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KMID : 1007520210300131733
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Food Science and Biotechnology
2021 Volume.30 No. 13 p.1733 ~ p.1742
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Predictive modeling and probabilistic risk assessment of Clostridium perfringens in hamburgers and sandwiches
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Choi Yun-Hui
Park Jin-Hwa
Kang Mi-Seon
Yoon Yo-Han
Ha Sang-Do
Kim Hyun-Jung
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Abstract
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This study aimed to develop a mathematical model for the survival of Clostridium perfringens in hamburgers and sandwiches and to evaluate their microbial risk. The primary model was developed in hamburgers using 4 strains of C. perfringens at 5, 10, 15, 25 and 37 °C, and the kinetic parameters of the primary model were fitted well with the Weibull model (R2?≥?0.95). The secondary model was developed and validated in hamburgers and sandwiches using the Davey model, which was evaluated by Bf, Af, and RMSE values within the acceptable range. A probabilistic risk model was developed and simulated using @Risk program to estimate the probability of infection (Pinf) of C. perfringens based on the data on prevalence (n?=?100), time, temperature, and consumption of hamburgers and sandwiches (150.00?±?20.96 g). Based on the simulation model, the mean C. perfringens exposure dose was 0.00976 CFU/g, and the estimated mean Pinf was 1.78?×?10?13, which was very low in comparison with the current available data. The proposed model and the result can thus be useful to establish risk management options and microbial criteria for C. perfringens contamination in hamburgers and sandwiches.
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KEYWORD
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Clostridium perfringens, Predictive model, Risk assessment, Hamburgers and sandwiches, Probabilistic
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