Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Chemical Engineering |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322013000300005 |
Resumo: | In this work, two-step enzymatic hydrolysis of sweet potato peel was optimized. The effects of time, enzyme dose and temperature on glucose concentration were investigated. The Box-Behnken design was applied and a total of 17 experimental runs were generated for each step. For the liquefaction step, an ANOVA test showed the quadratic model obtained to be significant (p < 0.05). The statistical model predicted the maximum glucose concentration to be 126.66 g/L at a temperature of 56.4 ºC, α-amylase dose 1% (v/v) and time 60 min. A quadratic model was also obtained for the saccharification step and the model was also significant (p < 0.05). The statistical model for the second step predicted the maximum glucose concentration to be 178.39 g/L, established at the temperature of 45 ºC, glucoamylase dose 1% (v/v) and time 60 min. The optimized liquefaction and saccharification conditions were validated with the actual glucose concentrations of 126.03 and 176.89 g/L, respectively. |
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Brazilian Journal of Chemical Engineering |
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Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approachHydrolysisEnzymesOptimizationResponse surface methodologySweet potato peelIn this work, two-step enzymatic hydrolysis of sweet potato peel was optimized. The effects of time, enzyme dose and temperature on glucose concentration were investigated. The Box-Behnken design was applied and a total of 17 experimental runs were generated for each step. For the liquefaction step, an ANOVA test showed the quadratic model obtained to be significant (p < 0.05). The statistical model predicted the maximum glucose concentration to be 126.66 g/L at a temperature of 56.4 ºC, α-amylase dose 1% (v/v) and time 60 min. A quadratic model was also obtained for the saccharification step and the model was also significant (p < 0.05). The statistical model for the second step predicted the maximum glucose concentration to be 178.39 g/L, established at the temperature of 45 ºC, glucoamylase dose 1% (v/v) and time 60 min. The optimized liquefaction and saccharification conditions were validated with the actual glucose concentrations of 126.03 and 176.89 g/L, respectively.Brazilian Society of Chemical Engineering2013-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322013000300005Brazilian Journal of Chemical Engineering v.30 n.3 2013reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/S0104-66322013000300005info:eu-repo/semantics/openAccessBetiku,E.Akindolani,O. O.Ismaila,A. R.eng2013-09-03T00:00:00Zoai:scielo:S0104-66322013000300005Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2013-09-03T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false |
dc.title.none.fl_str_mv |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
title |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
spellingShingle |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach Betiku,E. Hydrolysis Enzymes Optimization Response surface methodology Sweet potato peel |
title_short |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
title_full |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
title_fullStr |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
title_full_unstemmed |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
title_sort |
Enzymatic hydrolysis optimization of sweet potato (Ipomoea batatas) peel using a statistical approach |
author |
Betiku,E. |
author_facet |
Betiku,E. Akindolani,O. O. Ismaila,A. R. |
author_role |
author |
author2 |
Akindolani,O. O. Ismaila,A. R. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Betiku,E. Akindolani,O. O. Ismaila,A. R. |
dc.subject.por.fl_str_mv |
Hydrolysis Enzymes Optimization Response surface methodology Sweet potato peel |
topic |
Hydrolysis Enzymes Optimization Response surface methodology Sweet potato peel |
description |
In this work, two-step enzymatic hydrolysis of sweet potato peel was optimized. The effects of time, enzyme dose and temperature on glucose concentration were investigated. The Box-Behnken design was applied and a total of 17 experimental runs were generated for each step. For the liquefaction step, an ANOVA test showed the quadratic model obtained to be significant (p < 0.05). The statistical model predicted the maximum glucose concentration to be 126.66 g/L at a temperature of 56.4 ºC, α-amylase dose 1% (v/v) and time 60 min. A quadratic model was also obtained for the saccharification step and the model was also significant (p < 0.05). The statistical model for the second step predicted the maximum glucose concentration to be 178.39 g/L, established at the temperature of 45 ºC, glucoamylase dose 1% (v/v) and time 60 min. The optimized liquefaction and saccharification conditions were validated with the actual glucose concentrations of 126.03 and 176.89 g/L, respectively. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-09-01 |
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=S0104-66322013000300005 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322013000300005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0104-66322013000300005 |
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 |
Brazilian Society of Chemical Engineering |
publisher.none.fl_str_mv |
Brazilian Society of Chemical Engineering |
dc.source.none.fl_str_mv |
Brazilian Journal of Chemical Engineering v.30 n.3 2013 reponame:Brazilian Journal of Chemical Engineering instname:Associação Brasileira de Engenharia Química (ABEQ) instacron:ABEQ |
instname_str |
Associação Brasileira de Engenharia Química (ABEQ) |
instacron_str |
ABEQ |
institution |
ABEQ |
reponame_str |
Brazilian Journal of Chemical Engineering |
collection |
Brazilian Journal of Chemical Engineering |
repository.name.fl_str_mv |
Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ) |
repository.mail.fl_str_mv |
rgiudici@usp.br||rgiudici@usp.br |
_version_ |
1754213173934686208 |