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Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100
Zhang, Yu1,2; Xu, Jingliang1; Yuan, Zhenhong1; Xu, Huijuan1; Yu, Qiang1,2
2010-05-01
Source PublicationBIORESOURCE TECHNOLOGY
ISSN0960-8524
Volume101Issue:9Pages:3153-3158
Contribution Rank[Zhang, Yu; Xu, Jingliang; Yuan, Zhenhong; Xu, Huijuan; Yu, Qiang] Chinese Acad Sci, Guangzhou Inst Energy Convers, Key Lab Renewable Energy & Gas Hydrate, Guangzhou 510640, Guangdong, Peoples R China; [Zhang, Yu; Yu, Qiang] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
Corresponding Authoryuanzh@ms.giec.ac.cn
AbstractCellulase was covalently immobilized on a smart polymer, Eudragit L-100 by carbodiimide coupling. Using data of central composite design, response surface methodology (RSM) and artificial neural network (ANN) were developed to investigate the effect of pH, carbodiimide concentration, and coupling time on the activity yield of immobilized cellulase. Results showed simulation and prediction accuracy of ANN was apparently higher compared to RSM. The Maximum activity yield obtained from RSM was 57.56% at pH 5.54, carbodiimide concentration 0.32%, and coupling time 3.03 h, where the experimental value was 60.87 +/- 4.79%. Using ANN as fitness function, a maximum activity yield of 69.83% was searched by genetic algorithm at pH 5.07, carbodiimide concentration 0.36%, and Coupling time 4.10 h, where the experimental value was 66.75 +/- 5.21%. ANN gave a 9.7% increase of activity yield over RSM. After reusing immobilized cellulase for 5 cycles, the remaining productivity was over 50%. (C) 2009 Elsevier Ltd. All rights reserved.
SubtypeArticle
Other AbstractCellulase was covalently immobilized on a smart polymer, Eudragit L-100 by carbodiimide coupling. Using data of central composite design, response surface methodology (RSM) and artificial neural network (ANN) were developed to investigate the effect of pH, carbodiimide concentration, and coupling time on the activity yield of immobilized cellulase. Results showed simulation and prediction accuracy of ANN was apparently higher compared to RSM. The Maximum activity yield obtained from RSM was 57.56% at pH 5.54, carbodiimide concentration 0.32%, and coupling time 3.03 h, where the experimental value was 60.87 +/- 4.79%. Using ANN as fitness function, a maximum activity yield of 69.83% was searched by genetic algorithm at pH 5.07, carbodiimide concentration 0.36%, and Coupling time 4.10 h, where the experimental value was 66.75 +/- 5.21%. ANN gave a 9.7% increase of activity yield over RSM. After reusing immobilized cellulase for 5 cycles, the remaining productivity was over 50%. (C) 2009 Elsevier Ltd. All rights reserved.
KeywordImmobilized Cellulase Artificial Neural Network Smart Biocatalysis Response Surface Methodology Generic Algorithm
Subject AreaAgriculture ; Biotechnology & Applied Microbiology ; Energy & Fuels
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine ; Technology
DOI10.1016/j.biortech.2009.12.080
WOS Subject ExtendedAgriculture ; Biotechnology & Applied Microbiology ; Energy & Fuels
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WOS KeywordXYLAN-DEGRADING ENZYMES ; REPEATED HYDROLYSIS ; MEDIA OPTIMIZATION ; INTELLIGENCE ; KINETICS ; BIOMASS ; MODEL ; ACID
Indexed BySCI
Language英语
Funding OrganizationChinese Academy of Sciences [KSCX-YW-11-A3, KSCX2-YW-G-075, KSCX2-YW-G-063]; National High Technology Research and Development Program of China [2007AA05Z406, 2007AA100702-4, 2009AA05Z436]
WOS SubjectAgricultural Engineering ; Biotechnology & Applied Microbiology ; Energy & Fuels
WOS IDWOS:000274972600035
Citation statistics
Cited Times:57[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.giec.ac.cn/handle/344007/8501
Collection中国科学院广州能源研究所
生物质能源生化转化实验室
Affiliation1.Chinese Acad Sci, Guangzhou Inst Energy Convers, Key Lab Renewable Energy & Gas Hydrate, Guangzhou 510640, Guangdong, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Yu,Xu, Jingliang,Yuan, Zhenhong,et al. Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100[J]. BIORESOURCE TECHNOLOGY,2010,101(9):3153-3158.
APA Zhang, Yu,Xu, Jingliang,Yuan, Zhenhong,Xu, Huijuan,&Yu, Qiang.(2010).Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100.BIORESOURCE TECHNOLOGY,101(9),3153-3158.
MLA Zhang, Yu,et al."Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100".BIORESOURCE TECHNOLOGY 101.9(2010):3153-3158.
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