Premium
A new approach to bioconversion reaction kinetic parameter identification
Author(s) -
Chen Bing H.,
Hibbert Edward G.,
Dalby Paul A.,
Woodley John M.
Publication year - 2008
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.11545
Subject(s) - bioconversion , nonlinear regression , kinetic energy , nonlinear system , transketolase , identification (biology) , linear regression , mathematics , estimation theory , biological system , chemistry , regression analysis , mathematical optimization , statistics , physics , biochemistry , food science , botany , quantum mechanics , fermentation , biology , enzyme
The commonly used methods for bioconversion kinetic parameter identification are linear plotting and nonlinear regression. However, linear plotting methods generally require considerable experimentation, and nonlinear regression can lead to “local optimization” because the obtained parameters depend heavily on given initial values. In this article, a new and reliable nonlinear regression‐based approach to bioconversion kinetic parameter estimation is reported. By obtaining preliminary values of kinetic parameters on a step‐by‐step basis, the number of estimated parameters in each step can be reduced to 3 or 4. These preliminary values can then be used as initial guesses for the final parameter estimation via nonlinear regression. Compared with the linear plotting method, the proposed approach can significantly reduce the number of experiments required for kinetic parameter estimation. The transketolase catalyzed synthesis of 1,3‐dihydroxypentan‐2‐one from propionaldehyde and β‐hydroxypyruvate is used as an experimental example to illustrate the approach. © 2008 American Institute of Chemical Engineers AIChE J, 2008