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Optimization of saccharification of sweet sorghum bagasse using response surface methodology

► Lignocellulose rich sweet sorghum bagasse was used as a substrate for cellulolytic hydrolysis. ► The process for saccharification of SSB was optimized with response surface methodology using Box–Behnken design. ► To make the saccharification process economic and cost-effective, crude cellulase enz...

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Published in:Industrial crops and products 2013-01, Vol.44, p.211-219
Main Authors: Saini, Jitendra K., Anurag, Rahul K., Arya, Arti, Kumbhar, B.K., Tewari, Lakshmi
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Tewari, Lakshmi
description ► Lignocellulose rich sweet sorghum bagasse was used as a substrate for cellulolytic hydrolysis. ► The process for saccharification of SSB was optimized with response surface methodology using Box–Behnken design. ► To make the saccharification process economic and cost-effective, crude cellulase enzyme produced by novel fungal consortium of Aspergillus flavus F-80 and A. niger MTCC-2425 was used for saccharification process. ► Structural modification of SSB due to enzymatic saccharification was supported by changes in thermal decomposition behavior and pore formation observed during thermogravimetric and SEM analysis, respectively. The lignocellulose rich sweet sorghum bagasse (SSB) is a good feedstock for bioethanol production after conversion of its insoluble carbohydrates, mainly cellulose, to fermentable sugars. Main focus of the present investigation was therefore, to determine the optimum conditions for enzymatic saccharification of SSB using indigenously produced cellulases from a novel fungal consortium of Aspergillus flavus F-80 and Aspergillus niger MTCC-2425. Response surface methodology was adopted by using a three factor-three level Box–Behnken design by selecting substrate concentration (%, w/v), saccharification time (h) and enzyme loading (FPUg−1substrate) as the main process parameters. Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The developed model was found to be robust and was used to optimize the % saccharification yield during enzymatic hydrolysis. Under optimized conditions (substrate concentration 6%, w/v, time 48h and enzyme loading of 22FPUg−1substrate), maximum saccharification yield of 51.21% was achieved. Structural modification of SSB due to enzymatic saccharification was supported by changes in thermal decomposition behavior and pore formation observed during thermogravimetric and SEM analysis, respectively.
doi_str_mv 10.1016/j.indcrop.2012.11.011
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The lignocellulose rich sweet sorghum bagasse (SSB) is a good feedstock for bioethanol production after conversion of its insoluble carbohydrates, mainly cellulose, to fermentable sugars. Main focus of the present investigation was therefore, to determine the optimum conditions for enzymatic saccharification of SSB using indigenously produced cellulases from a novel fungal consortium of Aspergillus flavus F-80 and Aspergillus niger MTCC-2425. Response surface methodology was adopted by using a three factor-three level Box–Behnken design by selecting substrate concentration (%, w/v), saccharification time (h) and enzyme loading (FPUg−1substrate) as the main process parameters. Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The developed model was found to be robust and was used to optimize the % saccharification yield during enzymatic hydrolysis. Under optimized conditions (substrate concentration 6%, w/v, time 48h and enzyme loading of 22FPUg−1substrate), maximum saccharification yield of 51.21% was achieved. 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The lignocellulose rich sweet sorghum bagasse (SSB) is a good feedstock for bioethanol production after conversion of its insoluble carbohydrates, mainly cellulose, to fermentable sugars. Main focus of the present investigation was therefore, to determine the optimum conditions for enzymatic saccharification of SSB using indigenously produced cellulases from a novel fungal consortium of Aspergillus flavus F-80 and Aspergillus niger MTCC-2425. Response surface methodology was adopted by using a three factor-three level Box–Behnken design by selecting substrate concentration (%, w/v), saccharification time (h) and enzyme loading (FPUg−1substrate) as the main process parameters. Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The developed model was found to be robust and was used to optimize the % saccharification yield during enzymatic hydrolysis. Under optimized conditions (substrate concentration 6%, w/v, time 48h and enzyme loading of 22FPUg−1substrate), maximum saccharification yield of 51.21% was achieved. Structural modification of SSB due to enzymatic saccharification was supported by changes in thermal decomposition behavior and pore formation observed during thermogravimetric and SEM analysis, respectively.</description><subject>analysis of variance</subject><subject>Aspergillus flavus</subject><subject>Aspergillus niger</subject><subject>Aspergillus spp</subject><subject>bagasse</subject><subject>Bioprocess optimization</subject><subject>Box–Behnken design (BBD)</subject><subject>cellulases</subject><subject>cellulose</subject><subject>enzymatic hydrolysis</subject><subject>ethanol production</subject><subject>feedstocks</subject><subject>response surface methodology</subject><subject>Response surface methodology (RSM)</subject><subject>Saccharification</subject><subject>Sorghum</subject><subject>sugars</subject><subject>sweet sorghum</subject><subject>Sweet sorghum bagasse</subject><subject>thermal degradation</subject><issn>0926-6690</issn><issn>1872-633X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkMFq3DAQhkVpodukj1DqYy92ZmRbuzqVEpq2EMihCfQQELI08mpZW67GbkmfPg4byLGnYYbvn2E-IT4gVAioLg5VHL3LaaokoKwQK0B8JTa428pS1fWv12IDWqpSKQ1vxTvmAwBuQW434v5mmuMQ_9k5prFIoWDr3N7mGKJ7mf0lmgtOud8vQ9HZ3jJTsXAc-yITT2lcW15ysI6KgeZ98umY-odz8SbYI9P753om7q6-3l5-L69vvv24_HJdulqpuWx3DqnRqqGdtNp7LZtAsrMA5Dtrra-D0wFlt1OdIyDl6tppHbzusA6yq8_Ep9PeKaffC_FshsiOjkc7UlrYYCubRrZNq1e0PaGrL-ZMwUw5DjY_GATzZNMczLNN82TTIJrV5pr7eMoFm4ztc2Rz93MFGgBoG2hhJT6fCFo__RMpG3aRRkc-ZnKz8Sn-58Yj1j-NQQ</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Saini, Jitendra K.</creator><creator>Anurag, Rahul K.</creator><creator>Arya, Arti</creator><creator>Kumbhar, B.K.</creator><creator>Tewari, Lakshmi</creator><general>Elsevier B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>201301</creationdate><title>Optimization of saccharification of sweet sorghum bagasse using response surface methodology</title><author>Saini, Jitendra K. ; 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The lignocellulose rich sweet sorghum bagasse (SSB) is a good feedstock for bioethanol production after conversion of its insoluble carbohydrates, mainly cellulose, to fermentable sugars. Main focus of the present investigation was therefore, to determine the optimum conditions for enzymatic saccharification of SSB using indigenously produced cellulases from a novel fungal consortium of Aspergillus flavus F-80 and Aspergillus niger MTCC-2425. Response surface methodology was adopted by using a three factor-three level Box–Behnken design by selecting substrate concentration (%, w/v), saccharification time (h) and enzyme loading (FPUg−1substrate) as the main process parameters. Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The developed model was found to be robust and was used to optimize the % saccharification yield during enzymatic hydrolysis. Under optimized conditions (substrate concentration 6%, w/v, time 48h and enzyme loading of 22FPUg−1substrate), maximum saccharification yield of 51.21% was achieved. Structural modification of SSB due to enzymatic saccharification was supported by changes in thermal decomposition behavior and pore formation observed during thermogravimetric and SEM analysis, respectively.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.indcrop.2012.11.011</doi><tpages>9</tpages></addata></record>
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subjects analysis of variance
Aspergillus flavus
Aspergillus niger
Aspergillus spp
bagasse
Bioprocess optimization
Box–Behnken design (BBD)
cellulases
cellulose
enzymatic hydrolysis
ethanol production
feedstocks
response surface methodology
Response surface methodology (RSM)
Saccharification
Sorghum
sugars
sweet sorghum
Sweet sorghum bagasse
thermal degradation
title Optimization of saccharification of sweet sorghum bagasse using response surface methodology
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