Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/25500 |
Resumo: | Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes. |
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Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a reviewActivated sludgeAnaerobic digestionChemometricsFilamentous bulkingGranulationSludge volume indexScience & TechnologyQuantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal).SpringerKluwer Academic PublishersUniversidade do MinhoCosta, J. C.Mesquita, D. P.Amaral, A. L.Alves, M. M.Ferreira, Eugénio C.20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/25500eng0944-13440944-134410.1007/s11356-013-1824-523716077info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-16T01:19:34Zoai:repositorium.sdum.uminho.pt:1822/25500Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:45:47.183433Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
title |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
spellingShingle |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review Costa, J. C. Activated sludge Anaerobic digestion Chemometrics Filamentous bulking Granulation Sludge volume index Science & Technology |
title_short |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
title_full |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
title_fullStr |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
title_full_unstemmed |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
title_sort |
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review |
author |
Costa, J. C. |
author_facet |
Costa, J. C. Mesquita, D. P. Amaral, A. L. Alves, M. M. Ferreira, Eugénio C. |
author_role |
author |
author2 |
Mesquita, D. P. Amaral, A. L. Alves, M. M. Ferreira, Eugénio C. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Costa, J. C. Mesquita, D. P. Amaral, A. L. Alves, M. M. Ferreira, Eugénio C. |
dc.subject.por.fl_str_mv |
Activated sludge Anaerobic digestion Chemometrics Filamentous bulking Granulation Sludge volume index Science & Technology |
topic |
Activated sludge Anaerobic digestion Chemometrics Filamentous bulking Granulation Sludge volume index Science & Technology |
description |
Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2013-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/25500 |
url |
https://hdl.handle.net/1822/25500 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0944-1344 0944-1344 10.1007/s11356-013-1824-5 23716077 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer Kluwer Academic Publishers |
publisher.none.fl_str_mv |
Springer Kluwer Academic Publishers |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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