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Response surface methodology and artificial neural network modeling as predictive tools for phenolic compounds recovery from olive pomace

2024Journal article Open access
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dc.contributor.authorSilva, Ana Rita
dc.contributor.authorAyuso, Manuel
dc.contributor.authorOludemi, Taofiq
dc.contributor.authorGonçalves, Alexandre
dc.contributor.authorMelgar Castañeda, Bruno
dc.contributor.authorBarros, Lillian
dc.date.accessioned2024-01-15T11:58:35Z
dc.date.available2024-01-15T11:58:35Z
dc.date.issued2024
dc.description.abstractThis study optimized the extraction of three major phenolic compounds (oleuropein, tyrosol, and verbascoside) from olive pomace using microwave- and ultrasonic-assisted methods. Screening factorial design (SFD) and central composite design (CCD) were employed, and response surface methodology (RSM) and artificial neural networks (ANN) were used for data modeling. The microwave-assisted method in the SFD yielded higher compound amounts, with verbascoside showing a four-fold increase compared to the ultrasonic-assisted method. Factors like vessel diameter, ultrasonic power using UAE, and solvent acidity in both techniques had minimally impacted extractability. CCD-RSM revealed temperaturés significantly affect on oleuropein, but improved tyrosol recovery, with the effect on verbascoside being influenced by the temperature range. RSM and ANN integration enhanced understanding and prediction of factor behavior. Microwave-assisted extraction at 113 ◦C for 26 min, with minimum ramp time of 7.7 min, yielded 67.4, 57, and 5.1 mg of oleuropein, tyrosol, and verbascoside per gram of extract, respectively, with a prediction error ranging from 0.83 to 15.19.pt_PT
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT) for financial support to CIMO (UIDB/00690/2020 and UIDP/00690/2020), SusTEC (LA/P/0007/2020), L. Barros institutional contract, and Ana Rita Silva Doctoral Grant (SFRH/BD/145834/2019). To the ERDF through the Regional Operational Program North 2020, within the scope of the project OliveBIOextract (NORTE-01-0247- FEDER-049865). B. Melgar thanks the ERDF through the Regional Operational Program North 2020 for his contract within the Project OleaChain (NORTE-06-3559-FSE-000188). To MICINN for supporting the JDC contract of T. Oludemi (FJC2019-042549-I). Manuel Ayuso thanks PRIMA and FEDER-Interreg Espana- Portugal programme for financial support through the Local-NutLeg project (Section 1 2020 Agrofood Value Chain topic 1.3.1pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSilva, Ana Rita; Ayuso, Manuel; Oludemi, Taofiq; Gonçalves, Alexandre; Melgar, Bruno; Barros, Lillian (2024). Response surface methodology and artificial neural network modeling as predictive tools for phenolic compounds recovery from olive pomace. Separation and Purification Technology. ISSN 1383-5866. 330, p. 1-9pt_PT
dc.identifier.doi10.1016/j.seppur.2023.125351pt_PT
dc.identifier.eissn1873-3794
dc.identifier.issn1383-5866
dc.identifier.urihttp://hdl.handle.net/10198/29184
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relationMountain Research Center
dc.relationMountain Research Center
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relationCytinus hypocistis L. L.: a case study for the development of an innovative, safe, and effective anti-photoaging cosmeceutical formulation
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectOlive pomacept_PT
dc.subjectPhenolic compoundspt_PT
dc.subjectDesign of experimentspt_PT
dc.subjectResponse surface methodologypt_PT
dc.subjectArtificial neural networkspt_PT
dc.titleResponse surface methodology and artificial neural network modeling as predictive tools for phenolic compounds recovery from olive pomacept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMountain Research Center
oaire.awardTitleMountain Research Center
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardTitleCytinus hypocistis L. L.: a case study for the development of an innovative, safe, and effective anti-photoaging cosmeceutical formulation
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F145834%2F2019/PT
oaire.citation.endPage9pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleSeparation and Purification Technologypt_PT
oaire.citation.volume330pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPOR_NORTE
person.familyNameSilva
person.familyNameAyuso
person.familyNameOludemi
person.familyNameMelgar Castañeda
person.familyNameBarros
person.givenNameAna Rita
person.givenNameManuel
person.givenNameTaofiq
person.givenNameBruno
person.givenNameLillian
person.identifierABD-5857-2020
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person.identifier.ciencia-id6511-A057-C55F
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person.identifier.ciencia-id801C-0CD0-033F
person.identifier.ciencia-id9616-35CB-D001
person.identifier.orcid0000-0001-5819-9065
person.identifier.orcid0000-0002-1697-3857
person.identifier.orcid0000-0003-2822-3532
person.identifier.orcid0000-0002-5825-6872
person.identifier.orcid0000-0002-9050-5189
person.identifier.ridJ-3600-2013
person.identifier.scopus-author-id56725706500
person.identifier.scopus-author-id35236343600
project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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