Source:http://linkedlifedata.com/resource/pubmed/id/16233002
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4
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| pubmed:dateCreated |
2005-10-19
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| pubmed:abstractText |
Constrained optimization for microbial fermentation was studied. For optimization, we used not the maximum principle but a nonlinear programming method because of the need to consider many metabolic reactions. In the case of L-lysine fermentation, the optimization problem in L-lysine production was formulated as a nonlinear programming problem. In general, the state equations based on material balances are represented as differential equations, but such equations which are dependent on time can not be applied to a nonlinear programming problem. Therefore, the state equations were made discrete in a time base, and a new single vector which is not dependent on time was substituted. From these formulae, the objective function and the constraints using nonlinear programming problem were defined as the amount of L-lysine produced, and as a metabolic reaction model and empirical equations, respectively. Computer program was developed to solve this constrained nonlinear programming problem. The applied algorithm of the computer programming was a sequential quadratic programming method (SQP method). When the constrained nonlinear programming problem is solved using the SQP method, the maximum amount of L-lysine produced and the optimal feeding rate of L-threonine could be calculated. From the calculated results, it was clear that introduction of the equality and inequality constraints was easy. L-Lysine at a concentration up to 75.3 g/l could be produced when the fermentation was carried out under optimal conditions.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:issn |
1389-1723
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
91
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
344-51
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| pubmed:year |
2001
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| pubmed:articleTitle |
Constrained optimization of L-lysine production based on metabolic flux using a mathematical programming method.
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| pubmed:affiliation |
Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Suita, Osaka 565-0871, Japan.
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| pubmed:publicationType |
Journal Article
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