Abstract

AbstractGrowth data of Listeria monocytogenes on white cabbage were obtained at several fixed thermal conditions (4, 10, 15, 20, 25 and 30C) and were then fitted into four different primary models: the modified Gompertz model, Logistic model, the Logistic model with delay and Baranyi model. Then, these four primary models were compared by Akaike's information and Sawa's Bayesian information criteria. Accordingly, the obtained growth parameters such as growth rate (GR) and lag time (LT) from each primary model were used to develop the secondary models and the performances were then evaluated by median relative error (MRE), mean absolute relative error (MARE) and %standard error of prediction (%SEP). The results indicated that Baranyi model described the growth of L. monocytogenes on white cabbage better than Logistic model, the modified Gompertz model and the Logistic model with delay. The square root models can be used to describe the growth parameters of L. monocytogenes on white cabbage estimated from the modified Gompertz, Logistic, Logistic with delay and Baranyi models, which showed better predictions for GR than LT.Practical ApplicationThe responses of Listeria monocytogenes on white cabbage at various temperatures were investigated and modeled using different models. The goodness‐of‐fit and predictive abilities of different models were evaluated and the primary model with best performance to describe the growth behavior was selected. The growth parameters derived from each primary model were used to develop the secondary model using the square root model. The validated models can be used to predict potential L. monocytogenes growth on white cabbage, which are very valuable for the food safety purpose during the whole food chain of white cabbage from farm to table. They could provide reliable and valuable growth kinetics information for the quantitative microbiological risk assessment of L. monocytogenes on white cabbage.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call