Dynamic computer simulation of Clostridium perfringens growth in cooked ground beef.

The objective of this study was to develop a computer simulation algorithm to dynamically estimate and predict the growth of Clostridium perfringens in cooked ground beef. The computational algorithm was based on the implicit form of the Gompertz model, the growth kinetics of C. perfringens in cooked ground beef, and the fourth-order Runge-Kutta numerical method. This algorithm was validated using a cocktail of three strains of C. perfringens spores grown under isothermal, square-waved, linear cooling, and exponential cooling temperature profiles. In general, the results of computer simulation matched closely with the experimental data with the absolute errors less than 0.5 log(10) CFU/g. This method may be a useful tool for the food industry, regulatory agencies, distributors, and retailers to predict the effect of temperature abuse on the microbial safety of C. perfringens and other foodborne pathogens in processed meat products.

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