Ngoc-Du Luong

PhD thesis of Ngoc-Du Luong (2017-2020)

Acquisition de données biologiques et développement de modèles statistiques en vue de quantifier le risque d’altération de la viande (Sandrine Guillou, Jeanne-Marie Membré et Louis Coroller)

Ngoc-Du-Luong.jpg
Ngoc-Du Luong

This thesis is part of a national project labeled by the French National Research Agency (ANR), the Redlosses project coordinated by Secalim.

 

Abstract:

The growth of bacteria during storage is a major cause of meat spoilage. Understanding the link between bacterial activities and spoilage occurrence is difficult due to the complexity of the food ecosystem and requires the integration of various experimental data. This thesis focuses on the development of statistical tools and the modeling of heterogeneous data from sensory, microbiological and physico-chemical analyzes, in order to better understand the spoilage of fresh pork and poultry sausages. Four different models have been developed. A mixed-effect model makes it possible to explore the effects of storage duration and control strategies implemented at the industrial level (lactate formulation and modified atmosphere). A Bayesian model describes the evolution of the pH of products. Three multivariate regression approaches assess the link between the initial microbiota and the dynamics of spoilage. Finally, a multi-block data integration approach establishes causal links between the microbiota, the volatiloma and sensory profiles.
These models confirmed the dynamic nature of the responses associated with spoilage. The formulation and the modified atmosphere were found to have a different effect depending on the type of meat and the response studied. The multi-block model made it possible to identify bacterial species at the origin of volatile molecules responsible for sensory perceptions. Progress towards predicting spoilage from microbiological data will require further exploration of these models suitable for processing complex data.

Valorisation:

  • Luong, N.-D. M., L. Coroller, M. Zagorec, N. Moriceau, V. Anthoine, S. Guillou and J.-M. Membre 2022. A Bayesian approach to describe and simulate the pH evolution of fresh meat products depending on the preservation conditions. Foods 11(8). https://doi.org/10.3390/foods11081114
  • Luong, N.-D. M., J.-M. Membré, L. Coroller, M. Zagorec, S. Poirier, S. Chaillou, M.-H. Desmonts, D. Werner, V. Cariou and S. Guillou 2021. Application of a path-modelling approach for deciphering causality relationships between microbiota, volatile organic compounds and off-odour profiles during meat spoilage. International Journal of Food Microbiology 348: 109208. https://doi.org/10.1016/j.ijfoodmicro.2021.109208. Ranking du JCR: Q1 (JCR® 2019).
  • Luong, N.-D. M., L. Coroller, M. Zagorec, J.-M. Membré and S. Guillou 2020. Spoilage of chilled fresh meat products during storage: A quantitative analysis of literature data. Microorganisms 8(8). Ranking du JCR: Q2 (JCR® 2019). https://doi.org/10.3390/microorganisms8081198.
  • Luong, N.-D. M., S. Jeuge, L. Coroller, C. Feurer, M.-H. Desmonts, N. Moriceau, V. Anthoine, S. Gavignet, A. Rapin, B. Frémaux, E. Robieu, M. Zagorec, J.-M. Membré and S. Guillou 2020. Spoilage of fresh turkey and pork sausages: Influence of potassium lactate and modified atmosphere packaging. Food Research International 137: 109501. Ranking du JCR: Q1 (JCR® 2019). https://doi.org/10.1016/j.foodres.2020.109501.
  • Poirier, S., N.-D. M. Luong, V. Anthoine, S. Guillou, J.-M. Membre, N. Moriceau, S. Reze, M. Zagorec, C. Feurer, B. Fremaux, S. Jeuge, E. Robieu, M. Champomier-Verges, G. Coeuret, E. Cauchie, G. Daube, N. Korsak, L. Coroller, N. Desriac, M.-H. Desmonts, R. Gohier, D. Werner, V. Loux, O. Rue, M.-H. Dohollou, T. Defosse and S. Chaillou 2020. Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced meat products subjected to changes in lactate concentration and packaging atmosphere. Data in brief 30: 105453-105453. Ranking du JCR: https://10.1016/j.dib.2020.105453.

Modification date: 21 November 2023 | Publication date: 17 May 2017 | By: SG