Q4MRATools: Quantitative Tools for Microbial Risk Assessment
Author Information
Author(s): Luque Olga María Bonilla, Valero Antonio, Possas Arícia, Roufou Styliani, de Oliveira Mallia Jefferson, Valdramidis Vasilis
Primary Institution: Department of Food Science and Technology, UIC Zoonosis y Enfermedades Emergentes (ENZOEM), CeiA3 Universidad de Córdoba
Hypothesis
How can quantitative microbial risk assessments improve food safety?
Conclusion
The study developed predictive models to assess the impact of various factors on microbial inactivation and estimate public health risks associated with listeriosis from consuming artisanal Spanish fermented sausages.
Supporting Evidence
- The study focused on the assessment of the inhibitory activity of acids on food-borne microorganisms.
- Preliminary results discussed the impact of pH on microbial growth.
- The fellow designed and implemented various variables to assess the risks associated with Listeria monocytogenes in artisanal sausages.
- Predictive models were constructed using software tools like R Studio, @Risk, and MicroHibro.
Takeaway
This study helps us understand how to keep food safe by using math and science to predict how germs behave in different foods.
Methodology
The research involved training in predictive microbiology, experimental design, and the use of software tools for quantitative microbial risk assessments.
Limitations
The report includes only a portion of the data obtained, as the research is ongoing.
Participant Demographics
The fellow was from the Department of Food Science and Technology at the University of Córdoba, with a background in veterinary and public health.
Statistical Information
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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