Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2007 |
| Outros Autores: | , |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | https://hdl.handle.net/1822/7301 |
Resumo: | Morphological parameters, obtained by quantitative image analysis techniques, together with physiological and reactor performance data were inserted in principal components analysis (PCA) to detect operational problems and control of high rate anaerobic reactors during organic overloads. Four lab-scale Expanded Granular Sludge Blanket reactors were used to performed organic overloads of 18 kg.mˉ³.day ˉ¹(R1 – HRT of 8h; and, R2 – HRT of 2.5h) and 50 kg.mˉ³.dayˉ¹ (R3 - fed for 3 days; and, R4 - fed for 16 days). The application of PCA allowed the visualization of the main effects caused by the organic overloads. The first Principal Component (PC) extracted, in each shock load, retains enough information to group observations in agreement with operational conditions (normal or overload). The variables from quantitative image analysis presented high loadings, suggesting that might play an important role in organic overloads control. |
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Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludgeAnaerobic granular sludgeMethanogenic activityPrincipal component analysisQuantitative image analysisOrganic overloadMorphological parameters, obtained by quantitative image analysis techniques, together with physiological and reactor performance data were inserted in principal components analysis (PCA) to detect operational problems and control of high rate anaerobic reactors during organic overloads. Four lab-scale Expanded Granular Sludge Blanket reactors were used to performed organic overloads of 18 kg.mˉ³.day ˉ¹(R1 – HRT of 8h; and, R2 – HRT of 2.5h) and 50 kg.mˉ³.dayˉ¹ (R3 - fed for 3 days; and, R4 - fed for 16 days). The application of PCA allowed the visualization of the main effects caused by the organic overloads. The first Principal Component (PC) extracted, in each shock load, retains enough information to group observations in agreement with operational conditions (normal or overload). The variables from quantitative image analysis presented high loadings, suggesting that might play an important role in organic overloads control.Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/13317/2003, POCI/AMB/60141/2004.Universidade do MinhoCosta, J. C.Alves, M. M.Ferreira, Eugénio C.20072007-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/7301engIWA WORLD CONGRESS ON ANAEROBIC DIGESTION, 11, Brisbane, Australia, 2007 – “11th IWA World Congress on Anaerobic Digestion : proceedings”. [S.l. : s.n., 2007].info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T05:10:14Zoai:repositorium.sdum.uminho.pt:1822/7301Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:10:11.807815Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| title |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| spellingShingle |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge Costa, J. C. Anaerobic granular sludge Methanogenic activity Principal component analysis Quantitative image analysis Organic overload |
| title_short |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| title_full |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| title_fullStr |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| title_full_unstemmed |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| title_sort |
Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge |
| author |
Costa, J. C. |
| author_facet |
Costa, J. C. Alves, M. M. Ferreira, Eugénio C. |
| author_role |
author |
| author2 |
Alves, M. M. Ferreira, Eugénio C. |
| author2_role |
author author |
| dc.contributor.none.fl_str_mv |
Universidade do Minho |
| dc.contributor.author.fl_str_mv |
Costa, J. C. Alves, M. M. Ferreira, Eugénio C. |
| dc.subject.por.fl_str_mv |
Anaerobic granular sludge Methanogenic activity Principal component analysis Quantitative image analysis Organic overload |
| topic |
Anaerobic granular sludge Methanogenic activity Principal component analysis Quantitative image analysis Organic overload |
| description |
Morphological parameters, obtained by quantitative image analysis techniques, together with physiological and reactor performance data were inserted in principal components analysis (PCA) to detect operational problems and control of high rate anaerobic reactors during organic overloads. Four lab-scale Expanded Granular Sludge Blanket reactors were used to performed organic overloads of 18 kg.mˉ³.day ˉ¹(R1 – HRT of 8h; and, R2 – HRT of 2.5h) and 50 kg.mˉ³.dayˉ¹ (R3 - fed for 3 days; and, R4 - fed for 16 days). The application of PCA allowed the visualization of the main effects caused by the organic overloads. The first Principal Component (PC) extracted, in each shock load, retains enough information to group observations in agreement with operational conditions (normal or overload). The variables from quantitative image analysis presented high loadings, suggesting that might play an important role in organic overloads control. |
| publishDate |
2007 |
| dc.date.none.fl_str_mv |
2007 2007-01-01T00:00:00Z |
| dc.type.driver.fl_str_mv |
conference paper |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/7301 |
| url |
https://hdl.handle.net/1822/7301 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
IWA WORLD CONGRESS ON ANAEROBIC DIGESTION, 11, Brisbane, Australia, 2007 – “11th IWA World Congress on Anaerobic Digestion : proceedings”. [S.l. : s.n., 2007]. |
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info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
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application/pdf |
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