Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure

Detalhes bibliográficos
Autor(a) principal: Melo, Antonio
Data de Publicação: 2024
Outros Autores: Costa, Joana Sofia Gomes, Quintelas, Cristina Maria Catalão, Amaral, António Luís, Ferreira, Eugénio C., Mesquita, Daniela P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/91576
Resumo: Extracellular polymeric substances (EPS) play a vital role in biological wastewater treatment systems. This study investigates the impact of herbicide atrazine (ATZ) on the overall performance, EPS yield, composition, and sludge morphology in an activated sludge (AS) system operated in a sequencing batch reactor (SBR). Since conventional methods for analyzing EPS are time-consuming and releases residues, a new approach was developed in this work to evaluate the EPS fractions and components, based on the morphological characterization of the biomass using quantitative image analysis (QIA) technique coupled with multivariate statistics. Results showed that exposure to ATZ inhibit biomass activity in terms of organic matter (COD) and nitrogen removal. Moreover, both tightly bound EPS (TB-EPS) and loosely bound EPS (LB-EPS) increased under ATZ, indicating that microorganisms release EPS as a defense mechanism against environmental changes. The PN/PS ratio also increases, indicating likely increased hydrophobicity in ATZ phases. Furthermore, ATZ phases exhibit a predominance of large aggregates compared to intermediate and small ones, indicating a change in aggregate morphological structure associated with EPS production. The new approach using QIA coupled with partial least squares (PLS) modeling provides accurate predictions of EPS content. The increase in TB-EPS is closely related to the rise of large aggregates in phases exposed to higher ATZ concentrations. The PLS models demonstrate high accuracy for EPS prediction (coefficients of determination, R2 above 0.86), showcasing the feasibility of using QIA for EPS assessment in AS systems. This approach offers significant potential for regular process monitoring and management, providing a more environmentally friendly methodology by eliminating the need for chemical usage.
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spelling Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposureAtrazineSequencing batch reactorAggregatesImage analysisPartial least squaresExtracellular polymeric substances (EPS) play a vital role in biological wastewater treatment systems. This study investigates the impact of herbicide atrazine (ATZ) on the overall performance, EPS yield, composition, and sludge morphology in an activated sludge (AS) system operated in a sequencing batch reactor (SBR). Since conventional methods for analyzing EPS are time-consuming and releases residues, a new approach was developed in this work to evaluate the EPS fractions and components, based on the morphological characterization of the biomass using quantitative image analysis (QIA) technique coupled with multivariate statistics. Results showed that exposure to ATZ inhibit biomass activity in terms of organic matter (COD) and nitrogen removal. Moreover, both tightly bound EPS (TB-EPS) and loosely bound EPS (LB-EPS) increased under ATZ, indicating that microorganisms release EPS as a defense mechanism against environmental changes. The PN/PS ratio also increases, indicating likely increased hydrophobicity in ATZ phases. Furthermore, ATZ phases exhibit a predominance of large aggregates compared to intermediate and small ones, indicating a change in aggregate morphological structure associated with EPS production. The new approach using QIA coupled with partial least squares (PLS) modeling provides accurate predictions of EPS content. The increase in TB-EPS is closely related to the rise of large aggregates in phases exposed to higher ATZ concentrations. The PLS models demonstrate high accuracy for EPS prediction (coefficients of determination, R2 above 0.86), showcasing the feasibility of using QIA for EPS assessment in AS systems. This approach offers significant potential for regular process monitoring and management, providing a more environmentally friendly methodology by eliminating the need for chemical usage.info:eu-repo/semantics/publishedVersionElsevier 1Universidade do MinhoMelo, AntonioCosta, Joana Sofia GomesQuintelas, Cristina Maria CatalãoAmaral, António LuísFerreira, Eugénio C.Mesquita, Daniela P.2024-12-032024-12-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/91576engMelo, A. R. B.; Costa, Joana Sofia Gomes; Quintelas, Cristina; Amaral, A. Luís; Ferreira, Eugénio C.; Mesquita, Daniela P., Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure. Separation and Purification Technology, 349(127831), 20241383-586610.1016/j.seppur.2024.127831https://www.journals.elsevier.com/separation-and-purification-technologyinfo: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:RCAAP2024-06-08T01:19:55Zoai:repositorium.sdum.uminho.pt:1822/91576Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-06-08T01:19:55Repositório 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 assessing extracellular polymeric substances in activated sludge under atrazine exposure
title Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
spellingShingle Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
Melo, Antonio
Atrazine
Sequencing batch reactor
Aggregates
Image analysis
Partial least squares
title_short Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
title_full Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
title_fullStr Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
title_full_unstemmed Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
title_sort Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
author Melo, Antonio
author_facet Melo, Antonio
Costa, Joana Sofia Gomes
Quintelas, Cristina Maria Catalão
Amaral, António Luís
Ferreira, Eugénio C.
Mesquita, Daniela P.
author_role author
author2 Costa, Joana Sofia Gomes
Quintelas, Cristina Maria Catalão
Amaral, António Luís
Ferreira, Eugénio C.
Mesquita, Daniela P.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Melo, Antonio
Costa, Joana Sofia Gomes
Quintelas, Cristina Maria Catalão
Amaral, António Luís
Ferreira, Eugénio C.
Mesquita, Daniela P.
dc.subject.por.fl_str_mv Atrazine
Sequencing batch reactor
Aggregates
Image analysis
Partial least squares
topic Atrazine
Sequencing batch reactor
Aggregates
Image analysis
Partial least squares
description Extracellular polymeric substances (EPS) play a vital role in biological wastewater treatment systems. This study investigates the impact of herbicide atrazine (ATZ) on the overall performance, EPS yield, composition, and sludge morphology in an activated sludge (AS) system operated in a sequencing batch reactor (SBR). Since conventional methods for analyzing EPS are time-consuming and releases residues, a new approach was developed in this work to evaluate the EPS fractions and components, based on the morphological characterization of the biomass using quantitative image analysis (QIA) technique coupled with multivariate statistics. Results showed that exposure to ATZ inhibit biomass activity in terms of organic matter (COD) and nitrogen removal. Moreover, both tightly bound EPS (TB-EPS) and loosely bound EPS (LB-EPS) increased under ATZ, indicating that microorganisms release EPS as a defense mechanism against environmental changes. The PN/PS ratio also increases, indicating likely increased hydrophobicity in ATZ phases. Furthermore, ATZ phases exhibit a predominance of large aggregates compared to intermediate and small ones, indicating a change in aggregate morphological structure associated with EPS production. The new approach using QIA coupled with partial least squares (PLS) modeling provides accurate predictions of EPS content. The increase in TB-EPS is closely related to the rise of large aggregates in phases exposed to higher ATZ concentrations. The PLS models demonstrate high accuracy for EPS prediction (coefficients of determination, R2 above 0.86), showcasing the feasibility of using QIA for EPS assessment in AS systems. This approach offers significant potential for regular process monitoring and management, providing a more environmentally friendly methodology by eliminating the need for chemical usage.
publishDate 2024
dc.date.none.fl_str_mv 2024-12-03
2024-12-03T00:00:00Z
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/1822/91576
url https://hdl.handle.net/1822/91576
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Melo, A. R. B.; Costa, Joana Sofia Gomes; Quintelas, Cristina; Amaral, A. Luís; Ferreira, Eugénio C.; Mesquita, Daniela P., Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure. Separation and Purification Technology, 349(127831), 2024
1383-5866
10.1016/j.seppur.2024.127831
https://www.journals.elsevier.com/separation-and-purification-technology
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 Elsevier 1
publisher.none.fl_str_mv Elsevier 1
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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