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柚苷酶产生菌Penicillium sp.1523分批发酵动力学研究
引用本文:黎继烈,崔培梧,李忠海.柚苷酶产生菌Penicillium sp.1523分批发酵动力学研究[J].中国食品学报,2012,12(1):32-37.
作者姓名:黎继烈  崔培梧  李忠海
作者单位:1. 中南林业科技大学生命科学与技术学院 长沙 410004
2. 中南林业科技大学生命科学与技术学院 长沙 410004;湖南中医药大学药学院 长沙 410208
摘    要:分析柚苷酶产生菌青霉(Penicillium sp.)1523在5 L自控发酵罐中的分批发酵动力学。探讨了青霉1523在5 L罐分批发酵过程中菌体生长、柚苷酶合成及基质消耗的变化规律,结果表明:菌体生长呈典型S型曲线,酶的合成与菌体生长趋势呈现部分相关性,属于部分偶联型。基于这些过程曲线的变化规律,结合Logistic方程和Luedeking-Piret方程,建立了柚苷酶产生菌青霉1523分批发酵过程的动力学模型,并通过数学推导和非线性拟合获得了模型中各参数的最佳取值,最终确定了能够较好表征青霉1523分批发酵过程中菌体生长、产物柚苷酶合成以及基质消耗的动力学方程。

关 键 词:柚苷酶  分批发酵  动力学模型  非线性拟合

Batch Fermentation Kinetics of Naringinase Producing Strain Penicillium sp.1523
Li Jilie , Cui Peiwu , Li Zhonghai.Batch Fermentation Kinetics of Naringinase Producing Strain Penicillium sp.1523[J].Journal of Chinese Institute of Food Science and Technology,2012,12(1):32-37.
Authors:Li Jilie  Cui Peiwu  Li Zhonghai
Affiliation:1(1College of Life Science and Technology,Central South University of Forestry and Technology,Changsha 410004 2College of Pharmaceutical Science,Hunan University of Chinese Medicine,Changsha 410208)
Abstract:The kinetics of naringinase batch fermentation process was studied by Penicillium sp.1523 in a 5 L stirred bioreactor.Firstly cell growth,product formation and substrate consumption throughout the naringinase fermentation were investigated.The result shows that cell growth of Penicillium sp.1523 is characterized as an S-type curve,which presents partial correlation with naringinase synthesis indicating a partial coupling model.Based on variation of these process curves,the kinetics models for cell growth,naringinase synthesis and substrate consumption were established according to the Logistic equation and Luedeking-Piret equation.Through the nonlinear regression and mathematical derivation,the optimal parameters in the above models were obtained.Finally the kinetics equations of cell growth,naringinase synthesis and substrate consumption,which could characterize the batch fermentation process of Penicillium sp.1523,were obtained.
Keywords:naringinase  batch fermentation  kinetics model  nonlinear regression
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