Modelling the growth of Clostridium perfringens during the cooling of bulk meat.
A dynamic predictive model was developed to describe the effects of temperature, pH and NaCl concentration on the growth of Clostridium perfringens type A. The model for the specific growth rate was based on 81 growth curves generated in our laboratory or obtained from the publicly available ComBase database. Growth curves obtained during cooling were fitted with the dynamic model of Baranyi and Roberts. This made it possible to determine the parameter value reflecting the physiological state of C. perfringens after heating profiles typically applied to bulk meat. The model with the obtained parameters provided a good description of growth of C. perfringens in 24 heating/cooling curves generated specifically for this work (various non-isothermal treatments with a range of combinations of pH and NaCl concentration), and also for existing literature data. The dynamic model was implemented in Perfringens Predictor, a web-based application that can be accessed free of charge via www.combase.cc. It is anticipated that the use of this model and Perfringens Predictor will contribute to a reduction in the food poisoning incidence associated with C. perfringens.
Le Marc
Y
Y
Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK.
Plowman
J
J
Aldus
C F
CF
Munoz-Cuevas
M
M
Baranyi
J
J
Peck
M W
MW