Inactivation kinetics of a surrogate yield conservative predictions of foodborne pathogen reductions from low water activity foods of varying size and composition during low-temperature steam processing

Abstract

There is a growing interest in using models to predict foodborne pathogen inactivation as a way to validate or verify preventive controls. Unlike liquid foods, solid, low water activity foods (LWAF) are heterogenous in composition and structure and do not transfer heat uniformly. Using models constructed from one food to predict pathogen inactivation on another LWAF is complex and may not always be possible, even if the foods have similar composition. Using models constructed from inactivation kinetics of three foodborne pathogens and a surrogate from vacuum-steam-pasteurized (72 and 82 °C) whole macadamia nuts and dried apricot halves, 3-log reductions were predicted for the same pathogens and foods of reduced size. Model fits (First-order, Weibull, and Gompertz) were significantly impacted by the food type regardless of particle size. Despite the foods being identical in composition with particle size as the only altered characteristic, best-fit models accurately predicted the 3-log reductions only 50% of the time, but the surrogate inactivation models provided conservative predictions for pathogen reductions, highlighting that a surrogate's model may be a suitable tool for predicting pathogen reduction on LWAFs.

Keywords

• Predictive models
• Thermal inactivation
• LWAF
• Pediococcus acidilactici
• Listeria monocytogenes
• Salmonella enterica