Process Biotechnology

Biofilms

Electronic Journal of Biotechnology ISSN: 0717-3458 Vol. 10 No. 1, Issue of January 15, 2007
© 2007 by Pontificia Universidad Católica de Valparaíso -- Chile Received May 8, 2006 / Accepted August 9, 2006
DOI: 10.2225/vol10-issue1-fulltext-8  
RESEARCH ARTICLE

Fast and reliable calibration of solid substrate fermentation kinetic models using advanced non-linear programming techniques

M. Macarena Araya
Departamento de Ingeniería Química y de Bioprocesos
Escuela de Ingeniería
Pontificia Universidad Católica de Chile
Casilla 306, Santiago 22, Chile 

Juan J. Arrieta
Department of Chemical Engineering
Carnegie Mellon University
Doherty Hall, 5000 Forbes Avenue
Pittsburgh, Pennsylvania 15213, USA 

J. Ricardo Pérez-Correa*
Departamento de Ingeniería Química y de Bioprocesos
Escuela de Ingeniería
Pontificia Universidad Católica de Chile
Casilla 306, Santiago 22, Chile
Tel: 562 3544258
Fax: 562-354-5803
Email: perez@ing.puc.cl 

Lorenz T. Biegler
Department of Chemical Engineering
Carnegie Mellon University
Doherty Hall, 5000 Forbes Avenue
Pittsburgh, Pennsylvania 15213, USA
Fax: 1 412 268 7139
E-mail: lb01@andrew.cmu.edu

Héctor Jorquera
Departamento de Ingeniería Química y de Bioprocesos
Escuela de Ingeniería
Pontificia Universidad Católica de Chile
Casilla 306, Santiago 22, Chile
Fax: 562-354-5803
Email: jorquera@ing.puc.cl

Webpage: http://www.ing.puc.cl

*Corresponding author

Financial support: Projects FONDECYT 1030325 and 7040084.

Keywords: dynamic models, Gibberella fujikuroi, Gibberellic acid, nonlinear models, parameter estimation, secondary metabolites, solid substrate cultivation.

Abbreviations:

NLP: non-linear program
SeqSO: sequential solution/optimization
SimSO: simultaneous solution/optimization
SSF: Solid substrate fermentation

Abstract
Full Text

Calibration of mechanistic kinetic models describing microorganism growth and secondary metabolite production on solid substrates is difficult due to model complexity given the sheer number of parameters needing to be estimated and violation of standard conditions of numerical regularity. We show how advanced non-linear programming techniques can be applied to achieve fast and reliable calibration of a complex kinetic model describing growth of Gibberella fujikuroi and production of gibberellic acid on an inert solid support in glass columns. Experimental culture data was obtained under different temperature and water activity conditions. Model differential equations were discretized using orthogonal collocations on finite elements while model calibration was formulated as a simultaneous solution/optimization problem. A special purpose optimization code (IPOPT) was used to solve the resulting large-scale non-linear program. Convergence proved much faster and a better fitting model was achieved in comparison with the standard sequential solution/optimization approach. Furthermore, statistical analysis showed that most parameter estimates were reliable and accurate.

Supported by UNESCO / MIRCEN network