Development of a new logistic model for microbial growth in foods

Mathematical models are essentially needed to quantitatively predict microbial growth in food products during their production and distribution. Recently we developed a new logistic model for microbial growth. The model is an extended logistic model, which shows a sigmoid curve on a semi-log plot. The model could precisely describe and predict bacterial growth at constant and dynamic temperatures in broth, on nutrient agar plates, and in pouched food. Prediction results with our model were very similar to those with the Baranyi model, which is well known worldwide. The model also predicted the amount of metabolites (toxins) that would be produced by a microorganism. Namely, with the growth model and the kinetics of staphylococcal enterotoxin A production, the amount of the toxins produced by Staphylococcus aureus in milk was successfully predicted. Our model could be a tool in the alert system and the quantitative risk assessment of harmful microbes in food.