Multigradient method for optimization of slow biotechnological processes

Jussi Tammisola (Corresponding Author), Heikki Ojamo, Veli Kauppinen

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A new method (named a “jumping spider”) is introduced for the optimization of slow biotechnological processes. The more traditional sequential experimentation (i.e., gradient search, simplex, etc.) is not well suited for slow dynamic processes, e.g., plant cell culture and differentiation. Therefore, a more simultaneous approach is proposed. A large number of initial experiments are performed, on the basis of which several of the initial experiments are selected as starting points. A search is then performed simultaneously from several gradient directions and the optimum is estimated by a quadratic approximation. In simulations, the spider generally climbs up the slopes quickly and the final estimator yields good maximum point estimates even on a complex topography. The spider may even approach more than one local maximum point simultaneously. As a model application, the average xylitol conversion rate of Candida guilliermondii was optimized in relation to cultivation volume (oxygen availability) and the concentration of nitrogen and phosphorus in the medium. A threefold increase in xylitol production was obtained with three experimental steps.

Original languageEnglish
Pages (from-to)1301 - 1310
Number of pages10
JournalBiotechnology and Bioengineering
Volume42
Issue number11
DOIs
Publication statusPublished - 1993
MoE publication typeA1 Journal article-refereed

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