Stalked protozoa identification by image analysis and multivariable statistical techniques
Main Author: | |
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Publication Date: | 2008 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/1822/7946 |
Summary: | Protozoa are considered good indicators of the treatment quality in activated sludge systems as they are sensitive to physical, chemical and operational processes. Therefore, it is possible to correlate the predominance of certain species or groups and several operational parameters of the plant. This work presents a semiautomatic image analysis procedure for the recognition of the stalked protozoa species most frequently found in wastewater treatment plants by determining the geometrical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques. Geometrical descriptors were found to be responsible for the best identification ability and the identification of the crucial Opercularia and Vorticella microstoma microorganisms provided some degree of confidence to establish their presence in wastewater treatment plants. |
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Stalked protozoa identification by image analysis and multivariable statistical techniquesProtozoaMetazoaActivated sludgeImage analysisMultivariable statistical techniquesScience & TechnologyProtozoa are considered good indicators of the treatment quality in activated sludge systems as they are sensitive to physical, chemical and operational processes. Therefore, it is possible to correlate the predominance of certain species or groups and several operational parameters of the plant. This work presents a semiautomatic image analysis procedure for the recognition of the stalked protozoa species most frequently found in wastewater treatment plants by determining the geometrical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques. Geometrical descriptors were found to be responsible for the best identification ability and the identification of the crucial Opercularia and Vorticella microstoma microorganisms provided some degree of confidence to establish their presence in wastewater treatment plants.Springer VerlagUniversidade do MinhoAmaral, A. L.Ginoris, Y. P.Nicolau, AnaCoelho, M. A. Z.Ferreira, Eugénio C.2008-062008-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/7946eng"Analytical and Bioanalytical Chemistry". ISSN 1618-2642. 391:4 (June 2008) 1321-1325.1618-264210.1007/s00216-008-1845-y18327573info: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:RCAAP2024-05-11T05:22:12Zoai:repositorium.sdum.uminho.pt:1822/7946Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:16:09.303514Repositórios 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 |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
title |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
spellingShingle |
Stalked protozoa identification by image analysis and multivariable statistical techniques Amaral, A. L. Protozoa Metazoa Activated sludge Image analysis Multivariable statistical techniques Science & Technology |
title_short |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
title_full |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
title_fullStr |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
title_full_unstemmed |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
title_sort |
Stalked protozoa identification by image analysis and multivariable statistical techniques |
author |
Amaral, A. L. |
author_facet |
Amaral, A. L. Ginoris, Y. P. Nicolau, Ana Coelho, M. A. Z. Ferreira, Eugénio C. |
author_role |
author |
author2 |
Ginoris, Y. P. Nicolau, Ana Coelho, M. A. Z. Ferreira, Eugénio C. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Amaral, A. L. Ginoris, Y. P. Nicolau, Ana Coelho, M. A. Z. Ferreira, Eugénio C. |
dc.subject.por.fl_str_mv |
Protozoa Metazoa Activated sludge Image analysis Multivariable statistical techniques Science & Technology |
topic |
Protozoa Metazoa Activated sludge Image analysis Multivariable statistical techniques Science & Technology |
description |
Protozoa are considered good indicators of the treatment quality in activated sludge systems as they are sensitive to physical, chemical and operational processes. Therefore, it is possible to correlate the predominance of certain species or groups and several operational parameters of the plant. This work presents a semiautomatic image analysis procedure for the recognition of the stalked protozoa species most frequently found in wastewater treatment plants by determining the geometrical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques. Geometrical descriptors were found to be responsible for the best identification ability and the identification of the crucial Opercularia and Vorticella microstoma microorganisms provided some degree of confidence to establish their presence in wastewater treatment plants. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-06 2008-06-01T00:00:00Z |
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/1822/7946 |
url |
https://hdl.handle.net/1822/7946 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
"Analytical and Bioanalytical Chemistry". ISSN 1618-2642. 391:4 (June 2008) 1321-1325. 1618-2642 10.1007/s00216-008-1845-y 18327573 |
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 Verlag |
publisher.none.fl_str_mv |
Springer Verlag |
dc.source.none.fl_str_mv |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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