Applicability of bacterial growth models in spreadable processed cheese

Area of Science:

• Food Science
• Microbiology
• Predictive Modeling

Background:

• Food spoilage reduces quality and edibility due to bacterial growth and metabolites.
• Bacterial proliferation is a key factor limiting the shelf life of processed cheese products.

Purpose of the Study:

• To assess the reliability of microbiological growth models for predicting bacterial changes in spreadable processed cheese.
• Evaluate the predictive accuracy of models for total viable count (TVC) and Clostridium in processed cheese.

Main Methods:

• Investigated bacterial growth (TVC and Clostridium) at 8°C, 20°C, and 30°C.
• Utilized standard microbiological procedures and the Baranyi and Roberts primary model with nonlinear regression analysis.

Main Results:

• The Baranyi and Roberts model achieved a 70% determination coefficient for TVC at 20°C and 30°C.
• Models for Clostridium showed low reliability (R² of 25% and 30%) at these temperatures.
• Shelf life decreased significantly at higher temperatures (70 days at 20°C, 7 days at 30°C).
• At 8°C, bacterial counts decreased over the shelf life for both TVC and Clostridium.

Conclusions:

• The Baranyi and Roberts and nonlinear regression models demonstrated poor agreement with experimental data for processed cheese.
• These predictive models are not considered reliable tools for forecasting microbiological changes in this product.
• Despite limitations, the models provided insights into the dynamics of microbial proliferation in spreadable processed cheese.