This site is under development. For the current active site, go to bcbhub.csic.es.

Orcid Publication

Detalle de: Modelling the physiological status of yeast during wine fermentation enables the prediction of secondary metabolism

Title Modelling the physiological status of yeast during wine fermentation enables the prediction of secondary metabolism
Abstract

Saccharomyces non‐cerevisiae yeasts are gaining momentum in wine fermentation due to their potential to reduce ethanol content and achieve attractive aroma profiles. However, the design of the fermentation process for new species requires intensive experimentation. The use of mechanistic models could automate process design, yet to date, most fermentation models have focused on primary metabolism. Therefore, these models do not provide insight into the production of secondary metabolites essential for wine quality, such as aromas. In this work, we formulate a continuous model that accounts for the physiological status of yeast, that is, exponential growth, growth under nitrogen starvation and transition to stationary or decay phases. To do so, we assumed that nitrogen starvation is associated with carbohydrate accumulation and the induction of a set of transcriptional changes associated with the stationary phase. The model accurately described the dynamics of time series data for biomass and primary and secondary metabolites obtained for various yeast species in single culture fermentations. We also used the proposed model to explore different process designs, showing how the addition of nitrogen could affect the aromatic profile of wine. This study underlines the potential of incorporating yeast physiology into batch fermentation modelling and provides a new means of automating process design.

Apa Reference Moimenta, A. R., Henriques, D., Minebois, R., Querol, A., & Balsa‐Canto, E. (2023). Modelling the physiological status of yeast during wine fermentation enables the prediction of secondary metabolism. Microbial Biotechnology, 16(4), 847–861. Portico. 10.1111/1751-7915.14211
Doi 10.1111/1751-7915.14211
Publication Date Feb 2023
Publication Type Article
Researcher Eva Balsa Canto
Ontology Biosystems Modeling
Research Groups Biosystems and Bioprocess Engineering (Bio2Eng)
Tools

Suggest changes

Publications are synced automatically from ORCID, so they can't be edited here directly. Spotted something wrong? Let us know below and we'll take care of it.

← Return to Home