A Systematic Review of Beef Meat Quantitative Microbial Risk Assessment Models

Vincent Tesson, Michel Federighi, Enda Cummins, Juliana de Oliveira Mota, Sandrine Guillou and Géraldine Boué
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Vincent Tesson: INRA, Oniris, SECALIM, 44307 Nantes, France
Michel Federighi: INRA, Oniris, SECALIM, 44307 Nantes, France
Enda Cummins: Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, Agriculture and Food Science Centre, University College Dublin, Belfield, Dublin 4, Ireland
Juliana de Oliveira Mota: INRA, Oniris, SECALIM, 44307 Nantes, France
Sandrine Guillou: INRA, Oniris, SECALIM, 44307 Nantes, France
Géraldine Boué: INRA, Oniris, SECALIM, 44307 Nantes, France

IJERPH, 2020, vol. 17, issue 3, 1-28

Abstract: Each year in Europe, meat is associated with 2.3 million foodborne illnesses, with a high contribution from beef meat. Many of these illnesses are attributed to pathogenic bacterial contamination and inadequate operations leading to growth and/or insufficient inactivation occurring along the whole farm-to-fork chain. To ensure consumer health, decision-making processes in food safety rely on Quantitative Microbiological Risk Assessment (QMRA) with many applications in recent decades. The present study aims to conduct a critical analysis of beef QMRAs and to identify future challenges. A systematic approach, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was used to collate beef QMRA models, identify steps of the farm-to-fork chain considered, and analyze inputs and outputs included as well as modelling methods. A total of 2343 articles were collected and 67 were selected. These studies focused mainly on western countries and considered Escherichia coli (EHEC) and Salmonella spp. pathogens. Future challenges were identified and included the need of whole-chain assessments, centralization of data collection processes, and improvement of model interoperability through harmonization. The present analysis can serve as a source of data and information to inform QMRA framework for beef meat and will help the scientific community and food safety authorities to identify specific monitoring and research needs.

Keywords: food safety; meat; beef processing; farm-to-fork; mathematical model; predictive microbiology; QMRA (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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