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Estimation of proximate composition of quinoa (Chenopodium quinoa Willd.) flour by near-infrared transmission spectroscopy

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dc.contributor.authorEncina-Zelada, Christian
dc.contributor.authorCadavez, Vasco
dc.contributor.authorPereda, Jorge
dc.contributor.authorGómez-Pando, Luz
dc.contributor.authorSalvá-Ruíz, Bettit
dc.contributor.authorIbañez, Martha
dc.contributor.authorTeixeira, José
dc.contributor.authorGonzales-Barron, Ursula
dc.date.accessioned2018-03-23T16:47:18Z
dc.date.available2018-03-23T16:47:18Z
dc.date.issued2017
dc.description.abstractThe aim of this study was to develop chemometric models for protein, fat, ashes and carbohydrates contents of quinoa flour using Near-Infrared Transmission (NIT) spectroscopy. Spectra of quinoa flour obtained from grains of 70 different cultivars were scanned while dietary constituents were determined by reference AOAC methods. As a pre-treatment, spectra were subjected to extended multiplicative signal correction (EMSC) with polynomial degree 0, 1 or 2. Next, the Canonical Powered Partial Least Squares (CPPLS) algorithm was applied, and models were compared in terms of accuracy and predictability. For all models, root mean square errors of cross-validation (RMSECV), root meat square errors of prediction (RMSEP) and coefficient of correlation of cross-validation (RCV) were computed. Robust models were obtained when quinoa spectra were pre-processed using EMSC of polynomial degree 2 for both fat (RMSECV: 0.268% and RMSEP: 0.256%) and carbohydrates (RMSECV: 0.641% and RMSEP: 0.643%) following extraction of five CPPLS latent variables. Good coefficients of correlation of prediction (RP: 0.690–0.821) were found for all constituents when models were validated on a test data set consisting of 13 quinoa flour spectra. Thus, good predictions of the dietary constituents of quinoa flour could be achieved by using NIT technology, as implied by the low coefficient of variation of prediction (CVP): 5.64% for protein, 3.88% for fat 7.32% for ashes and 0.80% for carbohydrates contents.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationEncina-Zelada, Christian; Cadavez, Vasco; Pereda, Jorge; Gómez-Pando, Luz; Salvá-Ruiz, Bettit; Ibañez, Martha; Teixeira, José A.; Gonzales-Barron, Ursula A. (2017). Estimation of proximate composition of quinoa (Chenopodium quinoa Willd.) flour by near-infrared transmission spectroscopy. In Proceedings of the International Congress on Engineering and Sustainability in the XXI Century. [S.l.]: Springer, p. 227-235. iSBN 978-3-319-70271-1pt_PT
dc.identifier.isbn978-3-319-70271-1
dc.identifier.urihttp://hdl.handle.net/10198/16503
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectQuinoa flourpt_PT
dc.subjectCalibrationpt_PT
dc.subjectChemometricspt_PT
dc.subjectBootstrappt_PT
dc.titleEstimation of proximate composition of quinoa (Chenopodium quinoa Willd.) flour by near-infrared transmission spectroscopypt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceFaro, Portugalpt_PT
oaire.citation.endPage235pt_PT
oaire.citation.startPage227pt_PT
oaire.citation.titleProceedings of the International Congress on Engineering and Sustainability in the XXI Centurypt_PT
person.familyNameCadavez
person.familyNameGonzales-Barron
person.givenNameVasco
person.givenNameUrsula
person.identifierR-000-HDG
person.identifier.ciencia-id441B-01AB-A12E
person.identifier.ciencia-id0813-C319-B62A
person.identifier.orcid0000-0002-3077-7414
person.identifier.orcid0000-0002-8462-9775
person.identifier.ridA-3958-2010
person.identifier.scopus-author-id9039121900
person.identifier.scopus-author-id9435483700
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication57b410e9-f6b7-42ff-ab3d-b526278715eb
relation.isAuthorOfPublication17c6b98f-4fb5-41d3-839a-6f77ec70021a
relation.isAuthorOfPublication.latestForDiscovery57b410e9-f6b7-42ff-ab3d-b526278715eb

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