Influence of the Initial Cell Number on the Growth Fitness of Salmonella Enteritidis in Raw and Pasteurized Liquid Whole Egg, Egg White, and Egg Yolk

Guillén, Silvia; Marcén, Marcos; Álvarez, Ignacio; Mañas, Pilar; Cebrián, Guillermo

doi:10.3390/foods10071621

Cited by 4 publications

(1 citation statement)

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“…A QMRA needs mathematical models that provide quantitative estimates of the microbial response within the food chain (Allende et al., 2022 ). In this sense, the field of predictive microbiology is a well‐established methodology that defines the experimental and numerical protocols to define such models (Perez‐Rodriguez & Valero, 2013 ), that has served to define growth and inactivation models for most food pathogens (Guillén et al., 2021a , b ; Alvarenga et al., 2022 ; Georgalis et al., 2022 ). One of the main limitations of this approach is the complexity in the implementation of these mathematical models.…”

Section: Introductionmentioning

confidence: 99%

Training in modern statistical methodologies and software tools for the definition and analysis of (stochastic) quantitative microbial risk assessment models with a comparison between the Hungarian and Spanish food supply chains

Pleva,

Garre,

Escámez

2023

EFS2

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Human pathogenic Salmonella enterica strains have been infecting people since historical times. The original human pathogens, typhoid Salmonella strains (e.g. S. Typhi) played a huge role in the previous centuries but nowadays in the developed world the number of cases or outbreaks caused by these serotypes deceased due to the development of personal and public hygiene. Nowadays in these regions the animal‐borne zoonotic serotypes (e.g. S . Enteritidis) became more important because of their high prevalence in intensive animal husbandry. But these bacteria can also appear in fruits and vegetables. The fellow joined the scientific work of the Polytechnic University of Cartagena, Spain about the safety of plant‐based products, where he could gain experience in microbiological laboratory exercises and theoretical calculations of statistics and modelling. The activities in the laboratory were part of the research lines already established at the host institution, being based on the protocols they have already implemented. Nonetheless, the fellow had the opportunity to design his own experiment, do the experimental work required and analysed the data within the context of a qualitative microbiological risk assessment. The main focus was on the heat resistance of two strains of zoonotic Salmonella spp. at different temperatures. Experiments were done using a reference strain and an extremely resistant variant to evaluate this rare phenotype. The experiments were executed using a Mastia thermoresistometer, a device patented by the host institution that provides more control when studying thermal treatments than traditional methods. The data was analysed using the principles of predictive microbiology, using the D‐value as an estimate of heat resistance that provides insight into the bacterial behaviour. For this, the fellow used the bioinactivation software, developed within the host group. Through the work and results the fellow learned the principles of quantitative microbiological risk assessment (QMRA) and predictive microbiology, which was the aim for the EU‐FORA programme.

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