High hydrostatic pressure inactivation of microorganisms: A probabilistic model for target log-reductions

Abstract

A probabilistic model based on logistic regression was developed for a target log reduction of microorganisms inactivated by high hydrostatic pressure. Published inactivation data of Salmonella Typhimurium in broth for 4 and 5 log reductions, and Escherichia coli in buffer and carrot juice for 5 log reduction were used. The probabilities of achieving 4 or 5 log reductions for S. Typhimurium in broth and 5 log reduction for E. coli in buffer and carrot juice could be calculated at different pressure, temperature and time levels. The fitted interfaces of achieving/not achieving the target log reduction were consistent with the experimental data. Although the reliability of the predictions of the developed models could be questioned due to strain variation and different food matrix, a validation study has demonstrated that the developed models could be used to predict the target log reduction of these microorganisms at different pressure, temperature and time levels. This study has indicated that the probabilistic modeling for target log reductions can be useful tool for HHP inactivation of microorganisms, but further studies could be performed with several other factors such as pH and water activity of the food, concentration of certain additives as well as initial number of bacteria present in the food.

Keywords: Escherichia coli; High pressure; Logistic regression; Predictive microbiology; Salmonella Typhimurium.