A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater
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), laten...
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Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi)
2021-02-01
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doaj-6ee56541edec4e60937197620227a5432021-02-23T18:20:44ZengInstituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi)Revista Ambiente & Água1980-993X2021-02-011611910.4136/ambi-agua.2629A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater Arnulfo Antonio Tarón Dunoyer0https://orcid.org/0000-0001-7540-0920Rafael Emilio González Cuello1https://orcid.org/0000-0002-2674-2876Fredy Colpas Castillo2https://orcid.org/0000-0001-7203-6983Faculty of Engineering, Food Engineering Program. University of Cartagena, Street 30, n° 48-152, 130014, Zaragocilla, Cartagena, Colombia. Faculty of Engineering, Food Engineering Program. University of Cartagena, Street 30, n° 48-152, 130014, Zaragocilla, Cartagena, Colombia. Exact and Natural Sciences Faculty. Chemistry program. University of Cartagena, Street 50, n° 24120, 130014, Zaragocilla, Cartagena, Colombia. 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. https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309&lng=en&nrm=iso&tlng=enbiological treatmentpredictive microbiologyremovalwastewateryarrowia lipolytica |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arnulfo Antonio Tarón Dunoyer Rafael Emilio González Cuello Fredy Colpas Castillo |
spellingShingle |
Arnulfo Antonio Tarón Dunoyer Rafael Emilio González Cuello Fredy Colpas Castillo A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater Revista Ambiente & Água biological treatment predictive microbiology removal wastewater yarrowia lipolytica |
author_facet |
Arnulfo Antonio Tarón Dunoyer Rafael Emilio González Cuello Fredy Colpas Castillo |
author_sort |
Arnulfo Antonio Tarón Dunoyer |
title |
A predictive growth model for Yarrowia lipolytica ATCC 9773 in wastewater |
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 |
predictive growth model for yarrowia lipolytica atcc 9773 in wastewater |
publisher |
Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi) |
series |
Revista Ambiente & Água |
issn |
1980-993X |
publishDate |
2021-02-01 |
description |
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. |
topic |
biological treatment predictive microbiology removal wastewater yarrowia lipolytica |
url |
https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100309&lng=en&nrm=iso&tlng=en |
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