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Comparison of Desiccation Tolerance among Listeria monocytogenes, Escherichia coli O157:H7, Salmonella enterica, and Cronobacter sakazakii in Powdered Infant Formula
- Koseki, Shigenobu, Nakamura, Nobutaka, Shiina, Takeo
- Journal of food protection 2015 v.78 no.1 pp. 104-110
- Cronobacter sakazakii, Escherichia coli O157, Listeria monocytogenes, Monte Carlo method, Salmonella enterica, Weibull statistics, bacteria, drought tolerance, dry environmental conditions, food matrix, infant formulas, mathematical models, pathogens, probability distribution, storage temperature
- Bacterial pathogens such as Listeria monocytogenes, Escherichia coli O157:H7, Salmonella enterica, and Cronobacter sakazakii have demonstrated long-term survival in/on dry or lowâwater activity (aw) foods. However, there have been few comparative studies on the desiccation tolerance among these bacterial pathogens separately in a same food matrix. In the present study, the survival kinetics of the four bacterial pathogens separately inoculated onto powdered infant formula as a model low-aw food was compared during storage at 5, 22, and 35Â°C. No significant differences in the survival kinetics between E. coli O157:H7 and L. monocytogenes were observed. Salmonella showed significantly higher desiccation tolerance than these pathogens, and C. sakazakii demonstrated significantly higher desiccation tolerance than all other three bacteria studied. Thus, the desiccation tolerance was represented as C. sakazakii > Salmonella > E. coli O157:H7 = L. monocytogenes. The survival kinetics of each bacterium was mathematically analyzed, and the observed kinetics was successfully described using the Weibull model. To evaluate the variability of the inactivation kinetics of the tested bacterial pathogens, the Monte Carlo simulation was performed using assumed probability distribution of the estimated fitted parameters. The simulation results showed that the storage temperature significantly influenced survival of each bacterium under the dry environment, where the bacterial inactivation became faster with increasing storage temperature. Furthermore, the fitted rate and shape parameters of the Weibull model were successfully modelled as a function of temperature. The numerical simulation of the bacterial inactivation was realized using the functions of the parameters under arbitrary fluctuating temperature conditions.