Wednesday, May 11, 2016
Megaron Athens International Conference Center
Ji sun So, Department of Food and Nutrition, Kunsan National University, Gunsan, Korea, The Republic of
Ha-Neur Kim, Department of Food and Nutrition, Kunsan National University, Gunsan, Korea, The Republic of
Myoung-Su Park, Department of Food and Nutrition, Kunsan National University, Gunsan, Korea, The Republic of
Yong-Soo Kim, Korea Health Industry Development Institute, Chungju, Korea, The Republic of
Beom-Gill Lee, NS Shopping Safety Research Institute, Seongnam, Korea, The Republic of
Gyung Jin Bahk, Kunsan National University, Gunsan, Korea, The Republic of
Introduction: Kimchi is a Korean traditional fermented vegetable product and is gaining popularity as a functional food. Although this type of food is generally recognized as safe due to its high salinity (> 2.0%) and low pH (< 4.5), recent microbiological safety issues have thrown this assumption into doubt. Several large outbreaks of pathogenic
Escherichia coli in South Korea have been attributed to Kimchi. In South Korea in 2012, 1,642 people were infected by pathogenic
E. coli after eating Kimchi products.
Purpose: The objective of this study was to develop a predictive model of the growth of pathogenic E. coli in Kimchi as a function of storage temperature.
Methods: We investigated that growth of the cocktail of five pathogenic E. coli (EAEC, EHEC, EIEC, EPEC, and ETEC) strains inoculated in Kimchi at different storage temperatures (5, 10, 15, 20, 25, 30, and 35 °C) for a maximum of 12 days.
Results: Fitted into the Baranyi model to generate the growth parameters including specific growth rate (SGR) and lag time (LT) with high coefficients of determination (R2 > 0.95) except 10 °C (R2 < 0.90). The obtained SGR and LT were employed to develop secondary exponential equation models to evaluate the effects of storage temperature on the growth kinetics of pathogenic E. coli in Kimchi. The values of bias factor (1.000-1.004) and accuracy factor (1.004-1.070), which were regarded as acceptable, demonstrated that the obtained models could provide good and reliable predictions.
Significance: The developed predictive model could be suitable for the purpose of microbiological risk assessment of pathogenic E. coli in Kimchi.
