详细信息
Kinetic analysis of sodium gluconate production by Aspergillus niger with different inlet oxygen concentrations ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Kinetic analysis of sodium gluconate production by Aspergillus niger with different inlet oxygen concentrations
作者:Tian, Xiwei[1];Shen, Yuting[1];Zhuang, Yingping[1];Zhao, Wei[2];Hang, Haifeng[1];Chu, Ju[1]
机构:[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, 130 Meilong Rd,POB 329, Shanghai 200237, Peoples R China;[2]Shan Dong Fuyang Biol Technol Co Ltd, Dezhou, Peoples R China
年份:2018
卷号:41
期号:11
起止页码:1697
外文期刊名:BIOPROCESS AND BIOSYSTEMS ENGINEERING
收录:;EI(收录号:20183205667934);WOS:【SCI-EXPANDED(收录号:WOS:000447956900011)】;
基金:This work was financially supported by the National Science Foundation for Young Scientists of China (31700038), the National Key Research and Development Program (2017YFB0309302), and the Fundamental Research Funds for the Central Universities (WF1814032, 22221818014).
语种:英文
外文关键词:Aspergillus niger; Sodium gluconate; Oxygen; Kinetics
摘要:To further understand fermentation kinetics of sodium gluconate (SG) production by Aspergillus niger with different inlet oxygen concentrations, logistic model for cell growth and two-step models for SG production and glucose consumption were established. The results demonstrated that the maximum specific growth rate (mu(m)) presented exponential relationship with inlet oxygen concentration and the maximum biomass (X-m) exhibited linear increase. In terms of SG production, two-step model with Luedeking-Piret equation during growth phase and oxygen-dependent equation during stationary phase could well fit the experimental data. Notably, high inlet oxygen concentration exponentially improved SG yield (Y-P/S), whereas biomass yield to glucose (Y-X/S) and cell maintenance coefficient (m) were almost independent on inlet oxygen concentration, indicating that high oxygen supply enhancing SG synthesis not only functioning as a substrate directly, but also regulating glucose metabolism towards SG formation. Finally, the applicability and predictability of the proposed models were further validated by additional experiments.
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