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.

This work aims to describe the wine fermentation characteristics of 23 natural S. cerevisiae × S. kudriavzevii hybrid yeasts related to fermentative environments isolated from different regions and their significance for the aroma spectra of the produced wines. Fermentations were performed at 12 °C in artificial must, and S. cerevisiae and S. kudriavzevii pure species strains were used for comparison purposes. We determined the relevant kinetic parameters of fermentation, the concentration of the main metabolites and the main aroma-related compounds produced after fermentation. The results revealed that some strains that show well-rounded characteristics could be profitable yeast starters for low-temperature fermentation in winemaking, such as wine hybrid SPG172 but, surprisingly, also beer hybrid CECT11002, adding the efficient fermentative kinetics to the high production of aroma-related compounds. In addition, a novel metabolic correlation between fermentation performance and aroma production is described.

Nonconventional yeasts promise to provide new metabolic pathways for producing industrially relevant compounds and tolerating specific stressors such as cold temperatures. The mechanisms behind the cold tolerance of S. kudriavzevii or its sympatric relationship with S. cerevisiae in Mediterranean oaks are not well understood.

Nitrogen is essential for yeast metabolism and is often added to avoid slow or stuck fermentations in the wine industry. This study aimed to investigate the impact of different nitrogen supplementation strategies on the metabolism of various Saccharomyces yeast strains, with a particular focus on their fermentative performance, primary metabolite production, and aromatic profiles, including polyfunctional mercaptans (PFMs) varietal aromas. Two nitrogen supplements, organic (amino acids) and inorganic (NH₄Cl), were evaluated under conditions and addition limits representative of the oenological industry, using Saccharomyces cerevisiae and interspecific hybrid strains (S. cerevisiae x S. uvarum and S. cerevisiae x S. kudriavzevii). The findings of this study indicate that the effect of nitrogen supplementation on yeast fermentation and aroma production is highly strain dependent. While inorganic nitrogen generally improved fermentation kinetics, its influence on metabolite production and aromatic profiles varied across strains. Nitrogen supplementation had minimal impact on ethanol, glycerol, acetic acid, and malic acid metabolism but significantly affected succinic and lactic acid production. Additionally, organic nitrogen supplementation was particularly effective in enhancing polyfunctional mercaptans (PFMs) in specific strains such as S. cerevisiae x S. kudriavzevii hybrid strains. In contrast, inorganic supplementation favoured the production of ethyl esters and medium chain fatty acids. Overall, the study emphasizes the significance of selecting the appropriate type of nitrogen based on the yeast strain and desired wine characteristics. This knowledge can help winemakers optimize fermentation processes to achieve specific sensory profiles, thereby enhancing the aromatic quality of their wines.

Yeast batch fermentation is widely used in industrial biotechnology, yet its performance is strongly influenced by temperature and nitrogen availability, which affect growth kinetics and metabolite production. The development of predictive models that accurately describe these effects is essential for automating and optimizing fermentation design, reducing trial-and-error experimentation, and improving process efficiency and product quality. However, most mathematical models focus on primary metabolism and lack a systematic approach to integrate the effects of temperature. Existing models often rely on empirical corrections with limited predictive power beyond specific experimental conditions. Furthermore, there is no unified framework for optimizing fermentation processes while accounting for the temperature-dependent metabolic responses. We addressed these gaps by developing a temperature-dependent kinetic model for nitrogen-limited batch fermentation by Saccharomyces cerevisiae. The modeling approach is based on advanced systems identification, integrating identifiability analyses (structural and practical), multi-experiment parameter estimation, and automated model selection to determine the most appropriate temperature dependencies for key metabolic processes. Validated across five industrial S. cerevisiae strains in an illustrative example related to wine fermentation, the model exhibited strong predictive performance (NRMSE $<10.5\%$, median R²$>0.95$) and enabled simulation-based process optimization, including nitrogen-supplementation strategies and strain selection for improved fermentation outcomes. By providing a systematic modeling framework that accounts for temperature effects, this work bridges a critical gap in predictive modeling and advances the rational design and control of industrial fermentation processes.

The species Saccharomyces uvarum and Saccharomyces kudriavzevii have gained popularity in recent decades due to their interesting oenological properties. However, although it plays a crucial role in yeast fermentation performance and compound synthesis, our understanding of nitrogen metabolism in these species remains limited. Therefore, we compared how three strains of Saccharomyces cerevisiae , Saccharomyces uvarum and Saccharomyces kudriavzevii use relevant nitrogen sources by combining quantitative analysis approaches based on isotopic tracing and modelling. The model we have developed aims to facilitate the calculation and interpretation of stable isotope data for other experiments, by providing easy visualisation of the results and predicting the kinetics of isotope incorporation beyond the sampling points. The three species exhibit significant variations in their nitrogen assimilation profile. They differ in the timing of uptake of ammonium, arginine and glutamine: Saccharomyces cerevisiae prefers glutamine, Saccharomyces kudriavzevii ammonium and Saccharomyces uvarum arginine. This contributes to a different pattern of nitrogen redistribution towards proteinogenic amino acids between strains at the start of the exponential phase, which fades on entering the stationary phase. Additionally, we found that the contribution of leucine and valine to isoamyl alcohol production varies between species; also, Saccharomyces kudriavzevii activates the synthesis of volatile compounds earlier.