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Machine learning to identify olive-tree cultivars

2022Conference paper Restricted access
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dc.contributor.authorMendes, João
dc.contributor.authorLima, José
dc.contributor.authorCosta, Lino
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorBrandão, Diego
dc.contributor.authorLeitão, Paulo
dc.contributor.authorPereira, Ana I.
dc.date.accessioned2023-02-27T16:59:23Z
dc.date.available2023-02-27T16:59:23Z
dc.date.issued2022
dc.description.abstractThe identification of olive-tree cultivars is a lengthy and expensive process, therefore, the proposed work presents a new strategy for identifying different cultivars of olive trees using their leaf and machine learning algorithms. In this initial case, four autochthonous cultivars of the Trás-os-Montes region in Portugal are identified (Cobrançosa, Madural, Negrinha e Verdeal). With the use of this type of algorithm, it is expected to replace the previous techniques, saving time and resources for farmers. Three different machine learning algorithms (Decision Tree, SVM, Random Forest) were also compared and the results show an overall accuracy rate of the best algorithm (Random Forest) of approximately 93%.pt_PT
dc.description.sponsorshipThis work was carried out under the Project “OleaChain: Competências para a sustentabilidade e inovação da cadeia de valor do olival tradicional no Norte Interior de Portugal” (NORTE06-3559-FSE-000188), an operation to hire highly qualified human resources, funded by NORTE 2020 through the European Social Fund (ESF). The authors are grateful to the Foundation for Science and Technology (FCT,Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).pt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.citationMendes, João; Lima, José; Costa, Lino; Rodrigues, Nuno G.; Brandão, Diego; Leitão, Paulo; Pereira, Ana I. (2022). Machine learning to identify olive-tree cultivars. In 2nd International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022. Bragançapt_PT
dc.identifier.doi10.1007/978-3-031-23236-7_56
dc.identifier.urihttp://hdl.handle.net/10198/27263
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectMachine learningpt_PT
dc.subjectIdentificationpt_PT
dc.subjectLeafpt_PT
dc.subjectCultivarspt_PT
dc.subjectVarietiespt_PT
dc.titleMachine learning to identify olive-tree cultivarspt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.conferencePlaceBragançapt_PT
oaire.citation.title2nd International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMendes
person.familyNameLima
person.familyNameRodrigues
person.familyNameLeitão
person.familyNamePereira
person.givenNameJoão
person.givenNameJosé
person.givenNameNuno
person.givenNamePaulo
person.givenNameAna I.
person.identifier2726655
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person.identifier.ciencia-id8316-8F13-DA71
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0000-0003-0979-8314
person.identifier.orcid0000-0001-7902-1207
person.identifier.orcid0000-0002-9305-0976
person.identifier.orcid0000-0002-2151-7944
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridL-3370-2014
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id57225794972
person.identifier.scopus-author-id55851941311
person.identifier.scopus-author-id55258560600
person.identifier.scopus-author-id35584388900
person.identifier.scopus-author-id15071961600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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