Modification of a Predictive Model To Include the Influence of Fat Content on Salmonella Inactivation in...

Area of Science:

• Food safety
• Microbiology
• Risk assessment

Background:

• Low-water-activity (aw) foods, including those with fat, are frequently linked to Salmonella outbreaks.
• The specific impact of fat content on Salmonella survival in foods like peanut butter is not well understood.
• Certain Salmonella serovars exhibit remarkable resilience in low-moisture and extreme temperature environments.

Purpose of the Study:

• To investigate the influence of fat content on Salmonella survival in low-aw foods.
• To enhance an existing secondary inactivation model for predicting Salmonella behavior in higher-fat foods.
• To provide data for developing effective risk mitigation strategies for contaminated low-aw foods.

Main Methods:

• Whey protein powder with peanut oil was adjusted to low aw values (<0.60) and inoculated with Salmonella.
• Samples were stored at various temperatures (22–80°C) for extended periods (48 hours to 168 days).
• Survival data were analyzed using Weibull, Biphasic-linear, Double Weibull, and Geeraerd-tail models, with Weibull selected for secondary modeling.

Main Results:

• Fat content was a significant factor in Salmonella survival at temperatures ≥50°C.
• Water activity (aw) influenced survival at 37°C and 70°C.
• The revised secondary model showed improved prediction accuracy (% bias and % discrepancy) compared to the previous model, though less reliable at 80°C for peanut butter.

Conclusions:

• The developed model accurately predicts Salmonella survival in low-aw foods containing fat under various conditions.
• Fat content and water activity play distinct roles in Salmonella inactivation depending on temperature.
• The findings support the development of targeted risk management strategies for fatty, low-aw food products.