Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.bcab.2019.101182 http://hdl.handle.net/11449/189175 |
Resumo: | The objective of this study was to optimize the ethanol production from cheese whey, using the yeast Kluyveromyces marxianus URM 7404. The response surface methodology (RSM) with a central composite rotational design (CCRD) was used to evaluate the effects of pH (4–6), temperature (30–36 °C), and lactose concentration (50–70 g.L−1). Cheese whey underwent 17 fermentations and further three fermentations were conducted for the validation of the equation obtained by RSM. After the validation of the optimization, the fermentation process was scaled-up to the volumes of 1 L, 6 L, 21 L, and 36 L, and ethanol production (g.L−1), productivity (QP g.L−1. h−1), conversion (YP/S g.g−1), yield (η %), and chemical oxygen demand (mg COD. L−1) were evaluated. Temperature was the most significant factor used for the optimization of the ethanol production, followed by pH and lactose concentration. The conditions for the ethanol production of higher than 90% were as follows: temperature range from 32.5 to 35.0 °C, pH from 4.8 to 5.3, and lactose concentration from 61.0 to 65.0 g.L−1. The equation generated from the optimization process was validated and presented excellent values and precision for the use of this model in scale-up process, obtaining volume of 36 L, η 95.80%, QP 2.57 g.L−1. h−1, and YP/S 0.50 g.g−1. The COD of the cheese whey was reduced by 78.94%, proving it to be an effective process to reduce the environmental damages caused by this effluent. |
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Repositório Institucional da UNESP |
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Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404BiofuelCheese wheyKluyveromycesOptimizationScale–upYeastsThe objective of this study was to optimize the ethanol production from cheese whey, using the yeast Kluyveromyces marxianus URM 7404. The response surface methodology (RSM) with a central composite rotational design (CCRD) was used to evaluate the effects of pH (4–6), temperature (30–36 °C), and lactose concentration (50–70 g.L−1). Cheese whey underwent 17 fermentations and further three fermentations were conducted for the validation of the equation obtained by RSM. After the validation of the optimization, the fermentation process was scaled-up to the volumes of 1 L, 6 L, 21 L, and 36 L, and ethanol production (g.L−1), productivity (QP g.L−1. h−1), conversion (YP/S g.g−1), yield (η %), and chemical oxygen demand (mg COD. L−1) were evaluated. Temperature was the most significant factor used for the optimization of the ethanol production, followed by pH and lactose concentration. The conditions for the ethanol production of higher than 90% were as follows: temperature range from 32.5 to 35.0 °C, pH from 4.8 to 5.3, and lactose concentration from 61.0 to 65.0 g.L−1. The equation generated from the optimization process was validated and presented excellent values and precision for the use of this model in scale-up process, obtaining volume of 36 L, η 95.80%, QP 2.57 g.L−1. h−1, and YP/S 0.50 g.g−1. The COD of the cheese whey was reduced by 78.94%, proving it to be an effective process to reduce the environmental damages caused by this effluent.UNESP – São Paulo State University Department of Food Engineering and Technology Institute of Biosciences Humanities and Exact Sciences (Ibilce) Campus São José do Rio PretoUNESP – São Paulo State University Department of Food Engineering and Technology Institute of Biosciences Humanities and Exact Sciences (Ibilce) Campus São José do Rio PretoUniversidade Estadual Paulista (Unesp)Murari, Cleidiane Samara [UNESP]Machado, Whallans Raphael Couto [UNESP]Schuina, Guilherme Lorencini [UNESP]Del Bianchi, Vanildo Luiz [UNESP]2019-10-06T16:32:14Z2019-10-06T16:32:14Z2019-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.bcab.2019.101182Biocatalysis and Agricultural Biotechnology, v. 20.1878-8181http://hdl.handle.net/11449/18917510.1016/j.bcab.2019.1011822-s2.0-85066287436Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBiocatalysis and Agricultural Biotechnologyinfo:eu-repo/semantics/openAccess2021-10-22T21:09:47Zoai:repositorio.unesp.br:11449/189175Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:05:22.411695Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
title |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
spellingShingle |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 Murari, Cleidiane Samara [UNESP] Biofuel Cheese whey Kluyveromyces Optimization Scale–up Yeasts |
title_short |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
title_full |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
title_fullStr |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
title_full_unstemmed |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
title_sort |
Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404 |
author |
Murari, Cleidiane Samara [UNESP] |
author_facet |
Murari, Cleidiane Samara [UNESP] Machado, Whallans Raphael Couto [UNESP] Schuina, Guilherme Lorencini [UNESP] Del Bianchi, Vanildo Luiz [UNESP] |
author_role |
author |
author2 |
Machado, Whallans Raphael Couto [UNESP] Schuina, Guilherme Lorencini [UNESP] Del Bianchi, Vanildo Luiz [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Murari, Cleidiane Samara [UNESP] Machado, Whallans Raphael Couto [UNESP] Schuina, Guilherme Lorencini [UNESP] Del Bianchi, Vanildo Luiz [UNESP] |
dc.subject.por.fl_str_mv |
Biofuel Cheese whey Kluyveromyces Optimization Scale–up Yeasts |
topic |
Biofuel Cheese whey Kluyveromyces Optimization Scale–up Yeasts |
description |
The objective of this study was to optimize the ethanol production from cheese whey, using the yeast Kluyveromyces marxianus URM 7404. The response surface methodology (RSM) with a central composite rotational design (CCRD) was used to evaluate the effects of pH (4–6), temperature (30–36 °C), and lactose concentration (50–70 g.L−1). Cheese whey underwent 17 fermentations and further three fermentations were conducted for the validation of the equation obtained by RSM. After the validation of the optimization, the fermentation process was scaled-up to the volumes of 1 L, 6 L, 21 L, and 36 L, and ethanol production (g.L−1), productivity (QP g.L−1. h−1), conversion (YP/S g.g−1), yield (η %), and chemical oxygen demand (mg COD. L−1) were evaluated. Temperature was the most significant factor used for the optimization of the ethanol production, followed by pH and lactose concentration. The conditions for the ethanol production of higher than 90% were as follows: temperature range from 32.5 to 35.0 °C, pH from 4.8 to 5.3, and lactose concentration from 61.0 to 65.0 g.L−1. The equation generated from the optimization process was validated and presented excellent values and precision for the use of this model in scale-up process, obtaining volume of 36 L, η 95.80%, QP 2.57 g.L−1. h−1, and YP/S 0.50 g.g−1. The COD of the cheese whey was reduced by 78.94%, proving it to be an effective process to reduce the environmental damages caused by this effluent. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-06T16:32:14Z 2019-10-06T16:32:14Z 2019-07-01 |
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 |
http://dx.doi.org/10.1016/j.bcab.2019.101182 Biocatalysis and Agricultural Biotechnology, v. 20. 1878-8181 http://hdl.handle.net/11449/189175 10.1016/j.bcab.2019.101182 2-s2.0-85066287436 |
url |
http://dx.doi.org/10.1016/j.bcab.2019.101182 http://hdl.handle.net/11449/189175 |
identifier_str_mv |
Biocatalysis and Agricultural Biotechnology, v. 20. 1878-8181 10.1016/j.bcab.2019.101182 2-s2.0-85066287436 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Biocatalysis and Agricultural Biotechnology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128606911594496 |