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

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 coul...

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Detalhes bibliográficos
Autores: Moimenta, Artai R, Henriques, David, Minebois, Romain, Querol, Amparo, Balsa-Canto, Eva
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2023
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/297087
Acesso em linha:http://hdl.handle.net/10261/297087
https://api.elsevier.com/content/abstract/scopus_id/85147349834
Access Level:Acceso aberto
Palavra-chave:Saccharomyces non-cerevisiae yeasts
Wine fermentation
Mechanistic models
Secondary metabolites
Wine quality
Descrição
Resumo: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.