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dc.contributor.authorKaptan, Mehmet
dc.contributor.authorBayazit, Ozan
dc.date.accessioned2023-08-18T06:41:22Z
dc.date.available2023-08-18T06:41:22Z
dc.date.issued2023en_US
dc.identifier.citationKaptan, M. & Bayazit, O. (2023). Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers. Journal of Food Process Engineering, 46(7), e14358. https://doi.org/10.1111/jfpe.14358en_US
dc.identifier.issn0145-8876
dc.identifier.issn1745-4530
dc.identifier.urihttps://doi.org/10.1111/jfpe.14358
dc.identifier.urihttps://hdl.handle.net/11436/8057
dc.description.abstractIt is crucial to ensure food security to continue the sustainable nutrition of the world population. Food losses in the global food supply chain pose a significant risk to food security. Especially foods that require cold chain logistics are prone to deterioration and eventually food losses. Therefore, cold chain logistics processes require operational expertise and specialized equipment. Reefer (refrigerated) container is the most used cold chain transport equipment for perishable foods requiring atmospheric control. Analyzing operational and hardware-related causes and implementing relevant countermeasures are necessary to prevent food losses in reefer containers. With this motivation in the study, the relationships between the factors causing food losses in the reefer containers were evaluated qualitatively and quantitatively via the model built using the Fuzzy Bayesian network method. The findings indicate that the most critical root causes of food losses in reefer containers are excessive time off-power, inappropriate preload conditions, and refrigerant faults, respectively. Moreover, the riskiest combination of factors that causes food loss consists of excessive time-off power, refrigerant faults, and adverse weather conditions during navigation and in port. When the existing legal framework and professional practices are examined, in light of the results of the study, the following will be recommended: Establishing minimum standard and maintenance arrangements for cooling systems, ensuring safety margin in the shelf life of the foods carried in the reefer containers, making mandatory the automatic temperature recordings systems, and increasing the number of personnel specialized in product types and transportation. The study results will benefit supply chain stakeholders for process planning and implementation to mitigate the risk of food losses in reefer containers.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFood securityen_US
dc.subjectFood transporten_US
dc.subjectFuzzy Bayesian networken_US
dc.subjectReefer containeren_US
dc.subjectRisk analysisen_US
dc.titleFuzzy Bayesian network analysis of the factors causing food losses in reefer containersen_US
dc.typearticleen_US
dc.contributor.departmentRTEÜ, Turgut Kıran Denizcilik Fakültesi, Deniz Ulaştırma İşletme Mühendisliği Bölümüen_US
dc.contributor.institutionauthorKaptan, Mehmet
dc.contributor.institutionauthorBayazit, Ozan
dc.identifier.doi10.1111/jfpe.14358en_US
dc.identifier.volume46en_US
dc.identifier.issue7en_US
dc.identifier.endpagee14358en_US
dc.relation.journalJournal of Food Process Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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