Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/24923

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Campo DCValorIdioma
dc.contributor.authorMesquita, D. P.-
dc.contributor.authorSelvaggio, Gianluca-
dc.contributor.authorCunha, J. R.-
dc.contributor.authorLeal, Cristiano S.-
dc.contributor.authorAmaral, A. L.-
dc.contributor.authorFerreira, Eugénio C.-
dc.date.accessioned2013-08-02T16:49:17Z-
dc.date.available2013-08-02T16:49:17Z-
dc.date.issued2013-
dc.identifier.citationMesquita, D.P., Selvaggio, G., Cunha, J.R., Leal, C.S., Amaral, A.L., Ferreira, E.C. (2013). Image Analysis for Automatic Characterization of Polyhydroxyalcanoates Granules. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_91-
dc.identifier.isbn978-3-642-39093-7por
dc.identifier.issn1611-3349por
dc.identifier.urihttps://hdl.handle.net/1822/24923-
dc.description.abstractA new monitoring approach for polyhydroxyalcanoates (PHA) granules identification and characterization based on image analysis procedures is proposed. PHA granules were analyzed by Sudan Black B (SBB) staining in an enhanced biological phosphorus removal (EBPR) system. Color images captured on an optical microscope were analyzed through quantitative image analysis. The distribution of PHA granules was estimated by determination of the proportion of blue-black pixels. A relationship was found between image analysis parameters and PHA concentration. In conclusion, it may be inferred that the present image analysis procedure is suitable to quantify PHA granules in SBB staining images and a promising alternative to standard analysis.por
dc.description.sponsorshipFundação para a Ciência e a Tecnologia (FCT) in Portugal is gratefully acknowledged by their financial support through the project PTDC/EBB-EBI/103147/2008. D.P. Mesquita would like to acknowledge FCT for a post-doctoral grant (SFRH/BPD/82558/2011). G. Selvaggio also acknowledges FCT for a doctoral grant (SFRH/BD/51576/2011).-
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/PTDC%2FEBB-EBI%2F103147%2F2008/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/FARH/SFRH%2FBPD%2F82558%2F2011/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/OE/SFRH%2FBD%2F51576%2F2011/PT-
dc.rightsopenAccesspor
dc.subjectImage analysispor
dc.subjectEnhanced biological phosphorus removal (EBPR)por
dc.subjectPolyhydroxyalcanoate granules (PHA)por
dc.subjectSudan black B (SBB)por
dc.titleImage analysis for automatic characterization of polyhydroxyalcanoates granulespor
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.publicationstatuspublishedpor
oaire.citationStartPage790por
oaire.citationEndPage797por
oaire.citationIssue7950por
oaire.citationTitleLecture Notes in Computer Sciencepor
oaire.citationVolume7950por
dc.publisher.uriSpringer Verlagpor
dc.identifier.eissn0302-9743por
dc.identifier.doi10.1007/978-3-642-39094-4_91-
dc.identifier.eisbn978-3-642-39094-4-
dc.subject.wosScience & Technologypor
sdum.journalLecture Notes in Computer Sciencepor
sdum.conferencePublicationIMAGE ANALYSIS AND RECOGNITIONpor
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