Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review

Detalhes bibliográficos
Autor(a) principal: Costa, J. C.
Data de Publicação: 2013
Outros Autores: Mesquita, D. P., Amaral, A. L., Alves, M. M., Ferreira, Eugénio C.
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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spelling 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
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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
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0944-1344
10.1007/s11356-013-1824-5
23716077
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dc.publisher.none.fl_str_mv Springer
Kluwer Academic Publishers
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Kluwer Academic Publishers
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