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A two-step factorial design for optimization of protein extraction from industrial rapeseed meal after ethanol-assisted reduction of antinutrients

dc.contributor.authorKalaydzhiev, H.
dc.contributor.authorBrandão, T. R. S.
dc.contributor.authorIvanova, P.
dc.contributor.authorSilva, C. L. M.
dc.contributor.authorChalova, V. I.
dc.date.accessioned2019-10-16T17:45:10Z
dc.date.available2019-10-16T17:45:10Z
dc.date.issued2019
dc.description.abstractRapeseed meal is a by-product of oil production with relatively high antinutrient content which limits its application in both feed and food industries. A two-step procedure, including two-level full factorial and central composite designs, was used to assess the influence of five factors namely pH (6 and 12), temperature (20 and 40 degrees C), NaCl concentration (0 and 7.5%), rapeseed meal concentration (2.5 and 5%), and extraction longevity (15 and 60 min) on protein extraction from industrial rapeseed meal subjected to ethanol-assisted reduction of antinutrients. Data demonstrated that pH and its interaction with NaCl influenced protein extractability the most. While still significant, individual effects of NaCl, extraction longevity, temperature and its interaction with pH had a less significant effect on protein yield. Overall. higher protein yields were obtained in response to combining high pH values with low NaCl concentrations, and high pH values with high temperatures. The highest protein yield (59.56 +/- 1.29%) was achieved after extraction of 5% ethanol-treated rapeseed meal at pH 12 with no NaCl addition, at 40 degrees C and extraction longevity of 60 min. A second-order polynomial model for protein yield prediction was generated. The adequacy of the model was verified by coefficient of determination and residual analyses. A high correlation between experimentally obtained and predicted protein yields (R-2 = 0.95) was established. Since extraction conditions are strong determinants of protein characteristics, the predictive model generated in the present work is useful for the selection of factor combinations, which allows for the achievement of optimal protein yield of a product with desired techno-functional properties.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationKalaydzhiev, H., Brandão, T. R. S., Ivanova, P., Silva, C. L. M., Chalova, V. I. (2019). A two-step factorial design for optimization of protein extraction from industrial rapeseed meal after ethanol-assisted reduction of antinutrients. International Food Research Journal, 26(4), 1155-1163pt_PT
dc.identifier.eid85072603712
dc.identifier.eissn2231-7546
dc.identifier.issn1985-4668
dc.identifier.urihttp://hdl.handle.net/10400.14/28380
dc.identifier.wos000483983800005
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherUniversiti Putra Malaysia Presspt_PT
dc.relation577 / 17.08.2018
dc.subjectEthanol-treated rapeseed mealpt_PT
dc.subjectProtein yield optimizationpt_PT
dc.subjectResponse surface methodologypt_PT
dc.titleA two-step factorial design for optimization of protein extraction from industrial rapeseed meal after ethanol-assisted reduction of antinutrientspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1163
oaire.citation.issue4
oaire.citation.startPage1155
oaire.citation.titleInternational Food Research Journalpt_PT
oaire.citation.volume26
person.familyNameBrandão
person.familyNameSilva
person.givenNameTeresa
person.givenNameCristina
person.identifierJ-9418-2012
person.identifier1473674
person.identifier.ciencia-id7B19-E23B-BB31
person.identifier.ciencia-id6611-634A-132C
person.identifier.orcid0000-0002-8857-6471
person.identifier.orcid0000-0002-0495-3955
person.identifier.ridJ-9418-2012
person.identifier.ridA-3568-2013
person.identifier.scopus-author-id6602174128
person.identifier.scopus-author-id7201387397
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationebf7ead0-3772-4fd6-988c-f6b8722de84e
relation.isAuthorOfPublication4e2903de-0679-4cb1-981e-10de14c0c995
relation.isAuthorOfPublication.latestForDiscovery4e2903de-0679-4cb1-981e-10de14c0c995

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