Multigradient method for optimization of slow biotechnological processes

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

Research output: Contribution to journalArticleScientificpeer-review

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

Fingerprint

Xylitol
Spiders
Plant cell culture
Candida
Phosphorus
Topography
Nitrogen
Experiments
Plant Cells
Availability
Oxygen
Cell Differentiation
Cell Culture Techniques
Direction compound

Cite this

Tammisola, Jussi ; Ojamo, Heikki ; Kauppinen, Veli. / Multigradient method for optimization of slow biotechnological processes. In: Biotechnology and Bioengineering. 1993 ; Vol. 42, No. 11. pp. 1301 - 1310.
@article{19ffa590bf9d46db9a7ccc7b102c3e20,
title = "Multigradient method for optimization of slow biotechnological processes",
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.",
author = "Jussi Tammisola and Heikki Ojamo and Veli Kauppinen",
note = "Project code: -",
year = "1993",
doi = "10.1002/bit.260421107",
language = "English",
volume = "42",
pages = "1301 -- 1310",
journal = "Biotechnology and Bioengineering",
issn = "0006-3592",
publisher = "Wiley",
number = "11",

}

Multigradient method for optimization of slow biotechnological processes. / Tammisola, Jussi (Corresponding Author); Ojamo, Heikki; Kauppinen, Veli.

In: Biotechnology and Bioengineering, Vol. 42, No. 11, 1993, p. 1301 - 1310.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Multigradient method for optimization of slow biotechnological processes

AU - Tammisola, Jussi

AU - Ojamo, Heikki

AU - Kauppinen, Veli

N1 - Project code: -

PY - 1993

Y1 - 1993

N2 - 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.

AB - 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.

U2 - 10.1002/bit.260421107

DO - 10.1002/bit.260421107

M3 - Article

VL - 42

SP - 1301

EP - 1310

JO - Biotechnology and Bioengineering

JF - Biotechnology and Bioengineering

SN - 0006-3592

IS - 11

ER -