Predictive growth modeling of Yersinia enterocolitica in fresh kimchi cabbage brassica pekinensis as a function of storage temperature.

We developed a predictive growth model of for fresh Kimchi cabbages as a function of storage temperature (5-20 °C). The Baranyi equation used for primary modeling at these storage temperatures was suitable as a model for obtaining lag time (LT) and specific growth rate (SGR) (R = 0.97-0.98). As the temperature increased, the growth of tended to increase, with SGR values of 0.33, 0.40, 0.60 and 0.68 log colony-forming units/h at 8, 11, and 15 °C, and LT values of 5.63, 3.54, 2.23 and 1.09 h, respectively. The secondary model was determined by the non-linear regression analysis. The suitability of the modeling results for the SGR and LT value was verified by determining the mean square error (<0.01), bias factor (0.919-0.999), and accuracy factor (1.032-1.136). The predicted models can be used to predict the growth of in Kimchi cabbage at various temperatures and as an effective tool for maintaining the safe level of in the production, processing, and distribution of fresh agricultural products.