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.

ABSTRACT
 Materials and Methods
  Data collection
  Mathematical base
  Development of predictive modeling software
  Application on meat products
 Results and Discussion
 Conclusion
 Disclosure Statement
 국문요약
 References

• Heeyoung Lee(Risk Analysis Research Center, Sookmyung Women’s University)
• Panho Lee(TNH)
• Soomin Lee(Risk Analysis Research Center, Sookmyung Women’s University)
• Sejeong Kim(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University)
• Jeeyeon Lee(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University)
• Jimyeong Ha(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University)
• Hyemin Oh(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University)
• Yohan Yoon(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University) Correspondence to
• Yukyung Choi(Risk Analysis Research Center, Sookmyung Women’s University, Department of Food and Nutrition, Sookmyung Women’s University)