Towards tailored guidelines for microbial air quality in the food industry.

airborne microorganisms food contamination quantitative limits risk assessment

Journal

International journal of food microbiology
ISSN: 1879-3460
Titre abrégé: Int J Food Microbiol
Pays: Netherlands
ID NLM: 8412849

Informations de publication

Date de publication:
04 Jun 2024
Historique:
received: 15 01 2024
revised: 10 04 2024
accepted: 01 06 2024
medline: 10 6 2024
pubmed: 10 6 2024
entrez: 9 6 2024
Statut: aheadofprint

Résumé

Airborne microorganisms in food processing environments pose a potential risk for food product contamination. Yet, the absence of established standards or guidelines setting quantitative limits on airborne microorganisms underscores a critical gap in current regulatory frameworks. This review seeks to explore the feasibility of establishing quantitative limits for airborne microorganisms in food processing facilities, aiming to provide evidence-based guidance to enhance food safety practices in the industry. The review begins by addressing the complexities of microbial air quality in the food industry through a general literature search covering sources of airborne microorganisms, factors affecting particle deposition, air sampling methods and preventive measures. Subsequently, it employs a structured approach to assess the significance of air quality and its impact on product quality. Utilizing the PRISMA method, relevant scientific literature from May 2002 to May 2022 was examined, resulting in 26 articles meeting inclusion criteria from a pool of 11,737 original research papers. Additionally, the review investigates existing probability models for assessing airborne contamination to enhance air quality risk assessment in food safety management systems. The literature reveals a lack of substantial evidence supporting a direct correlation between airborne microorganisms and food contamination. The absence of standardized air sampling methodologies in previous studies hinders the comparability and reliability of research findings. Additionally, the literature fails to establish a conclusive relationship between influencing factors such as total particle counts, temperature, relative humidity and airborne contamination. Contradictory probability models for quantifying airborne contamination, and the absence of tailored preventive measures, hinder effective control and undermine microbial contamination control in diverse food processing contexts. In conclusion, the development of numeric guidelines for airborne contamination necessitates a tailored approach, considering factors such as product characteristics and production context. By integrating risk assessment models into this process, a more thorough comprehension of contamination risks can be achieved, providing tailored guidance based on the identified risk levels for each product. Ongoing collaborative efforts are essential to develop evidence-based guidelines that effectively mitigate risks without incurring unnecessary costs.

Identifiants

pubmed: 38852216
pii: S0168-1605(24)00223-X
doi: 10.1016/j.ijfoodmicro.2024.110779
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

110779

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Pieter-Jan Loveniers (PJ)

Research Unit VEG-i-TEC, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Campus Kortrijk, Sint-Martens-Latemlaan 2B, 8500 Kortrijk, Belgium.

Frank Devlieghere (F)

Research Unit Food Microbiology and Food Preservation (FMFP), Department of Food Technology, Safety and Health, Ghent University, Coupure Links 653, 9000 Ghent, Belgium.

Imca Sampers (I)

Research Unit VEG-i-TEC, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Campus Kortrijk, Sint-Martens-Latemlaan 2B, 8500 Kortrijk, Belgium. Electronic address: imca.sampers@ugent.be.

Classifications MeSH