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Mathematical Models for Prediction of Temperature Effects on Kinetic Parameters of Microorganisms’ Inactivation: Tools for Model Comparison and Adequacy in Data Fitting

2017-09-18Journal article Open access
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datacite.subject.sdg12:Produção e Consumo Sustentáveis
datacite.subject.sdg13:Ação Climática
datacite.subject.sdg14:Proteger a Vida Marinha
dc.contributor.authorGil, Maria M
dc.contributor.authorMiller, Fátima A.
dc.contributor.authorBrandão, Teresa R. S.
dc.contributor.authorSilva, Cristina L. M.
dc.date.accessioned2025-06-05T13:36:52Z
dc.date.available2025-06-05T13:36:52Z
dc.date.issued2017-09-18
dc.description.abstractMicrobial inactivation often follows a sigmoidal kinetic behaviour, with an initial lag phase, followed by a maximum inactivation rate period and tending to a final as ymptotic value. Mathematically, such tendencies may be de scribed by using primary kinetic models (Gompertz based model is one example) that describe microbial survival throughout processing time when stressing conditions are ap plied. The parameters of kinetic models are directly affected by temperature. Despite the number of mathematical equa tions used to describe the dependence of the kinetic parame ters on temperature (so-called secondary models), there is a lack of studies regarding model comparison and adequacy in data fitting. This work provides a review of mathematical models that describe the temperature dependence of kinetic parameters related to microbial thermal inactivation. Regression analysis schemes and tests seeking model compar ison are presented. A case study is included to provide guid ance for the assessment of secondary model adequacy and regression analyses procedures. When modelling temperature effects on sigmoidal inactivation kinetics of microorganisms, one should be aware about the regression methodology ap plied. The most adequate models according to the two-step regression methodology may not be the best selection if a global fit is applied.eng
dc.description.sponsorshipFátima A. Miller and Teresa R.S. Brandão grate fully acknowledge Fundação para a Ciência e Tecnologia (FCT) and Fundo Social Europeu (FSE) for the financial support through the Post Doctoral grants SFRH/BPD/65041/2009 and SFRH/BPD/101179/2014, respectively. This study had the support of FCT, through the strategic project UID/MAR/04292/2013 granted to MARE and through project UID/Multi/50016/2013 granted to CBQF.
dc.identifier.citationGil, M.M., Miller, F.A., Brandão, T.R.S. et al. Mathematical Models for Prediction of Temperature Effects on Kinetic Parameters of Microorganisms’ Inactivation: Tools for Model Comparison and Adequacy in Data Fitting. Food Bioprocess Technol 10, 2208–2225 (2017). https://doi.org/10.1007/s11947-017-1989-x
dc.identifier.doi10.1007/s11947-017-1989-x
dc.identifier.issn1935-5130
dc.identifier.issn1935-5149
dc.identifier.urihttp://hdl.handle.net/10400.8/13125
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Science and Business Media LLC
dc.relationExploitation of bioactive and nutritive compounds from waste parts of fruits, seeking development of new strategies for adding value to fruit waste
dc.relationMARE - Marine and Environmental Sciences Centre
dc.relationCentre for Biotechnology and Fine Chemistry
dc.relationUID/Multi/50016/2013
dc.relation.hasversionhttp://link.springer.com/journal/11947
dc.relation.ispartofFood and Bioprocess Technology
dc.rights.uriN/A
dc.subjectMicrobial inactivation
dc.subjectMaximum inactivation rate
dc.subjectShoulder parameter
dc.subjectTemperature effects
dc.titleMathematical Models for Prediction of Temperature Effects on Kinetic Parameters of Microorganisms’ Inactivation: Tools for Model Comparison and Adequacy in Data Fittingeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleExploitation of bioactive and nutritive compounds from waste parts of fruits, seeking development of new strategies for adding value to fruit waste
oaire.awardTitleMARE - Marine and Environmental Sciences Centre
oaire.awardTitleCentre for Biotechnology and Fine Chemistry
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBPD%2F101179%2F2014/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMAR%2F04292%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMulti%2F50016%2F2013/PT
oaire.citation.endPage2225
oaire.citation.issue12
oaire.citation.startPage2208
oaire.citation.titleFood and Bioprocess Technology
oaire.citation.volume10
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameGil
person.givenNameMaria M
person.identifier.ciencia-id7313-A289-DF48
person.identifier.orcid0000-0002-8008-9839
person.identifier.ridO-4858-2015
person.identifier.scopus-author-id12785024700
project.funder.identifierhttp://doi.org/10.13039/501100001871
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
project.funder.nameFundação para a Ciência e a Tecnologia
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relation.isAuthorOfPublication.latestForDiscovery2461492f-3d73-40e9-a6ed-76944bcb1b71
relation.isProjectOfPublication76483a41-c3b9-4736-8ee5-c2397b203002
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