Combining Mechanistic Modeling and Raman Spectroscopy for Real-Time Monitoring of Fed-Batch Penicillin Production

被引：34
|
作者：
Golabgir, Aydin [1 ]
Herwig, Christoph [1 ,2 ]
机构：
[1] Vienna Univ Technol, Inst Chem Engn, Gumpendorfer Str 1a-166-4, A-1060 Vienna, Austria
[2] Vienna Univ Technol, CD Lab Mechanist & Physiol Methods Improved Biopr, Gumpendorfer Str 1a-166-4, A-1060 Vienna, Austria
来源：
CHEMIE INGENIEUR TECHNIK | 2016年 / 88卷 / 06期
关键词：
Bioprocess monitoring; Mechanistic modeling; Raman spectroscopy; Soft sensor; STRUCTURED MODEL; PAT APPLICATIONS; SOFT SENSORS; GROWTH; CHRYSOGENUM; PARAMETERS; REGRESSION; GLUCOSE; TOOL;
D O I：
10.1002/cite.201500101
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
A soft sensor that combines data from Raman spectroscopy and off-gas analyzers with a dynamic mechanistic bioprocess model was investigated for online monitoring of the physiological characteristics of Penicillium chrysogenum fed-batch cultivations. A systematic workflow based on nonlinear observability analysis was established for accelerating and improving the process of soft-sensor development. Using in situ Raman spectroscopy, it was possible to perform accurate and frequent measurements of the penicillin concentration in the bioreactor, which were combined with measurements of respiratory rates. Using a particle filter algorithm, the soft sensor allowed for the online estimation of the biomass concentration, the specific growth rate, and the specific penicillin production rate.
引用
收藏
页码：764 / 776
页数：13
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