Quantitative tools in microbial and chemical risk assessment

Area of Science:

• Food microbiology
• Food safety
• Predictive microbiology

Background:

• Growing consumer demand for natural, clean-label food products drives interest in biological preservatives.
• Lactic acid bacteria (LAB) are recognized for their antimicrobial properties and potential to enhance food safety.
• While LAB's direct application is established, the use of their cell-free supernatants (CFS) requires further investigation.

Purpose of the Study:

• To explore qualitative measures for investigating new bacteria-origin food additives.
• To understand the application of predictive microbiology in food safety risk assessment.
• To evaluate the use of cell-free supernatants (CFS) from Lactic acid bacteria (LAB) as food preservatives.

Main Methods:

• Training in predictive microbiology fundamentals and modeling strategies.
• Acquiring knowledge in experimental design and specific software tools (MATLAB, GInaFiT, DMFit).
• Focus on understanding differences in modeling bacterial growth and inactivation.

Main Results:

• Gained foundational knowledge in predictive microbiology and modeling techniques.
• Developed understanding of experimental design for risk assessment.
• Acquired skills in specialized software for microbiological modeling.

Conclusions:

• Qualitative measures can effectively contribute to the investigation of novel bacteria-origin food additives.
• Predictive microbiology modeling is crucial for robust food safety risk assessment.
• Further research into LAB cell-free supernatants (CFS) is warranted for food preservation applications.