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Biosynthesis of Ethanol and Hydrogen by Glycerol Fermentation Using <i>Escherichia coli</i>
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作者 Nida Chaudhary michael o. ngadi +1 位作者 Benjamin K. Simpson Lamin S. Kassama 《Advances in Chemical Engineering and Science》 2011年第3期83-89,共7页
Production of high value products from glycerol via anaerobic fermentation is of utmost importance for the biodiesel industry. The microorganism Escherichia coli (E. coli) K12 was used for fermentation of glycerol. Th... Production of high value products from glycerol via anaerobic fermentation is of utmost importance for the biodiesel industry. The microorganism Escherichia coli (E. coli) K12 was used for fermentation of glycerol. The effects of glycerol concentration and headspace conditions on the cell growth, ethanol and hydrogen production were investigated. A full factorial experimental design with 3 replicates was conducted in order to test these factors. Under the three headspace conditions tested, the increase of glycerol concentration accelerated glycerol fermentation. The yields of hydrogen and ethanol were the lowest when glycerol concentration of 10 g/L was used. The maximum production of hydrogen was observed with an initial glycerol concentration of 25 g/L at a final concentration of hydrogen was 32.15 mmol/L. This study demonstrated that hydrogen production negatively affects cell growth. Maximum ethanol yield was obtained with a glycerol concentration of 10 g/L and was up to 0.40 g/g glycerol under membrane condition headspace. Statistical optimization showed that optimal conditions for hydrogen production are 20 g/L initial glycerol with initial sparging of the reactor headspace. The optimal conditions for ethanol production are 10 g/L initial glycerol with membrane. 展开更多
关键词 Fermentation ETHANOL HYDROGEN GLYCEROL Cell Growth Reactor HEADSPACE
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基于高光谱图像技术的雪花梨品质无损检测 被引量:109
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作者 洪添胜 乔军 +3 位作者 Ning Wang michael o. ngadi 赵祚喜 李震 《农业工程学报》 EI CAS CSCD 北大核心 2007年第2期151-155,共5页
为探讨基于高光谱图像技术对雪花梨品质进行无损检测的可行性,研究了利用高光谱图像系统提取雪花梨中糖和水的光谱响应和形态特征参数,获取样品含糖量和含水率的敏感水分吸收光谱带,利用人工神经网络建立雪花梨含糖量和含水率预测模型... 为探讨基于高光谱图像技术对雪花梨品质进行无损检测的可行性,研究了利用高光谱图像系统提取雪花梨中糖和水的光谱响应和形态特征参数,获取样品含糖量和含水率的敏感水分吸收光谱带,利用人工神经网络建立雪花梨含糖量和含水率预测模型及利用投影图像面积预测雪花梨鲜重。结果表明,基于高光谱图像技术对雪花梨品质进行无损检测是可行的。雪花梨含糖量预测值和实际值间相关系数R为0.996,误差平均值为0.5°Brix;含水率预测值和实际值间相关系数R为0.94,相对误差平均值为0.62%;鲜重预测值和实际值间相关系数R为0.93。 展开更多
关键词 高光谱图像 雪花梨 无损检测 人工神经网络 水果品质
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