Purpose: The aim of the study was to identify the main influencing factors and to predict survival rates for three major pathogens: Listeria monocytogenes, Staphylococcus aureus and Salmonella enterica.
Methods: In contrast with thermal treatments, HHP inactivation kinetics do not always follow first-order kinetics but show tailing and the use of DP values is consequently often unadapted. Therefore a dataset of 120 inactivation curves achieving at least three log10 reductions of the selected pathogens, was collected from the literature and analysed with reparameterized Weibull model to estimate t3D values, time needed to reach 3-log10 reduction. Bayesian hierarchical modeling was used to develop within a meta-regression analysis, a mixed-effect linear model with log10 t3D values (s) as response and pressure intensity and temperature as explicative variables. Treatment medium was considered as a co-variable having fixed effects whereas species, strain and study were considered as random factors. Several models differing by their description of variability on log10 t3Dand including combinations of factors were tested.
Results: Based on goodness-of-fit and parsimony, a model was chosen. Resistance to HHP was found to be the highest in meat products and the lowest in fruit juices. The determination of ZHP values, increase of pressure necessary to decrease log10 t3D by 10, enabled to rank the three pathogenic species according to high-pressure resistance. L. monocytogenes appeared to be the most resistant to HHP, then followed by S. aureus.
Significance: The model developed could be profitably used by food manufacturers to set appropriate HHP processing parameters to assure food safety.