ArticleEFSA journal. European Food Safety Authority2024
Combined stochastic modelling of pathogenic and spoilage microorganisms.
Article in EFSA journal. European Food Safety Authority, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Beyond predictive accuracy: A case for mechanism-informed, uncertainty-aware machine learning in food microbiology.iScience · 2026Review
- Probabilistic MIC modelling for AMR risk assessment.EFSA journal. European Food Safety Authority · 2025Article
- Application of Machine Learning in Food Safety Risk Assessment.Foods (Basel, Switzerland) · 2025Review
- Combined stochastic modelling of pathogenic and spoilage microorganisms.EFSA journal. European Food Safety Authority · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative microbiological risk assessment (QMRA) of pathogens in food safety is well established, but steps are being taken to expand this methodology to food spoilage. Parallels can be drawn between the steps involved in a QMRA for pathogens and its application to specific spoilage organisms (SSO). During hazard characterisation for pathogens, the appropriate dose-response model is used to link the hazard level to the health outcome by estimating the probability of illness, resulting from the ingestion of a certain dose of the hazard. The dose-response model, in the case of food spoilage, may be translated into a spoilage-response relationship linking the spoilage-level with the probability the consumer will discard the food and not consume it. Such models are developed with sensory testing, assessing consumers sensitivity to microbial spoilage quality defects and correlating them to the SSO concentration. Ignoring food spoilage before the stated expiration date can lead to the final health risk being overestimated, since cases in which the food item poses a real risk to the consumer but is not consumed due to perceived spoilage are not excluded. Plenty of risk assessments have been carried out for pathogens in different RTE foods. What is missing is the integration of the two approaches into a single model that can estimate the risk of illness, factoring in the variability of consumer responses to spoilage. The spoilage-response relationship was combined with a stochastic modelling approach for lactic acid bacteria (LAB) and
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