Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Control of Feed Rate Using Neurocontroller Incorporated with Genetic Algorithm in Fed-Batch Cultivation of Scutellaria baicalensis Georgi

  • Choi, Jeong-Woo (Department of Chemical Engineering, Sogang University) ;
  • Lee, Woochang (Department of Chemical Engineering, Sogang University) ;
  • Cho, Jin-Man (Department of Chemical Engineering, Sogang University) ;
  • Kim, Young-Kee (Department of Chemical Engineering, Hankyong University) ;
  • Park, Soo-Yong (Department of Computer Science, Sogang University) ;
  • Lee, Won-Hong (Department of Chemical Engineering, Sogang University)
  • Published : 2002.08.01
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Abstract

To enhance the production of flavonoids [baicalin, wogonin-7-Ο-glucuronic acid (GA)], which are secondary metabolites of Scutellaria baicalensis Georgi(G.) plant cells, a multilayer perceptron control system was applied to regulate the substrate feeding in a fed-batch cultivation. The optimal profile for the substrate feeding rate in a fed-batch culture of S. baicalensis G. was determined by simulating a kinetic model using a genetic algorithm. Process variable profiles were then prepared for the construction of a multilayer perceptron controller that included massive parallelism, trainability, and fault tolerance. An error back-propagation algorithm was applied to train the multiplayer perceptron. The experimental results showed that neurocontrol incorporated with a genetic algorithm improved the flavonoid production compared with a simple fuzzy logic control system. Furthermore, the specific production yield and flavonoid productivity also increased.

Keywords

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