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薯干粉间歇式酒精发酵动力学研究 被引量:1

Kinetic Consideration About the Study of Batch Alcoholic Fermentation of Starch Hydrolysate of Batata
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摘要 本文报道了以薯干粉为底物原材料,用两个酿酒酵母1308~#和5~#,以90、135、185,285g/L(以葡萄糖含量计)4个不同底物浓度进行间歇式酒精发酵过程中的动力学研究,在所得大量实验数据的基础上,经计算机处理,建立了新的动力学模型.并且用这个模型可以确定产物抑制发生的时刻,本文还指出:薯干粉原料发酵最适底物浓度为90—135g/l. The kinetic consideration about the study of batch alcoholic fermentation of starch hydrolysate of batata was reported for four different initial glucose concentration,namely 90,135,185,285g/1,and 5~# and 1308~# saccharomyces cerevisiae yeast strains in fermentation. Based on a lot of experimental data,a new kinetic model r=Ae^(B(?))[1- (P/P_m)]~n was proposed to evaluate the influences of substrate and product inhibition on the specific yeild.The experimental results showed that A and B in the kinetic model were the parameters which represented the substrate inhibition degrees respectively:A value was dependent on not only the substrate concentrations,but also the species of yeast strains,while B value dependent on the substrate concentrations only,but independent on the species of yeast strains.The exponent n was a parameter which indicated the pro- duct inhibition degrees.Moreover,the time at which the product inhibition effect happened could be determined by this model.For the above substrate, the product inhibition occured at about 1/2 P_m for 1308~# strain and 1/3P_m for 5~# strain respectively.The optimal range of substrate concentration covered 90-135g/1.
出处 《成都科技大学学报》 EI CAS CSCD 1991年第2期7-12,20,共7页
关键词 薯干 酒精 发酵 间歇式 动力学模型 batata alcoholic fermentation hinetic model
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  • 1Jeongseok Lee, Sang Yup Lee, Sunwon Park, Anton P J Middelberg. Control of fed-batch fermentations.Biotechnology advances, 1999,17(1): 29-48.
  • 2Dimitris C Psichogios, Lyle H Ungar. A hybrid network-first principles approach to process modeling.AIChE Journal,1992,38(10):1499-1511.
  • 3Caracotsion M, Stewart W E. Sensitivity analysis of initial value problems with mixed ODE'S and algebraic equations.Comp.Chem.Eng., 1985,9:359-365.
  • 4Vapnik V N. The Nature of Statistical Learning Theory. New York: Springer, 1995.
  • 5Lin C J. On the convergence of the decomposition method for support vector machines.IEEE Transactions on Neural Networks, 2001,12 (6): 1288.
  • 6Shene C,Diez C,Bravo S.Neural networks for the prediction of the state of Zymomonas mobilis CP4 batch fermentations.Computers & Chemical Engineering, 1999,23(8):1097-1108.
  • 7Harvey W Blanch, Douglas S Clark. Biochemical Engineering.New York:Marcel Dekker Inc., 1997.
  • 8Michael L Thompson, Mark A Karmer. Modeling chemical processes using prior knowledge and neural networks.AIChE J., 1994,40(8): 1328-1340.
  • 9宋晓峰,俞欢军,陈德钊,胡上序.藉助自适应支持向量机为延迟焦化反应过程建模[J].化工学报,2004,55(1):147-150. 被引量:4

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