Modeling oxygen dissolution and biological uptake during pulse oxygen additions in oenological fermentations.

Discrete oxygen additions during oenological fermentations can have beneficial effects both on yeast performance and on the resulting wine quality. However, the amount and time of the additions must be carefully chosen to avoid detrimental effects. So far, most oxygen additions are carried out empirically, since the oxygen dynamics in the fermenting must are not completely understood. To efficiently manage oxygen dosage, we developed a mass balance model of the kinetics of oxygen dissolution and biological uptake during wine fermentation on a laboratory scale. Model calibration was carried out employing a novel dynamic desorption-absorption cycle based on two optical sensors able to generate enough experimental data for the precise determination of oxygen uptake and volumetric mass transfer coefficients. A useful system for estimating the oxygen solubility in defined medium and musts was also developed and incorporated into the mass balance model. Results indicated that several factors, such as the fermentation phase, wine composition, mixing and carbon dioxide concentration, must be considered when performing oxygen addition during oenological fermentations. The present model will help develop better oxygen addition policies in wine fermentations on an industrial scale.

Coupling kinetic expressions and metabolic networks for predicting wine fermentations.

Problematic fermentations are commonplace and cause wine industry producers substantial economic losses through wasted tank capacity and low value final products. Being able to predict such fermentations would enable enologists to take preventive actions. In this study we modeled sugar uptake kinetics and coupled them to a previously developed stoichiometric model, which describes the anaerobic metabolism of Saccharomyces cerevisiae. The resulting model was used to predict normal and slow fermentations under winemaking conditions. The effects of fermentation temperature and initial nitrogen concentration were modeled through an efficiency factor incorporated into the sugar uptake expressions. The model required few initial parameters to successfully reproduce glucose, fructose, and ethanol profiles of laboratory and industrial fermentations. Glycerol and biomass profiles were successfully predicted in nitrogen rich cultures. The time normal or slow wine fermentations needed to complete the process was predicted accurately, at different temperatures. Simulations with a model representing a genetically modified yeast fermentation, reproduced qualitatively well literature results regarding the formation of minor compounds involved in wine complexity and aroma. Therefore, the model also proves useful to explore the effects of genetic modifications on fermentation profiles.

Fast and reliable calibration of solid substrate fermentation kinetic models using advanced non-linear programming techniques

Calibration of mechanistic kinetic models describing microorganism growth and secondary metabolite production on solid substrates is difficult due to model complexity given the sheer number of parameters needing to be estimated and violation of standard conditions of numerical regularity. We show how advanced non-linear programming techniques can be applied to achieve fast and reliable calibration of a complex kinetic model describing growth of Gibberella fujikuroi and production of gibberellic acid on an inert solid support in glass columns. Experimental culture data was obtained under different temperature and water activity conditions. Model differential equations were discretized using orthogonal collocations on finite elements while model calibration was formulated as a simultaneous solution/optimization problem. A special purpose optimization code (IPOPT) was used to solve the resulting large-scale non-linear program. Convergence proved much faster and a better fitting model was achieved in comparison with the standard sequential solution/optimization approach. Furthermore, statistical analysis showed that most parameter estimates were reliable and accurate.

Wine distillates: practical operating recipe formulation for stills.

Consumer perceptions of flavors are associated with the chemical composition of foods. However, consumer preferences change; therefore, it is necessary for food manufacturers to be able to adapt their products. Unlike in aged spirits, the chemical composition of young spirits is determined during distillation; therefore, this is where distillers must tailor their operating recipes to the new trends. Even for an experienced distiller, the complexity of the process makes adapting the operating recipe far from straightforward. In this study, we developed a methodology for generating practical recipes that makes use of computer simulations and optimization techniques. We used Pisco Brandy, a young Muscat wine distillate from Chile and Peru as our case study. Even so, because our methodology is independent of the chemical composition of the broth, it can be applied throughout the industry. Drawing on the experience and preferences of industry enologists, we designed a preferred distillate and used our methodology to obtain the appropriate recipe. This recipe was validated in lab scale experiments, and we obtained a much closer distillate to the desired prescription than commercial products.

Modeling of yeast metabolism and process dynamics in batch fermentation.

Much is known about yeast metabolism and the kinetics of industrial batch fermentation processes. In this study, however, we provide the first tool to evaluate the dynamic interaction that exists between them. A stoichiometric model, using wine fermentation as a case study, was constructed to simulate batch cultures of Saccharomyces cerevisiae. Five differential equations describe the evolution of the main metabolites and biomass in the fermentation tank, while a set of underdetermined linear algebraic equations models the pseudo-steady-state microbial metabolism. Specific links between process variables and the reaction rates of metabolic pathways represent microorganism adaptation to environmental changes in the culture. Adaptation requirements to changes in the environment, optimal growth, and homeostasis were set as the physiological objectives. A linear programming routine was used to define optimal metabolic mass flux distribution at each instant throughout the process. The kinetics of the process arise from the dynamic interaction between the environment and metabolic flux distribution. The model assessed the effect of nitrogen starvation and ethanol toxicity in wine fermentation and it was able to simulate fermentation profiles qualitatively, while experimental fermentation yields were reproduced successfully as well.