Validation of mathematical models for Salmonella growth in raw ground beef under dynamic temperature conditions representing loss of refrigeration.

ABSTRACT

Temperature is a primary factor in controlling the growth of microorganisms in food. The current U. S. Food and Drug Administration Model Food Code guidelines state that food can be kept out of temperature control for up to 4 h without qualifiers, or up to 6 h, if the food product starts at an initial 41 °F (5 °C) temperature and does not exceed 70 °F (21 °C) at 6 h. This project validates existing ComBase computer models for Salmonella growth under changing temperature conditions modeling scenarios using raw ground beef as a model system. A cocktail of Salmonella serovars isolated from different meat products ( Salmonella Copenhagen, Salmonella Montevideo, Salmonella Typhimurium, Salmonella Saintpaul, and Salmonella Heidelberg) was made rifampin resistant and used for all experiments. Inoculated samples were held in a programmable water bath at 4.4 °C (40 °F) and subjected to linear temperature changes to different final temperatures over various lengths of time and then returned to 4.4 °C (40 °F). Maximum temperatures reached were 15.6, 26.7, or 37.8 °C (60, 80, or 100 °F), and the temperature increases took place over 4, 6, and 8 h, with varying cooling times. Our experiments show that when maximum temperatures were lower (15.6 or 26.7 °C), there was generally good agreement between the ComBase models and experiments when temperature increases of 15.6 or 26.7 °C occurred over 8 h, experimental data were within 0.13 log CFU of the model predictions. When maximum temperatures were 37 °C, predictive models were fail-safe. Overall bias of the models was 1.11. and accuracy was 2.11. Our experiments show the U.S. Food and Drug Administration Model Food Code guidelines for holding food out of temperature control are quite conservative. Our research also shows that the ComBase models for Salmonella growth are accurate or fail-safe for dynamic temperature conditions as might be observed due to power loss from natural disasters or during transport out of temperature control.