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Updated: Jun 14, 2026
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Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method
Published on: May 12, 2023
Updating parameters of the chicken processing line model.
Dorota Kurowicka1, Maarten Nauta, Katarzyna Jozwiak
1Delft University of Technology, Delft, The Netherlands. d.kurowicka@tudelft.ne
Summary
This study updates a mathematical model for Campylobacter transmission during chicken processing using Bayesian methods. Microbiological data refines expert judgment, improving accuracy in describing slaughterhouse contamination.
Area of Science:
- Food safety
- Microbiology
- Mathematical modeling
Background:
- Campylobacter transmission on chicken carcasses is a significant food safety concern.
- A mathematical model (Nauta et al., 2005) previously described this transmission using expert judgment.
- Updating model parameters with empirical data is crucial for relevance.
Purpose of the Study:
- To update parameters of a chicken processing mathematical model.
- To evaluate Bayesian updating for integrating microbiological data with expert judgment.
- To enhance the model's accuracy in describing Campylobacter transmission in slaughterhouses.
Main Methods:
- Utilized Bayesian updating techniques.
- Incorporated microbiological data (Berrang and Dickens) to refine model parameters.
- Applied the updated model to a chicken processing line.
Main Results:
- Demonstrated the effectiveness of Bayesian updating for parameter refinement.
- Showcased improved model performance with empirical data integration.
- Quantified Campylobacter transmission dynamics with updated parameters.
Conclusions:
- Bayesian updating is a suitable method for enhancing mathematical models with microbiological data.
- Updated models provide a more accurate representation of Campylobacter transmission in chicken processing.
- This approach improves understanding and control of foodborne pathogens in poultry.
