Abstract
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.
| Translated title of the contribution | Predicting trehalose cytoplasmic content during a saccharomyces cerevisiae biomass production process |
|---|---|
| Original language | English |
| Pages (from-to) | 71-78 |
| Number of pages | 8 |
| Journal | Revista Mexicana de Ingeniera Quimica |
| Volume | 7 |
| Issue number | 1 |
| State | Published - Apr 2008 |
Keywords
- Biomass production
- Dynamical neural networks
- Process identification
- Saccharomyces cerevisiae
- Structured modelling
- Trehalose