SciELO - Scientific Electronic Library Online

 
vol.7 issue1Preliminar study of the vacuum pressure and steam effect on a batch cristalizer at pilot plant levelMicroemulsion polymerization: building a model using the experimental conversion and its derivative author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista mexicana de ingeniería química

Print version ISSN 1665-2738

Abstract

ARANDA, J. S.; CABRERA, A. I.  and  CHAIREZ, J. I.. Predicting trehalose cytoplasmic content during a Saccharomyces cerevisiae biomass production process. Rev. Mex. Ing. Quím [online]. 2008, vol.7, n.1, pp.71-78. ISSN 1665-2738.

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.

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

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License