中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source

文献类型:期刊论文

作者Guo, Ying1,2; Xu, Jingliang1; Zhang, Yu1,2; Xu, Huijuan1; Yuan, Zhenhong1; Li, Dong1,2
刊名bioresource technology
出版日期2010-11-01
卷号101期号:22页码:8784-8789
关键词Syngas fermentation Clostridium autoethanogenum Response surface methodology Artificial neural network Genetic algorithm
ISSN号0960-8524
产权排序[guo, ying; xu, jingliang; zhang, yu; xu, huijuan; yuan, zhenhong; li, dong] chinese acad sci, guangzhou inst energy convers, key lab renewable energy & gas hydrate, guangzhou 510640, peoples r china; [guo, ying; zhang, yu; li, dong] chinese acad sci, grad univ, beijing 100049, peoples r china
通讯作者xjl@ms.giec.ac.cn ; yuanzh@ms.giec.ac.cn
中文摘要plackett-burman and central composite designs were applied to optimize the medium for ethanol production by clostridium autoethanogenum with co as sole carbon source, and a medium containing (g/l): nacl 1.0, kh(2)po(4) 0.1, cacl(2) 0.02, yeast extract 0.15. mgso(4) 0.116, nh(4)cl 1.694 and ph 4.74 was found optimal. the optimum ethanol yields predicted by response surface methodology (rsm) and an artificial neural network-genetic algorithm (ann-ga) were 247.48 and 261.48 mg/l, respectively. these values are similar to those obtained experimentally under the optimal conditions suggested by the statistical methods (254.26 and 259.64 mg/l). the fitness of the ann-ga model was higher than that of the rsm model. the yields obtained substantially exceed those previously reported (60-70 mg/l) with this organism.
英文摘要plackett-burman and central composite designs were applied to optimize the medium for ethanol production by clostridium autoethanogenum with co as sole carbon source, and a medium containing (g/l): nacl 1.0, kh(2)po(4) 0.1, cacl(2) 0.02, yeast extract 0.15. mgso(4) 0.116, nh(4)cl 1.694 and ph 4.74 was found optimal. the optimum ethanol yields predicted by response surface methodology (rsm) and an artificial neural network-genetic algorithm (ann-ga) were 247.48 and 261.48 mg/l, respectively. these values are similar to those obtained experimentally under the optimal conditions suggested by the statistical methods (254.26 and 259.64 mg/l). the fitness of the ann-ga model was higher than that of the rsm model. the yields obtained substantially exceed those previously reported (60-70 mg/l) with this organism. (c) 2010 elsevier ltd. all rights reserved.
WOS标题词science & technology ; life sciences & biomedicine ; technology
学科主题agriculture ; biotechnology & applied microbiology ; energy & fuels
类目[WOS]agricultural engineering ; biotechnology & applied microbiology ; energy & fuels
研究领域[WOS]agriculture ; biotechnology & applied microbiology ; energy & fuels
关键词[WOS]artificial neural-networks ; genetic algorithms ; synthesis gas ; sp-nov ; biological production ; fermentation ; biomass ; ljungdahlii ; growth ; cells
收录类别SCI
资助信息national high technology research and development program of china [2007aa05z406]; chinese academy of sciences [kgcx2-yw-335, kscx-yw-11-a3, kscx2-yw-g-075-09]
原文出处https://dx.doi.org/10.1016/j.biortech.2010.06.072
语种英语
WOS记录号WOS:000281262900044
公开日期2014-12-24
源URL[http://ir.giec.ac.cn/handle/344007/8472]  
专题中国科学院广州能源研究所
生物质能源生化转化实验室
作者单位1.Chinese Acad Sci, Guangzhou Inst Energy Convers, Key Lab Renewable Energy & Gas Hydrate, Guangzhou 510640, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Guo, Ying,Xu, Jingliang,Zhang, Yu,et al. Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source[J]. bioresource technology,2010,101(22):8784-8789.
APA Guo, Ying,Xu, Jingliang,Zhang, Yu,Xu, Huijuan,Yuan, Zhenhong,&Li, Dong.(2010).Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source.bioresource technology,101(22),8784-8789.
MLA Guo, Ying,et al."Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source".bioresource technology 101.22(2010):8784-8789.

入库方式: OAI收割

来源:广州能源研究所

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