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Omnibus modeling of listeria monocytogenes growth rates at low temperatures

2021Journal article Open access
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dc.contributor.authorPennone, Vincenzo
dc.contributor.authorGonzales-Barron, Ursula
dc.contributor.authorHunt, Kevin
dc.contributor.authorCadavez, Vasco
dc.contributor.authorMcAuliffe, Olivia
dc.contributor.authorButler, Francis
dc.date.accessioned2018-02-19T10:00:00Z
dc.date.accessioned2021-11-22T14:46:31Z
dc.date.available2018-01-19T10:00:00Z
dc.date.available2021-11-22T14:46:31Z
dc.date.issued2021
dc.description.abstractListeria monocytogenes is a pathogen of considerable public health importance with a high case fatality. L. monocytogenes can grow at refrigeration temperatures and is of particular concern for ready-to-eat foods that require refrigeration. There is substantial interest in conducting and modeling shelf-life studies on L. monocytogenes, especially relating to storage temperature. Growth model parameters are generally estimated from constant-temperature growth experiments. Traditionally, first-order and second-order modeling (or primary and secondary) of growth data has been done sequentially. However, omnibus modeling, using a mixed-effects nonlinear regression approach, can model a full dataset covering all experimental conditions in one step. This study compared omnibus modeling to conventional sequential first-order/second-order modeling of growth data for five strains of L. monocytogenes. The omnibus model coupled a Huang primary model for growth with secondary models for growth rate and lag phase duration. First-order modeling indicated there were small significant differences in growth rate depending on the strain at all temperatures. Omnibus modeling indicated smaller differences. Overall, there was broad agreement between the estimates of growth rate obtained by the first-order and omnibus modeling. Through an appropriate choice of fixed and random effects incorporated in the omnibus model, potential errors in a dataset from one environmental condition can be identified and explored.en_EN
dc.description.sponsorshipThis research was part funded by the Irish Department of Agriculture, Food, and Marine Research Funding Program, Project Reference 17/F/244, “Understanding Listeria monocytogrenes growth in food”. U. Gonzales-Barron and V. Cadavez are grateful to the EU PRIMA program and the Portuguese Foundation for Science and Technology (FCT) for funding the ArtiSaneFood project (PRIMA/0001/2018) and to FCT for financial support through national funds FCT/MCTES to CIMO (UIDB/00690/2020). U. Gonzales-Barron acknowledges the national funding by FCT, P.I., through the Institutional Scientific Employment Program contract.
dc.description.versioninfo:eu-repo/semantics/publishedVersionen_EN
dc.identifier.citationPennone, Vincenzo; Gonzales-Barron, Ursula; Hunt, Kevin; Cadavez, Vasco; McAuliffe, Olivia; Butler, Francis (2021). Omnibus modeling of listeria monocytogenes growth rates at low temperatures. Foods. eISSN 2304-8158. 10:5, p. 1-14en_EN
dc.identifier.doi10.3390/foods10051099en_EN
dc.identifier.urihttp://hdl.handle.net/10198/24265
dc.language.isoeng
dc.peerreviewedyesen_EN
dc.relationInnovative Bio-interventions and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Mediterranean Artisanal Fermented Foods
dc.relationMountain Research Center
dc.subjectGrowth modelsen_EN
dc.subjectHuang modelen_EN
dc.subjectListeria monocytogenesen_EN
dc.subjectOmnibus modelingen_EN
dc.subjectPredictive microbiologyen_EN
dc.titleOmnibus modeling of listeria monocytogenes growth rates at low temperaturesen_EN
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInnovative Bio-interventions and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Mediterranean Artisanal Fermented Foods
oaire.awardTitleMountain Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PRIMA%2F0001%2F2018/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameGonzales-Barron
person.familyNameCadavez
person.givenNameUrsula
person.givenNameVasco
person.identifierR-000-HDG
person.identifier.ciencia-id0813-C319-B62A
person.identifier.ciencia-id441B-01AB-A12E
person.identifier.orcid0000-0002-8462-9775
person.identifier.orcid0000-0002-3077-7414
person.identifier.ridA-3958-2010
person.identifier.scopus-author-id9435483700
person.identifier.scopus-author-id9039121900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccessen_EN
rcaap.typearticleen_EN
relation.isAuthorOfPublication17c6b98f-4fb5-41d3-839a-6f77ec70021a
relation.isAuthorOfPublication57b410e9-f6b7-42ff-ab3d-b526278715eb
relation.isAuthorOfPublication.latestForDiscovery57b410e9-f6b7-42ff-ab3d-b526278715eb
relation.isProjectOfPublication75b223ba-4ae7-45dc-a445-c3acb8c8950e
relation.isProjectOfPublication29718e93-4989-42bb-bcbc-4daff3870b25
relation.isProjectOfPublication.latestForDiscovery29718e93-4989-42bb-bcbc-4daff3870b25

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