Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/39402

TitleUV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)
Author(s)Moresco, Rodolfo
Uarrota, Virgílio Gavicho
Pereira, Aline
Tomazzoli, Maíra Maciel
Nunes, Eduardo da C.
Peruch, Luiz Augusto Martins
Gazzola, Jussara
Costa, Christopher Borges
Rocha, Miguel
Maraschin, Marcelo
KeywordsChemometrics
Descriptive models
Partial metabolome
Cassava genotypes
Carotenoids
RP-HPLC
UV-vis
Issue dateOct-2015
PublisherDe Gruyter Open
JournalJournal of Integrative Bioinformatics
CitationMoresco, Rodolfo; Uarrota, Virgílio Gavicho; Pereira, Aline; Tomazzoli, Maíra Maciel; Nunes, Eduardo da C.; Peruch, Luiz Augusto Martins; Gazzola, Jussara; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo, UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz). Journal of Integrative Bioinformatics, 12(4), 280, 2015
Abstract(s)In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.
TypeArticle
URIhttp://hdl.handle.net/1822/39402
DOI10.2390/biecoll-jib-2015-280
ISSN1613-4516
e-ISSN1613-4516
Publisher versionhttp://journal.imbio.de/article.php?aid=280
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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