A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater

Detalhes bibliográficos
Autor(a) principal: Dunoyer,Arnulfo Antonio Tarón
Data de Publicação: 2021
Outros Autores: Cuello,Rafael Emilio González, Castillo,Fredy Colpas
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Ambiente & Água
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309
Resumo: Abstract This study focuses on the development of a secondary model for Yarrowia lipolytica in a sewage treatment process. The raw data of Y. lipolytica growth were adjusted to the Buchanan model in order to obtain growth parameters such as initial count cells (Y0), maximum specific growth rate (μmax), latency phase (λ) and maximum cell population (Ymax). The µ values obtained at different pH levels (5.0 to 8.0) were used to build the secondary model based on a linear equation. The results showed a significant effect of pH on µmax values. The validation process of the developed models displays accuracy (Af) and bias factor (Bf) values close to one, while the values of root mean square error (RMSE) were low, confirming that such models can predict the growth of Y. lipolytica in dairy wastewater. This can be interesting to optimize sewage treatments that involve this kind of microorganism. Moreover, the dairy wastewater was a good substrate to support the Yarrowia lipolytica's growth and could be used to produce enzymes.
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spelling A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewaterbiological treatmentpredictive microbiologyremovalwastewaterYarrowia lipolyticaAbstract This study focuses on the development of a secondary model for Yarrowia lipolytica in a sewage treatment process. The raw data of Y. lipolytica growth were adjusted to the Buchanan model in order to obtain growth parameters such as initial count cells (Y0), maximum specific growth rate (μmax), latency phase (λ) and maximum cell population (Ymax). The µ values obtained at different pH levels (5.0 to 8.0) were used to build the secondary model based on a linear equation. The results showed a significant effect of pH on µmax values. The validation process of the developed models displays accuracy (Af) and bias factor (Bf) values close to one, while the values of root mean square error (RMSE) were low, confirming that such models can predict the growth of Y. lipolytica in dairy wastewater. This can be interesting to optimize sewage treatments that involve this kind of microorganism. Moreover, the dairy wastewater was a good substrate to support the Yarrowia lipolytica's growth and could be used to produce enzymes.Instituto de Pesquisas Ambientais em Bacias Hidrográficas2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309Revista Ambiente & Água v.16 n.1 2021reponame:Revista Ambiente & Águainstname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)instacron:IPABHI10.4136/ambi-agua.2629info:eu-repo/semantics/openAccessDunoyer,Arnulfo Antonio TarónCuello,Rafael Emilio GonzálezCastillo,Fredy Colpaseng2021-02-10T00:00:00Zoai:scielo:S1980-993X2021000100309Revistahttp://www.ambi-agua.net/PUBhttps://old.scielo.br/oai/scielo-oai.php||ambi.agua@gmail.com1980-993X1980-993Xopendoar:2021-02-10T00:00Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)false
dc.title.none.fl_str_mv A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
title A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
spellingShingle A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
Dunoyer,Arnulfo Antonio Tarón
biological treatment
predictive microbiology
removal
wastewater
Yarrowia lipolytica
title_short A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
title_full A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
title_fullStr A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
title_full_unstemmed A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
title_sort A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
author Dunoyer,Arnulfo Antonio Tarón
author_facet Dunoyer,Arnulfo Antonio Tarón
Cuello,Rafael Emilio González
Castillo,Fredy Colpas
author_role author
author2 Cuello,Rafael Emilio González
Castillo,Fredy Colpas
author2_role author
author
dc.contributor.author.fl_str_mv Dunoyer,Arnulfo Antonio Tarón
Cuello,Rafael Emilio González
Castillo,Fredy Colpas
dc.subject.por.fl_str_mv biological treatment
predictive microbiology
removal
wastewater
Yarrowia lipolytica
topic biological treatment
predictive microbiology
removal
wastewater
Yarrowia lipolytica
description Abstract This study focuses on the development of a secondary model for Yarrowia lipolytica in a sewage treatment process. The raw data of Y. lipolytica growth were adjusted to the Buchanan model in order to obtain growth parameters such as initial count cells (Y0), maximum specific growth rate (μmax), latency phase (λ) and maximum cell population (Ymax). The µ values obtained at different pH levels (5.0 to 8.0) were used to build the secondary model based on a linear equation. The results showed a significant effect of pH on µmax values. The validation process of the developed models displays accuracy (Af) and bias factor (Bf) values close to one, while the values of root mean square error (RMSE) were low, confirming that such models can predict the growth of Y. lipolytica in dairy wastewater. This can be interesting to optimize sewage treatments that involve this kind of microorganism. Moreover, the dairy wastewater was a good substrate to support the Yarrowia lipolytica's growth and could be used to produce enzymes.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.4136/ambi-agua.2629
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto de Pesquisas Ambientais em Bacias Hidrográficas
publisher.none.fl_str_mv Instituto de Pesquisas Ambientais em Bacias Hidrográficas
dc.source.none.fl_str_mv Revista Ambiente & Água v.16 n.1 2021
reponame:Revista Ambiente & Água
instname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron:IPABHI
instname_str Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron_str IPABHI
institution IPABHI
reponame_str Revista Ambiente & Água
collection Revista Ambiente & Água
repository.name.fl_str_mv Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
repository.mail.fl_str_mv ||ambi.agua@gmail.com
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