Neural modeling of bromelain extraction by reversed micelles
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Archives of Biology and Technology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132010000200026 |
Resumo: | A pulsed-cap microcolumn was used for bromelain extraction from pineapple juice by reversed micelles. The cationic micellar solution used BDBAC as the surfactant, isooctane as the solvent and hexanol as the co-solvent. In order to capture the dynamic behavior and the nonlinearities of the column, the operating conditions were modified in accordance with the central composite design for the experiment, using the ratio between the light phase flow rate and the total flow rate, and the time interval between pulses. The effects on the purification factor and on total protein yield were modeled via neural networks. The best topology was defined as 16-9-2, and the input layer was a moving window of the independent variables. The neural model successfully predicted both the purification factor and the total protein yield from historical data. At the optimal operating point, a purification factor of 4.96 and a productivity of 1.29 mL/min were obtained. |
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Brazilian Archives of Biology and Technology |
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Neural modeling of bromelain extraction by reversed micellesbromelainreversed micellesextractionneural networkspineappleA pulsed-cap microcolumn was used for bromelain extraction from pineapple juice by reversed micelles. The cationic micellar solution used BDBAC as the surfactant, isooctane as the solvent and hexanol as the co-solvent. In order to capture the dynamic behavior and the nonlinearities of the column, the operating conditions were modified in accordance with the central composite design for the experiment, using the ratio between the light phase flow rate and the total flow rate, and the time interval between pulses. The effects on the purification factor and on total protein yield were modeled via neural networks. The best topology was defined as 16-9-2, and the input layer was a moving window of the independent variables. The neural model successfully predicted both the purification factor and the total protein yield from historical data. At the optimal operating point, a purification factor of 4.96 and a productivity of 1.29 mL/min were obtained.Instituto de Tecnologia do Paraná - Tecpar2010-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132010000200026Brazilian Archives of Biology and Technology v.53 n.2 2010reponame:Brazilian Archives of Biology and Technologyinstname:Instituto de Tecnologia do Paraná (Tecpar)instacron:TECPAR10.1590/S1516-89132010000200026info:eu-repo/semantics/openAccessFileti,Ana Maria FrattiniFischer,Gilvan AndersonTambourgi,Elias Basileeng2010-04-06T00:00:00Zoai:scielo:S1516-89132010000200026Revistahttps://www.scielo.br/j/babt/https://old.scielo.br/oai/scielo-oai.phpbabt@tecpar.br||babt@tecpar.br1678-43241516-8913opendoar:2010-04-06T00:00Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar)false |
dc.title.none.fl_str_mv |
Neural modeling of bromelain extraction by reversed micelles |
title |
Neural modeling of bromelain extraction by reversed micelles |
spellingShingle |
Neural modeling of bromelain extraction by reversed micelles Fileti,Ana Maria Frattini bromelain reversed micelles extraction neural networks pineapple |
title_short |
Neural modeling of bromelain extraction by reversed micelles |
title_full |
Neural modeling of bromelain extraction by reversed micelles |
title_fullStr |
Neural modeling of bromelain extraction by reversed micelles |
title_full_unstemmed |
Neural modeling of bromelain extraction by reversed micelles |
title_sort |
Neural modeling of bromelain extraction by reversed micelles |
author |
Fileti,Ana Maria Frattini |
author_facet |
Fileti,Ana Maria Frattini Fischer,Gilvan Anderson Tambourgi,Elias Basile |
author_role |
author |
author2 |
Fischer,Gilvan Anderson Tambourgi,Elias Basile |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Fileti,Ana Maria Frattini Fischer,Gilvan Anderson Tambourgi,Elias Basile |
dc.subject.por.fl_str_mv |
bromelain reversed micelles extraction neural networks pineapple |
topic |
bromelain reversed micelles extraction neural networks pineapple |
description |
A pulsed-cap microcolumn was used for bromelain extraction from pineapple juice by reversed micelles. The cationic micellar solution used BDBAC as the surfactant, isooctane as the solvent and hexanol as the co-solvent. In order to capture the dynamic behavior and the nonlinearities of the column, the operating conditions were modified in accordance with the central composite design for the experiment, using the ratio between the light phase flow rate and the total flow rate, and the time interval between pulses. The effects on the purification factor and on total protein yield were modeled via neural networks. The best topology was defined as 16-9-2, and the input layer was a moving window of the independent variables. The neural model successfully predicted both the purification factor and the total protein yield from historical data. At the optimal operating point, a purification factor of 4.96 and a productivity of 1.29 mL/min were obtained. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-04-01 |
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=S1516-89132010000200026 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132010000200026 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1516-89132010000200026 |
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 Tecnologia do Paraná - Tecpar |
publisher.none.fl_str_mv |
Instituto de Tecnologia do Paraná - Tecpar |
dc.source.none.fl_str_mv |
Brazilian Archives of Biology and Technology v.53 n.2 2010 reponame:Brazilian Archives of Biology and Technology instname:Instituto de Tecnologia do Paraná (Tecpar) instacron:TECPAR |
instname_str |
Instituto de Tecnologia do Paraná (Tecpar) |
instacron_str |
TECPAR |
institution |
TECPAR |
reponame_str |
Brazilian Archives of Biology and Technology |
collection |
Brazilian Archives of Biology and Technology |
repository.name.fl_str_mv |
Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar) |
repository.mail.fl_str_mv |
babt@tecpar.br||babt@tecpar.br |
_version_ |
1750318273934655488 |