Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling

For a successful refining of lignocellulosic biomass in production of bioethanol, it needs a delignification step to increase production of sugar. In this study, we use Laccase enzyme (as environment-friendly pretreatment) to pretreat sawdust and evaluate the degree of delignification after pretreat...

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Main Authors: Hashabra, Amani M., Makky, Essam A., Rashid, Shah Samiur
Format: Conference or Workshop Item
Language:English
Published: Universiti Malaysia Pahang 2017
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Online Access:http://umpir.ump.edu.my/id/eprint/17622/1/19.%20Laccase%20as%20bio-pretreatment%20step%20of%20sawdust%20for%20ethanol%20production%20-%20%20optimization%20and%20statistical%20modeling.pdf
http://umpir.ump.edu.my/id/eprint/17622/
http://fgic.ump.edu.my/images/docman/1st-FGIC-Proceedings.pdf
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spelling my.ump.umpir.176222018-01-24T07:38:11Z http://umpir.ump.edu.my/id/eprint/17622/ Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling Hashabra, Amani M. Makky, Essam A. Rashid, Shah Samiur TD Environmental technology. Sanitary engineering For a successful refining of lignocellulosic biomass in production of bioethanol, it needs a delignification step to increase production of sugar. In this study, we use Laccase enzyme (as environment-friendly pretreatment) to pretreat sawdust and evaluate the degree of delignification after pretreatment in terms of weight loss percentage (%) and Total sugar produced (mg/dL). The parameters used in the optimization process was temperature (oC), pH, time of pretreatment (hrs), enzyme concentration (IU/g), substrate concentration (%), substrate size (mm) and speed of agitation (RPM). In order to achieve best condition of pretreatment, first, we use the one-factor-at-a-time (OFAT) analysis to see the significance of parameters then the Face-Centered Central Composite Design (FCCCD) of Response Surface Methodology (RSM) is used to study the combined effect of temperature and pH parameters. Our experimental results show that optimized conditions for sawdust pretreatment are: temperature, 35oC; pH 5; time, 10 hrs; enzyme concentration, 20 IU/g of sawdust; substrate concentration, 5% (w/v); sample size, 1 mm and Agitation, 150 rpm. The experiments also show a high pretreatment result considering energy sustainability which can be achieved by using sample Size of 2 mm, temperature of 25 °C and 4 hrs. Universiti Malaysia Pahang 2017 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/17622/1/19.%20Laccase%20as%20bio-pretreatment%20step%20of%20sawdust%20for%20ethanol%20production%20-%20%20optimization%20and%20statistical%20modeling.pdf Hashabra, Amani M. and Makky, Essam A. and Rashid, Shah Samiur (2017) Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling. In: Proceedings of the FGIC 1st Conference on Governance & Integrity, 3-4 April 2017 , Yayasan Pahang, Kuantan, Malaysia. pp. 355-369.. ISBN 978-967-2054-37-5 http://fgic.ump.edu.my/images/docman/1st-FGIC-Proceedings.pdf
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TD Environmental technology. Sanitary engineering
spellingShingle TD Environmental technology. Sanitary engineering
Hashabra, Amani M.
Makky, Essam A.
Rashid, Shah Samiur
Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
description For a successful refining of lignocellulosic biomass in production of bioethanol, it needs a delignification step to increase production of sugar. In this study, we use Laccase enzyme (as environment-friendly pretreatment) to pretreat sawdust and evaluate the degree of delignification after pretreatment in terms of weight loss percentage (%) and Total sugar produced (mg/dL). The parameters used in the optimization process was temperature (oC), pH, time of pretreatment (hrs), enzyme concentration (IU/g), substrate concentration (%), substrate size (mm) and speed of agitation (RPM). In order to achieve best condition of pretreatment, first, we use the one-factor-at-a-time (OFAT) analysis to see the significance of parameters then the Face-Centered Central Composite Design (FCCCD) of Response Surface Methodology (RSM) is used to study the combined effect of temperature and pH parameters. Our experimental results show that optimized conditions for sawdust pretreatment are: temperature, 35oC; pH 5; time, 10 hrs; enzyme concentration, 20 IU/g of sawdust; substrate concentration, 5% (w/v); sample size, 1 mm and Agitation, 150 rpm. The experiments also show a high pretreatment result considering energy sustainability which can be achieved by using sample Size of 2 mm, temperature of 25 °C and 4 hrs.
format Conference or Workshop Item
author Hashabra, Amani M.
Makky, Essam A.
Rashid, Shah Samiur
author_facet Hashabra, Amani M.
Makky, Essam A.
Rashid, Shah Samiur
author_sort Hashabra, Amani M.
title Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
title_short Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
title_full Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
title_fullStr Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
title_full_unstemmed Laccase as Bio-Pretreatment Step of Sawdust for Ethanol Production: Optimization and Statistical Modeling
title_sort laccase as bio-pretreatment step of sawdust for ethanol production: optimization and statistical modeling
publisher Universiti Malaysia Pahang
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/17622/1/19.%20Laccase%20as%20bio-pretreatment%20step%20of%20sawdust%20for%20ethanol%20production%20-%20%20optimization%20and%20statistical%20modeling.pdf
http://umpir.ump.edu.my/id/eprint/17622/
http://fgic.ump.edu.my/images/docman/1st-FGIC-Proceedings.pdf
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score 13.214268