Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge

Bibliographic Details
Main Author: Costa, J. C.
Publication Date: 2007
Other Authors: Alves, M. M., Ferreira, Eugénio C.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/1822/7301
Summary: 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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spelling 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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