Determination of carotenoid and tocopherol content in maize flour and oil samples using near-infrared spectroscopy

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dc.contributor.authorKahrıman, Fatih
dc.contributor.authorOnac, Iskender
dc.contributor.authorTurk, Figen Mert
dc.contributor.authorOner, Fatih
dc.contributor.authorEgesel, Cem Omer
dc.date.accessioned2025-01-27T21:04:22Z
dc.date.available2025-01-27T21:04:22Z
dc.date.issued2019
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractSecondary metabolites are important components in terms of nutrition and health. Carotenoids and tocopherols, two groups of the fat-soluble components, are also included in this category. There is an increasing interest in the detection of secondary metabolites with near-infrared spectroscopy. However, the number of scientific studies for the detection of these components, especially for tocopherols in corn flour or oil samples by near-infrared reflectance spectroscopy is rather limited. This study was carried out to determine the amount of carotenoids and tocopherols in flour and oil samples of 250 different maize genotypes by near-infrared reflectance spectroscopy using the partial least squares regression modeling method. Liquid chromatography mass spectrophotometry was used as a reference method in order to determine the contents of five carotenoids and four tocopherol subcomponents. The estimation models were created by using the spectral data collected from ground samples, and oil samples extracted from the same flour; along with the results of the reference analysis. The reliability of these models was tested by external validation (n?=?50). The prediction models generated by the spectra taken from corn flour yielded more successful results than the models created with the spectra taken from the oil samples. Among the models compared, the one developed with the spectra taken from flour samples for lutein was the most successful. It is seen that the estimation models generated from flour samples can be used for screening purposes, though different approaches are needed to increase the success of models.
dc.description.sponsorshipScientific and Technological Research Council of Turkey [T_UB_ITAK 215O867]
dc.description.sponsorshipThis work was supported by The Scientific and Technological Research Council of Turkey [Project Number: T_UB_ITAK 215O867]. We thank T_UB_ITAK for financial support of this study.
dc.identifier.doi10.1080/00387010.2019.1671872
dc.identifier.endpage481
dc.identifier.issn0038-7010
dc.identifier.issn1532-2289
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85073614211
dc.identifier.scopusqualityQ3
dc.identifier.startpage473
dc.identifier.urihttps://doi.org/10.1080/00387010.2019.1671872
dc.identifier.urihttps://hdl.handle.net/20.500.12428/27624
dc.identifier.volume52
dc.identifier.wosWOS:000489441800001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofSpectroscopy Letters
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectAntioxidants
dc.subjectmodel development
dc.subjectpartial least squares
dc.subjectZea mays
dc.titleDetermination of carotenoid and tocopherol content in maize flour and oil samples using near-infrared spectroscopy
dc.typeArticle

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