen are amongst others: strain variability, growth phase (age) of the culture, growth conditions, recovery media, and characteristics of foods such as salt content, aw, acidity, and the presence of other inhibitors (Doyle et al, 2001)

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