Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/50702
Registro completo de metadados
Campo DCValorIdioma
dc.creatorAbreu, Danilo José Machado de-
dc.creatorLorenço, Mario Sérgio-
dc.creatorFerreira, Aline Norberto-
dc.creatorScalice, Henrique Kovacs-
dc.creatorVilas Boas, Eduardo Valério de Barros-
dc.creatorPiccoli, Roberta Hilsdorf-
dc.creatorCarvalho, Elisângela Elena Nunes-
dc.date.accessioned2022-07-22T22:19:32Z-
dc.date.available2022-07-22T22:19:32Z-
dc.date.issued2022-
dc.identifier.citationABREU, D. J. M. de et al. Artificial neural networks for the evaluation of physicochemical properties of carrots (Daucus carota L.) subjected to different cooking conditions as an alternative to traditional statistical methods. ACS Food Science & Technology, [S.l.], v. 2, n. 1, p. 143-150, 2022.pt_BR
dc.identifier.urihttps://pubs.acs.org/doi/10.1021/acsfoodscitech.1c00375pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/50702-
dc.description.abstractThe study aimed to evaluate the impact of different cooking methods (sous vide, boiling, and steamed) on the physicochemical properties of carrots (Daucus carota L.). The colorimetric parameters, texture, carotenoid content, and antioxidant capacity of carrots were observed. The steam cooking method proved to be the best method to preserve the concentration of carotenoids and showed a protection of about 40%, regarding the antioxidant capacity, a property also observed in the sous vide method, independent of the time. In terms of texture, the steam cooking method rendered them a greater softness. Moreover, this study corroborates that artificial neural networks (ANNs) can be used as an effective tool for data treatments by grouping according to their similarities. The results obtained with ANN provided the same information when compared to those of the commonly used traditional multivariate statistical techniques considering that the self-organizing maps proved to be easier to visualize and analyze.pt_BR
dc.languageen_USpt_BR
dc.publisherACS Publicationspt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceACS Food Science & Technologypt_BR
dc.subjectBoiledpt_BR
dc.subjectSous vidept_BR
dc.subjectSteampt_BR
dc.subjectPrincipal Component Analysis (PCA)pt_BR
dc.subjectHierarchical Cluster Analysis (HCApt_BR
dc.subjectSelf-organizing mapspt_BR
dc.titleArtificial neural networks for the evaluation of physicochemical properties of carrots (Daucus carota L.) subjected to different cooking conditions as an alternative to traditional statistical methodspt_BR
dc.typeArtigopt_BR
Aparece nas coleções:DCA - Artigos publicados em periódicos

Arquivos associados a este item:
Não existem arquivos associados a este item.


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.