Predicting outgrowth and inactivation of Clostridium perfringens in meat products during low temperature long time heat treatment

Abstract

With low temperature long time (LTLT) cooking it can take hours for meat to reach a final core temperature above 53°C and germination followed by growth of Clostridium perfringens is a concern. Available and new growth data in meats including 154 lag times (tlag), 224 maximum specific growth rates (μmax) and 25 maximum population densities (Nmax) were used to developed a model to predict growth of C. perfringens during the coming-up time of LTLT cooking. New data were generate in 26 challenge tests with chicken (pH6.8) and pork (pH5.6) at two different slowly increasing temperature (SIT) profiles (10°C to 53°C) followed by 53°C in up to 30h in total. Three inoculum types were studied including vegetative cells, non-heated spores and heat activated (75°C, 20min) spores of C. perfringens strain 790-94. Concentrations of vegetative cells in chicken increased 2 to 3logCFU/g during the SIT profiles. Similar results were found for non-heated and heated spores in chicken, whereas in pork C. perfringens 790-94 increased less than 1logCFU/g. At 53°C C. perfringens 790-94 was log-linearly inactivated. Observed and predicted concentrations of C. perfringens, at the time when 53°C (log(N53)) was reached, were used to evaluate the new growth model and three available predictive models previously published for C. perfringens growth during cooling rather than during SIT profiles. Model performance was evaluated by using mean deviation (MD), mean absolute deviation (MAD) and the acceptable simulation zone (ASZ) approach with a zone of ±0.5logCFU/g. The new model showed best performance with MD=0.27logCFU/g, MAD=0.66logCFU/g and ASZ=67%. The two growth models that performed best, were used together with a log-linear inactivation model and D53-values from the present study to simulate the behaviour of C. perfringens under the fast and slow SIT profiles investigated in the present study. Observed and predicted concentrations were compared using a new fail-safe acceptable zone (FSAZ) method. FSAZ was defined as the predicted concentration of C. perfringens plus 0.5logCFU/g. If at least 85% of the observed log-counts were below the FSAZ, the model was considered fail-safe. The two models showed similar performance but none of them performed satisfactorily for all conditions. It is recommended to use the models without a lag phase until more precise lag time models become available.