Purpose: The purpose of this project was to conduct a meta-analysis of existing thermal inactivation data and parameters for Salmonella in low moisture foods.
Methods: Data were compiled from a range of available studies that included thermal inactivation of Salmonella in/on low-moisture food matrices. A minority of the data were acquired directly from ComBase, while other publications were identified and acquired through searches of various indexes and journals. Data from 20 representative studies were characterized in terms of product, conditions, and the extent to which data variability and model uncertainty were reported
Results: The representative studies encompassed ~600 inactivation data sets that included ~4,200 individual data points. The fraction of these data involving particulates (e.g., nuts), powders (e.g., flour), and pastes (e.g., peanut butter) were 55% (n = 2,286), 42% (n = 1.763), and 3% (n = 144), respectively. Only 10% of the studies reported any measure of replication error to characterize uncertainty; 75% reported some indication of parameter estimation error. Of the selected studies, 65% were performed under isothermal conditions, and 30% (n = 6) included dynamic water activity. However, of the 70% that reported an inactivation model, only one study reported a model accounting for dynamic water conditions.
Significance: The resulting database of Salmonella thermal resistance data for low-moisture foods meets an important need for an industry, which currently lacks access to and analysis of data and models sufficient to use them to validate thermal pasteurization processes.