Two modelling approaches of winemaking: first principle and metabolic engineering

Charnomordic, Brigitte; David, Robert; Dochain, Denis; Hilgert, Nadine; Mouret, Jean-Roch; Sablayrolles, Jean‐Marie; Wouwer, Alain Vande

doi:10.1080/13873954.2010.514701

Cited by 11 publications

(9 citation statements)

References 39 publications

(65 reference statements)

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“…cerevisiae was expanded from that of Varela and co-workers [6] including the transport reactions for 19 amino acids and ammonium and anabolic or catabolic pathways according to the criteria mentioned above. Moreover, according to the current trend in oenological research [38], the metabolism of fusel alcohols (directly related to amino acid breakdown) has also been included.…”

Section: Resultsmentioning

confidence: 99%

“…Fusel alcohols produced by yeast during wine fermentation have a strong impact on the sensorial properties of the final product [38]. For this reason and for the first time, five of the most relevant fusel alcohols (i.e., isoamyl alcohol, active amyl alcohol, phenyl 2-ethanol, n-propanol and isobutanol) have been analyzed and included in a stoichiometric model.…”

Section: Resultsmentioning

confidence: 99%

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Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

et al. 2013

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As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

et al. 2013

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“…The objective is to find the best compromise between fermentation kinetics and aroma production. The development of metabolic models predicting the synthesis of aroma compounds [20], in combination with the model of gas-liquid partitioning and with a kinetic model [21] represents a complex but very promising prospect. Comparison with k i measured in static conditions by the PRV method ().…”

Section: Resultsmentioning

confidence: 99%

Modelling of the gas–liquid partitioning of aroma compounds during wine alcoholic fermentation and prediction of aroma losses

Morakul¹,

Mouret²,

Nicolle³

et al. 2011

Process Biochemistry

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A model was elaborated to quantify the gas-liquid partitioning of four of the most important volatile compounds produced during winemaking fermentations, namely isobutanol, ethyl acetate, isoamyl acetate and ethyl hexanoate. Analyses of constant rate fermentations demonstrated that the partitioning was not influenced by the CO 2 production rate and was a function of only the must composition and the temperature. The parameters of the model were identified in fermentations run at different temperatures, including anisothermal conditions. The prediction of the partition coefficient (k i) by the model was very accurate for isobutanol, isoamyl acetate and ethyl hexanoate. The technological potential of the model was confirmed by using it to calculate the losses of volatiles in the gas phase during fermentation and comparing them with experimental data. Up to 70% of the produced volatile compounds were lost. The difference between observed losses and losses estimated from predicted k i values never exceeded 3%.

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“…Furthermore, in , thermal phenomena in the fermentation process as the production of heat by the yeast and the heat loss to the environment are considered. In , results of ODE simulations of a fermentation are presented. A first attempt to formulate wine fermentation optimal control problems can be found in with the aim to improve energy saving and aromatic profile.…”

Section: Introductionmentioning

confidence: 99%

Optimal control of a system of reaction–diffusion equations modeling the wine fermentation process

Merger

Borzì

Herzog

2016

Optim Control Appl Methods

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SUMMARYThe investigation of a reaction-diffusion system with new nonlinear reactions kinetics to model the fermentation of wine is presented. The reactive part extends existing ordinary differential models by taking into account oxygen availability and ethanol toxicity. The presence of spatial diffusion and the inclusion of a heat equation allow geometrical and thermal effects in the model. Existence, uniqueness, and regularity of solutions to this system of reaction-diffusion partial differential equations are discussed. A boundary optimal control problem is formulated with the purpose of steering an ideal fermentation process. This optimal control problem is theoretically investigated and numerically solved in the adjoint method framework. The existence of an optimal control is proved, and its solution is characterized by means of the corresponding optimality system. To solve this system, an implicit-explicit splitting approach is considered, and a BroydenFletcher-Goldfarb-Shanno (BFGS) optimization scheme is implemented. Results of numerical experiments demonstrate the validity of the fermentation model and of the proposed control strategy.

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Two modelling approaches of winemaking: first principle and metabolic engineering

Cited by 11 publications

References 39 publications

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

Modelling of the gas–liquid partitioning of aroma compounds during wine alcoholic fermentation and prediction of aroma losses

Optimal control of a system of reaction–diffusion equations modeling the wine fermentation process

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