Development of User-Friendly Modeling Software and Its Application in Processed Meat Products

Abstract

The objective of this study was to develop software to predict the kinetic behavior and the probability of foodborne bacterial growth on processed meat products. It is designed for rapid application by non-specialists in predictive microbiology. The software, named Foodborne bacteria Animal product Modeling Equipment (FAME), was developed using Javascript and HTML. FAME consists of a kinetic model and a probabilistic model, and it can be used to predict bacterial growth pattern and probability. In addition, validation and editing of model equation are available in FAME. The data used by the software were constructed with 5,400 frankfurter samples for the kinetic model and 345,600 samples for the probabilistic model using a variety of combinations including atmospheric conditions, temperature, NaCl concentrations and NaNO2 concentrations. Using FAME, users can select the concentrations of NaCl and NaNO2 meat products as well as storage conditions (atmosphere and temperature). The software displays bacterial growth patterns and growth probabilities, which facilitate the determination of optimal safety conditions for meat products. FAME is useful in predicting bacterial kinetic behavior and growth probability, especially for quick application, and is designed for use by non-specialists in predictive microbiology.