Evaluation of thermal destruction kinetics of Clostridium difficile spores (ATCC 17857) in lean ground beef with first‐order/Weibull modeling considerations

Abstract

AbstractThermal destruction kinetics of spores of Clostridium difficile ATCC 17857 was evaluated between 74 and 82°C and characterized using the first‐order log‐linear and Weibull models. Computed decimal reduction times using the first‐order model ranged from 4.39 min at 82°C to 146 min at 74°C, with a z value of 5.17°C. Thermal destruction data were also analyzed using the Weibull model. Based on regression, the predicted one‐D value (first‐order model) and the reliable life (tR) (Weibull model) were 3.86 and 4.05 min at 82°C and 136 and 165 min at 74°C, respectively, indicating the Weibull model to be more conservative yielding higher decimal reduction time values. However, when extended to achieve 2.5, 4, and 6 decimal reductions in C. difficile spores, the calculated process times were more conservative with the first‐order model than with the Weibull model. Moreover, within the experimental range, when data for both models could be compared, predictions from the first‐order model were much closer to the experimental values. Therefore, when used for process calculation for 2.5 or higher log reductions, the first‐order model would give more conservative and safer process times. The study provides destruction kinetics data for C. difficile under a range of temperature conditions.Practical ApplicationsClostridium difficile is a major cause of antibiotic‐associated diarrhea and pseudomembranous colitis in humans. C. difficile infection is the leading cause of gastroenteritis‐associated death. C. difficile infections have been increasing in recent years, and therefore warrant appropriate remedial measures. Thermal inactivation is the most common method for pathogen control, and often the cooking practices are adjusted to a level pre‐established to make the foods pathogen free. Available information on thermal destruction kinetics is scarce, and therefore the data generated here should be of significant importance for safety considerations.