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Published on: May 6, 2013
Bayesian inference for quantifying Listeria monocytogenes prevalence and concentration in minced pork meat from
Nikolaos D Andritsos1, Marios Mataragas, Spiros Paramithiotis
1Laboratory of Food Quality Control and Hygiene, Department of Food Science and Technology, Agricultural University of Athens, Iera Odos 75, GR-118 55 Athens, Greece.
Abstract:
The purpose of this work was to estimate the prevalence and concentration of Listeria monocytogenes in minced pork meat by the application of a Bayesian modeling approach. Samples (n = 100) collected from local markets were tested for L. monocytogenes using in parallel the PALCAM, ALOA and RAPID'L.mono selective media. Presence of the pathogen was confirmed through biochemical and molecular tests. Independent experiments (n = 10) for validation purposes were performed. No L. monocytogenes was enumerated by direct-plating (<10 CFU/g), though the pathogen was detected in 22% of the samples. Sensitivity and specificity varied depending on the culture method. L. monocytogenes concentration was estimated at 14-17 CFU/kg. Validation showed good agreement between observed and predicted prevalence (error = -2.17%). The use of at least two culture media in parallel enhanced the efficiency of L. monocytogenes detection. Bayesian modeling may reduce the time needed to draw conclusions regarding L. monocytogenes presence and the uncertainty of the results obtained.
Insights
Listeria monocytogenes was detected in 22% of minced pork samples, with concentrations estimated using Bayesian modeling. Employing multiple culture media improved detection efficiency for this foodborne pathogen.
Area of Science:
- Food Microbiology
- Quantitative Risk Assessment
- Bayesian Statistics
Background:
- Listeria monocytogenes is a significant foodborne pathogen.
- Accurate estimation of its prevalence and concentration in food products is crucial for public health.
- Traditional microbiological methods can be time-consuming and may underestimate low-level contamination.
Purpose of the Study:
- To estimate the prevalence and concentration of Listeria monocytogenes in minced pork using Bayesian modeling.
- To compare the performance of different selective culture media for Listeria monocytogenes detection.
- To validate the Bayesian model's predictions against experimental data.
Main Methods:
- Collection and microbiological analysis of 100 minced pork samples.
- Parallel use of PALCAM, ALOA, and RAPID'L.mono selective media for Listeria monocytogenes detection.
- Biochemical and molecular confirmation of pathogen presence.
- Application of Bayesian modeling for prevalence and concentration estimation.
- Validation experiments with 10 independent trials.
Main Results:
- Listeria monocytogenes was detected in 22% of samples, though direct plating yielded no enumeration (<10 CFU/g).
- Estimated pathogen concentration ranged from 14-17 CFU/kg.
- Sensitivity and specificity varied across different culture media.
- The Bayesian model showed good agreement with observed prevalence (error = -2.17%).
Conclusions:
- Parallel use of multiple culture media enhances Listeria monocytogenes detection efficiency.
- Bayesian modeling provides a robust approach for estimating pathogen prevalence and concentration in minced pork.
- This modeling approach can reduce the time and uncertainty associated with microbiological analysis.
