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Validation of Predictive Mathematical Models Describing Growth of Staphylococcus aureus
Isabel Walls1, Virginia N Scott1, Dane T Bernard1
1National Food Processors Association, 1401 New York Ave, N. W., Washington, D.C. 20005, USA.
Journal of Food Protection
|June 5, 2019
Summary
This study found that predictive models often underestimate Staphylococcus aureus growth in sterile foods. These models should guide, not solely determine, food safety assessments.
Area of Science:
- Food microbiology
- Predictive modeling
- Bacterial growth kinetics
Background:
- Accurate prediction of bacterial growth is crucial for food safety.
- Existing models like Pathogen Modeling Program (PMP) and Food MicroModel (FMM) are used to estimate microbial behavior in food.
- Staphylococcus aureus is a significant foodborne pathogen requiring careful monitoring.
Purpose of the Study:
- To investigate the growth of Staphylococcus aureus in a sterile food matrix under various temperature, salt, and pH conditions.
- To compare the experimentally determined growth kinetics with predictions from the PMP and FMM.
- To evaluate the reliability of these models in predicting S. aureus growth in food.
Main Methods:
- Growth experiments of Staphylococcus aureus were conducted at different temperatures (12°C, 20°C, 25°C, 35°C), NaCl concentrations (1.2% to 15.8%), and pH levels (5.5 to 7.5).
- Growth data were analyzed using the Gompertz equation to determine growth kinetics.
- Experimental results were compared against predictions generated by the Pathogen Modeling Program (PMP) and Food MicroModel (FMM).
Main Results:
- Both PMP and FMM generally underestimated Staphylococcus aureus growth in the tested sterile food.
- Predicted lag-phase durations from PMP varied significantly, often being longer than observed.
- FMM also showed discrepancies in lag-phase predictions, and both models exhibited some differences in predicted growth rates compared to experimental data.
Conclusions:
- Predictive models like PMP and FMM can serve as useful guides for estimating bacterial growth rates in foods.
- However, these models should not be the sole basis for food safety decisions due to underestimation of S. aureus growth.
- Further refinement of predictive models is necessary for more accurate food safety assessments.
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