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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #208583


item Juneja, Vijay
item Huang, Lihan

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/10/2007
Publication Date: 9/16/2007
Citation: Juneja, V.K., Marks, H.M., Huang, L., Thippareddi, H. 2007. Predictive model for growth of clostridium perfringens at temperatures applicable to cooling of cooked uncured beef and chicken. Meeting Abstract.

Interpretive Summary:

Technical Abstract: The common methodology for developing growth models for dynamic environments is to first determine growth kinetic parameters from a series of growth experiments conducted within well-defined environments under isothermal conditions. Subsequently, secondary models are developed to evaluate the effect of temperature and other environmental conditions on growth rates. Based on such models, a judiciously selected set of differential equations can be developed to be used for predicting relative growth of bacteria within a changing environment. The objective of this investigation was to develop a model for predicting relative growth of Clostridium perfringens from spore inocula in uncured beef and chicken during the cooling of thermally treated product. Isothermal growth of C. perfringens at various temperatures from 10-48.9 degree C were evaluated from which secondary level equations for the growth kinetics were derived. These equations were not significantly different between the species. The estimated theoretical minimum and maximum growth temperatures of C. perfringens in cooked uncured beef were 10 and 53 degree C, respectively. These bounds were similar for uncured chicken. For a temperature decline from 54.4 degree C to 27 degree C in 1.5 h, the standard model predicted a log10 relative growth of 1.1 – 1.2, while observed results ranged from about 0.4 to 0.9 log10. For the same temperature decline in 3 h, the predicted log10 relative growth was 3.6 log10 and the observed log10 relative growth was 2.4 - 3.0 log10. When the cooling scenarios were extended to lower temperature, the predictions were improved, taking into account the larger relative growth: for a cooling scenario of 54.4 degree C to 27 degree C in 1.5 h and 27 degree C to 4 degree C in 12.5 h, the average predicted and observed log10 relative growths were 3.2 – 3.3 log10 and 2.4 – 2.9 log10, respectively; when cooling (27 to 4 degree C) was extended to 15 h, the average predicted and observed log10 relative growth were 3.6 – 3.7 and 3.4 – 3.7 log10, respectively. For the latter cooling scenario, the C. perfringens population were > 6 log10, but still less than stationary levels (7 - 8 log10). By incorporating memory, assuming that the instantaneous cell-state transition rates at a given time are actually functions of the determined (isothermally) instantaneous rates at times equal to or before the given time, the predicted values can be improved to within +/- 0.5 log10 of the mean of the observed values for the cooling scenarios. The kinetic growth parameters obtained from this study, and the derived models of growth from them, can be used in evaluating growth of C. perfringens from spore populations during dynamically changing temperature conditions such as those encountered in meat processing, and thus can be of aid in designing microbiologically safe cooling regimes for uncured beef and chicken.