Development of a model to predict growth of Clostridium perfringens in cooked beef during cooling

Abstract

The objective of this work was to develop a new model to predict the growth of Clostridium perfringens in cooked meat during cooling. All data were collected under changing temperature conditions. Individual growth curves were fit using DMFit. Germination outgrowth and lag (GOL) time was modeled versus temperature at the end of GOL using conservative assumptions. Each growth curve was used to estimate a series of exponential growth rates at a series of temperatures. The square-root model was used to describe the relationship between the square root of the average exponential growth rate and effective temperature. Predictions from the new model were in close agreement with the data used to create the model. When predictions from the model were compared with new observations, fail-dangerous predictions were made a majority of the time. When GOL time was predicted exactly, many fail-dangerous predictions shifted toward the fail-safe direction. Two important facts regarding C. perfringens should impact future modeling research with this organism and may have broader food safety policy implications: (i) the normal variability in the response of the organism from replicate to replicate may be quite large (1 log CFU) and may exceed the current U.S. Food Safety Inspection Service performance standard, and (ii) the accuracy of the GOL time model has a profound influence upon the overall prediction, with small differences in GOL time prediction (∼1 h) having a very large effect on the predicted final concentration of C. perfringens.