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Modelling in Drying Technology of Food Products: A Comprehensive Survey.

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dc.contributor.authorGuiné, Raquel
dc.contributor.authorGolpour, I.
dc.contributor.authorBarroca, M. J.
dc.contributor.authorKaveh, M.
dc.date.accessioned2020-11-03T08:29:34Z
dc.date.available2020-11-03T08:29:34Z
dc.date.issued2020
dc.description.abstractDrying of foods has been used to preserve food and agricultural products since immemorial times. However, still nowadays it assumes a prominent place among food processing technologies applied industrially to extend shelf life of foods. Although having some important advantages, like the reduction in water activity and subsequent minimization of degradation reactions of biological, chemical or enzymatic nature, reduction in size for transportation and storage or avoidance of refrigeration systems during transportation and storage, it is also true that drying brings high energy costs and some possible undesirable changes in quality parameters. Hence, the optimization of drying processes is of the utmost importance to minimize energy costs and maximize quality. Mathematical modelling in food process engineering allows important savings, while also guaranteeing the safety of industrial plants and workers, and finally achieving ultimate quality of the dried foods. Because artificial neural networks (ANNs) have been gaining importance in the context of many problems in the fields of engineering, among others, this chapter aims to do a review of scientific literature about the use of artificial neural networks to modelling and optimization of food drying processes. Finally, opportunities and restrictions of the ANNs technique for drying process simulation, optimization, and control are achieved to guide future R&D in this area.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationGuiné R, Golpour I, Barroca MJ and Kaveh M (2020) Application of Artificial Neural Networks (ANNS) Modelling in Drying Technology of Food Products: A Comprehensive Survey. In Skaar S (Ed.) A Comprehensive Guide to Neural Network Modeling. Chapter 1, pp. 1-56, Nova Science Publishers, Inc., USA.pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.19/6396
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherNova Science Publishers, Inc., USApt_PT
dc.relation.publisherversionhttps://novapublishers.com/shop/a-comprehensive-guide-to-neural-network-modeling/pt_PT
dc.subjectdrying technologypt_PT
dc.subjectprocess control and modellingpt_PT
dc.titleModelling in Drying Technology of Food Products: A Comprehensive Survey.pt_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.conferencePlaceEUApt_PT
oaire.citation.endPage56pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleA Comprehensive Guide to Neural Network Modelingpt_PT
person.familyNamede Pinho Ferreira Guiné
person.givenNameRaquel
person.identifierhttps://scholar.google.pt/citations?user=abFDovIAAAAJ&hl=pt-PT
person.identifier.ciencia-id8B13-5492-0F23
person.identifier.orcid0000-0003-0595-6805
person.identifier.scopus-author-id6603138390
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublication59580952-77cc-4e4e-ae90-527a8b994f9f
relation.isAuthorOfPublication.latestForDiscovery59580952-77cc-4e4e-ae90-527a8b994f9f

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