Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source

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	Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source
	Guo, Ying 1,2; Xu, Jingliang 1; Zhang, Yu1,2 ; Xu, Huijuan 1; Yuan, Zhenhong1 ; Li, Dong 1,2
刊名	bioresource technology
	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
通讯作者	xjl@ms.giec.ac.cn ; yuanzh@ms.giec.ac.cn
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
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.
学科主题	agriculture ; biotechnology & applied microbiology ; energy & fuels
WOS标题词	science & technology ; life sciences & biomedicine ; technology
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
内容类型	期刊论文
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.