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A model for L ‐methionine production describing oxygen–productivity relationship
Author(s) -
Ranjan Amalendu P.,
Nayak Rajib,
Gomes James
Publication year - 2009
Publication title -
journal of chemical technology and biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 117
eISSN - 1097-4660
pISSN - 0268-2575
DOI - 10.1002/jctb.2097
Subject(s) - methionine , biological system , nonlinear system , production (economics) , productivity , methionine synthase , nonlinear regression , process (computing) , substrate (aquarium) , chemistry , mathematics , computer science , regression analysis , statistics , amino acid , biochemistry , ecology , physics , biology , economics , macroeconomics , quantum mechanics , operating system
BACKGROUND: The state‐time profile of cell mass, substrate and methionine concentrations of a methionine synthesis process shows strongly nonlinear features. A mathematical representation of this process was developed that conformed to systems analysis required for monitoring and controlling methionine production. The specific growth rate was defined by an exponential term to describe the lag phase in growth, extended before the onset of methionine production and substrate inhibition observed for this process. A switching function was used to describe the relation between methionine synthesis and dissolved oxygen concentration. In addition, the product formation kinetics of this model described the reutilization of methionine feedback regulation whenever the residual substrate concentration dropped below a critical value. RESULTS: The parameters for the model were determined from experimental data using a nonlinear regression technique. A complete nonlinear systems analysis of the model proved that using this model, the system was controllable and observable. The model prediction of methionine production in controlled and uncontrolled environments was satisfactory. Six statistical measures were employed to validate model prediction and its adequacy was shown through simulations. CONCLUSIONS: The proposed model for methionine production possesses the correct system architecture for application in process control. It predicts satisfactorily the relationship between methionine synthesis and dissolved oxygen, and time profiles of state variables. Copyright © 2008 Society of Chemical Industry