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On‐line state recognition in a yeast fed‐batch culture using error vectors
Author(s) -
Shimizu Hiroshi,
Miura Keigo,
Shioya Suteaki,
Suga Kenichi
Publication year - 1995
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.260470207
Subject(s) - yeast , fuzzy logic , ethanol , state (computer science) , energy balance , biological system , line (geometry) , fed batch culture , ethanol fuel , production (economics) , mathematics , state vector , artificial intelligence , computer science , pattern recognition (psychology) , biology , biochemistry , algorithm , fermentation , physics , ecology , geometry , macroeconomics , classical mechanics , economics
The physiological states with respect to cell growth and ethanol production in a yeast fed‐batch culture expressed in linguistic form could be recognized on‐line by fuzzy inferencing based on error vectors. The error vector was newly defined here in a macroscopic elemental balance equation. The physiological states for cell growth and ethanol production were characterized by error vectors using many experimental data from fed‐batch cultures. Fuzzy membership functions were constructed from the frequency distributions of the error vectors and state recognition was performed by fuzzy inferencing. In particular, an unusual physiological state for a yeast cultivation, in which aerobic ethanol production was accompanied by very low cell growth, could be recognized accurately. According to the results of the state recognition, an energy parameter, the P/O ratio in the metabolic reaction model was adaptively estimated, and the cell growth was successfully evaluated with the estimated P/O. © 1995 John Wiley & Sons, Inc.