Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/49955
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Afonso, T. | por |
dc.contributor.author | Rodolfo, Moresco | por |
dc.contributor.author | Uarrota, Virgilio G. | por |
dc.contributor.author | Navarro, Bruno Bachiega | por |
dc.contributor.author | Nunes, Eduardo da C. | por |
dc.contributor.author | Marcelo, Maraschin | por |
dc.contributor.author | Rocha, Miguel | por |
dc.date.accessioned | 2018-02-01T09:17:00Z | - |
dc.date.available | 2018-02-01T09:17:00Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Afonso, T.; Rodolfo, Moresco; Uarrota, Virgilio G.; Navarro, Bruno Bachiega; Nunes, Eduardo da C.; Marcelo, Maraschin; Rocha, Miguel, UV-Vis and CIELAB based chemometric characterization of manihot esculenta carotenoid contents. Journal of Integrative Bioinformatics, 14(4, SI), 2017 | por |
dc.identifier.issn | 1613-4516 | por |
dc.identifier.uri | https://hdl.handle.net/1822/49955 | - |
dc.description.abstract | Vitamin A deficiency is a prevalent health problem in many areas of the world, where cassava genotypes with high pro-vitamin A content have been identified as a strategy to address this issue. In this study, we found a positive correlation between the color of the root pulp and the total carotenoid contents and, importantly, showed how CIELAB color measurements can be used as a non-destructive and fast technique to quantify the amount of carotenoids in cassava root samples, as opposed to traditional methods. We trained several machine learning models using UV-visible spectrophotometry data, CIELAB data and a low-level data fusion of the two. Best performance models were obtained for the total carotenoids contents calculated using the UV-visible dataset as input, with R2 values above 90 %. Using CIELAB and fusion data, values around 60 % and above 90 % were found. Importantly, these results demonstrated how data fusion can lead to a better model performance for prediction when comparing to the use of a single data source. Considering all these findings, the use of colorimetric data associated with UV-visible and HPLC data through statistical and machine learning methods is a reliable way of predicting the content of total carotenoids in cassava root samples. | por |
dc.description.sponsorship | To CNPq (National Counsel of Technological and Scientific Development) for financial support (Process n 407323/2013-9), to CAPES (Coordination for the Improvement of Higher Education Personnel (CAPES), and EPAGRI(AgriculturalResearchandRuralExtensionCompanyofSantaCatarina).Theresearchfellowshipfrom CNPqonbehalfofM.Maraschinisacknowledged.TheworkispartiallyfundedbyProjectPropMine,funded bytheagreementbetweenPortugueseFCT(FoundationforScienceandTechnology)andBrazilianCNPq. | por |
dc.language.iso | eng | por |
dc.publisher | De Gruyter Open | por |
dc.rights | openAccess | por |
dc.subject | Carotenoids | por |
dc.subject | Cassava genotypes | por |
dc.subject | Chemometrics | por |
dc.subject | CIELAB | por |
dc.subject | Machine learning | por |
dc.title | UV-Vis and CIELAB based chemometric characterization of manihot esculenta carotenoid contents | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.comments | CEB47425 | por |
oaire.citationIssue | 4, SI | por |
oaire.citationConferencePlace | Germany | - |
oaire.citationVolume | 14 | por |
dc.date.updated | 2018-01-28T14:13:37Z | - |
dc.identifier.eissn | 1613-4516 | por |
dc.identifier.doi | 10.1515/jib-2017-0056 | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Journal of Integrative Bioinformatics | por |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document_47425_1.pdf | 1,87 MB | Adobe PDF | Ver/Abrir |