Abstract
Trehalose is commonly used as an indicator of a good yeast fermentation capacity and viability. An attempt of estimating trehalose concentration in yeast cells through two different mathematical approaches is presented. It combines a biomass and trehalose concentrations estimator developed with a differential neural network technique, and a structured model applied for explaining the main metabolic events that induce trehalose accumulation. Our results allow us to think that the coupling of both methods can provide suitable information aimed at reaching a high trehalose content in an actual yeast production process.
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