Méthodes de Monte Carlo du second ordre et d’inférence bayésienne pour l’évaluation des risques microbiologiques et des bénéfices nutritionnels dans la transformation des légumes

Abstract : The aim of this work is to set up microbiological risk and nutritional benefit assessment methods in the transformation of vegetables, in view of a risk-benefit analysis. The considered (industrial) risk is the alteration of green bean cans due to thermophilic bacteria Geobacillus stearothermophilus, and the nutritional benefit is the vitamin C content in appertized green beans. Reference parameters have first been acquired, by a meta-analysis using Bayesian inference for the risk part. Thermal resistance parameters D at 121.1°C and pH 7, zT and zpH of G.stearothermophilus have been respectively estimated at 3.3 min, 9.1°C and 4.3 pH units on average in aqueous media. The risk and benefit models have then been analyzed by a two-dimensional Monte Carlo simulation method, allowing a separated propagation of uncertainty and variability. The vitamin C losses between fresh and appertized green beans predicted by the model are of 86% on average, and the predicted non-stability at 55°C rate is of 0.5% on average, in good accordance with reality. A risk-benefit analysis has then been carried out to optimize benefit while keeping risk at an acceptable level, by exploring possible intervention scenarios based on some sensibility analysis results. Finally, a risk analysis model involving pathogenic bacteria Bacillus cereus in a courgette puree has been confronted to incubated product contamination data, by means of a Bayesian inference.
Document type :
Theses
Complete list of metadatas

Cited literature [189 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/pastel-00967496
Contributor : Abes Star <>
Submitted on : Friday, March 28, 2014 - 5:27:08 PM
Last modification on : Friday, December 1, 2017 - 1:20:37 AM
Long-term archiving on : Saturday, June 28, 2014 - 12:20:11 PM

File

These_CRigaux.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : pastel-00967496, version 1

Collections

Citation

Clémence Rigaux. Méthodes de Monte Carlo du second ordre et d’inférence bayésienne pour l’évaluation des risques microbiologiques et des bénéfices nutritionnels dans la transformation des légumes. Sociologie. AgroParisTech, 2013. Français. ⟨NNT : 2013AGPT0015⟩. ⟨pastel-00967496⟩

Share

Metrics

Record views

1177

Files downloads

1202