The use of predictive microbiology for the prediction of the shelf life of food products

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dc.contributor.authorTarlak, Fatih
dc.date.accessioned2024-06-13T20:18:32Z
dc.date.available2024-06-13T20:18:32Z
dc.date.issued2023
dc.departmentFakülteler, Sağlık Bilimleri Fakültesi, Beslenme ve Diyetetik Bölümü
dc.description.abstractMicrobial shelf life refers to the duration of time during which a food product remains safe for consumption in terms of its microbiological quality. Predictive microbiology is a field of science that focuses on using mathematical models and computational techniques to predict the growth, survival, and behaviour of microorganisms in food and other environments. This approach allows researchers, food producers, and regulatory bodies to assess the potential risks associated with microbial contamination and spoilage, enabling informed decisions to be made regarding food safety, quality, and shelf life. Two-step and one-step modelling approaches are modelling techniques with primary and secondary models being used, while the machine learning approach does not require using primary and secondary models for describing the quantitative behaviour of microorganisms, leading to the spoilage of food products. This comprehensive review delves into the various modelling techniques that have found applications in predictive food microbiology for estimating the shelf life of food products. By examining the strengths, limitations, and implications of the different approaches, this review provides an invaluable resource for researchers and practitioners seeking to enhance the accuracy and reliability of microbial shelf life predictions. Ultimately, a deeper understanding of these techniques promises to advance the domain of predictive food microbiology, fostering improved food safety practices, reduced waste, and heightened consumer confidence.
dc.description.sponsorshipIstanbul Gedik University
dc.identifier.doi10.3390/foods12244461
dc.identifier.issn2304-8158
dc.identifier.issue24
dc.identifier.pmid38137265
dc.identifier.scopus2-s2.0-85180655225
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/foods12244461
dc.identifier.urihttps://hdl.handle.net/11501/1431
dc.identifier.volume12
dc.identifier.wosWOS:001131104800001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorTarlak, Fatih
dc.institutionauthorid0000-0001-5351-1865
dc.language.isoen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.relation.ispartofFoods
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectModelling
dc.subjectMicrobial Growth
dc.subjectSpoilage
dc.subjectMachine Learning Approach
dc.titleThe use of predictive microbiology for the prediction of the shelf life of food products
dc.typeReview Article

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