Development of a New Logistic Model for Prediction of Microbial Growth in Foods

Abstract

Recently we developed a new logistic model for prediction of microbial growth in foods. The model is an extended logistic model for expression of microbial growth which shows a sigmoid curve on the semi-log plot. The model could describe and predict bacterial growth at constant and dynamic temperatures in broth, on nutrient agar plate, and in pouched food. Prediction with our model was very similar to that with the Baranyi model, which is well known worldwide. The model also predicted the amount of a metabolite (toxin) by a microorganism. Namely, with the growth model and the kinetics of staphylococcal enterotoxin A production, the amount of the toxin produced by Staphylococcus aureus in milk was successfully predicted. Further, a predictive growth program running on a personal computer was developed with our model for users dealing with food safety. Our model can be a tool in the alert system and the risk assessment for microbial food safety. © 2007, Japan Society for Food Engineering. All rights reserved.