Predicting trehalose cytoplasmic content during a Saccharomyces cerevisiae biomass production process

被引：0

作者：

Aranda, J. S. ^{[1
]}

Cabrera, A. I. ^{[2
]}

Chairez, J. I. ^{[2
]}

机构：

[1] IPN, Unidad Profes Interdisciplinaria Biotecnol, Dept Bioingn, Mexico City 07340, DF, Mexico

[2] IPN, Unidad Profes Interdisciplinaria Biotecnol, Dept Bioelect, Mexico City 07340, DF, Mexico

来源：

REVISTA MEXICANA DE INGENIERIA QUIMICA | 2008年 / 7卷 / 01期

关键词：

Saccharomyces cerevisiae; trehalose; biomass production; dynamical neural networks; structured modelling; process identification;

D O I：

暂无

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

Trehalose is a dimeric carbohydrate and yeast biomass component generally used as an indicator of good viability and fermentation capacity. Yeast biomass production processes aim at inducing an intracellular accumulation of trehalose. However, during a production process, the trehalose must be quantified by off-line analytical methods after sample taking because it is a cytoplasmic compound. Thus, knowing experimental measurements of yeast trehalose content is always delayed. As a result, not oportune actions can be implemented in order to lead the production process toward a high intracellular trehalose accumulation in the produced biomass. Therefore, an online estimation method to forecast real-time intracellular trehalose content in yeast is developed. It is based on the main metabolic events involved in trehalose biosynthesis, as well as on a differential neural network algorithm to estimate trehalose concentration in the cytoplasm.

引用

页码：71 / 78

页数：8

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