We developed a sensory-based methodology to aromatically enrich wines using different aromatic fractions recovered during fermentations of Sauvignon Blanc must. By means of threshold determination ...and generic descriptive analysis using a trained sensory panel, the aromatic fractions were characterized, selected, and clustered. The selected fractions were grouped, re-assessed, and validated by the trained panel. A consumer panel assessed overall liking and answered a CATA question on some enriched wines and their ideal sample. Differences in elicitation rates between non-enriched and enriched wines with respect to the ideal product highlighted product optimization and the role of aromatic enrichment. Enrichment with aromatic fractions increased the aromatic quality of wines and enhanced consumer appreciation.
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•Sauvignon Blanc wines were enriched with natural aromas condensed from fermentation.•By means of a sensory-based methodology, positive aromatic condensates were selected.•The selected aromatic groups improved the perception of wine quality.•CATA showed the positive effect of aromatic enrichment on consumer perception.
Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a ...challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints.
Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol.
A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations.
Automated algorithm to determine kLa considering system delay Torres, Paulina; Cerri, Marcel Otavio; de Arruda Ribeiro, Marcelo Perencin ...
Journal of chemical technology and biotechnology (1986),
July 2017, Letnik:
92, Številka:
7
Journal Article
This work presents a hybrid model for
Cabernet Sauvignon
(CS) red wine-making that combines mechanistic and data-driven approaches to optimize the fermentation process and improve the quality of red ...wine. The model incorporates two sub-units representing the interaction between alcoholic fermentation and phenolic extraction, considering factors such as temperature, products addition, draining time, and must composition. To develop and validate the model, a database of 270 industrial CS fermentation from 2017-2021 harvest seasons was collected. The models were calibrated using experimental data, achieving an average R
2
of 0.94 for fermentation kinetics model and 45% and 80.9% test accuracy for tannins and anthocyanins predictors, respectively. A multi-objective dynamic optimization problem was formulated and solved to find fermentation operation conditions that optimize simultaneously phenolic quality, process costs and productivity. A similar distribution of the Paretos were obtained for varietal and premium wines. Finally, these tools were packed in a digital platform for practical use in industrial cellars. The models generate the predictions and recipes prescription for each fermentation tank when the pre fermentative juice is analyzed. As a result, it is obtained useful information for wine decision-making like maceration length and wine phenolic composition at least five days in advance.
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.
► Superstructure optimization of bio-processes considering all their individual steps. ► Development of a combined simulation optimization approach for the design of bioprocesses. ► Application of a ...reduced-space mixed-integer dynamic optimization (MIDO) algorithm to the design of biotechnological plants. ► Optimization of the production of L-lysine using systematic mathematical programming tools.
In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer
® with an external NLP solver implemented in Matlab
®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid
L-lysine.
In this study we explore the applicability of MIR technology to detect early indications of wine fermentation problems. An oenologist could improve the chances of a vinification process finishing ...optimally if anomalies are detected early. A comparative analysis of three fermentations with artificial musts was performed; one of normal behaviour, one subject to a temperature gradient, and the third deficient in assimilable nitrogen. We tracked each fermentation through changes in spectra in addition to changes in must composition. It was easier to detect anomalous behaviour by monitoring wine metabolite concentrations than through direct spectra analysis, nevertheless, calibrations needed to be derived from fermenting must samples and so cost more. All measured compounds (glucose, fructose, ethanol, glycerol, succinic and acetic acids) exhibited behavioural changes at 30
h of fermentation in nitrogen deficient musts. Temperature deviations were reflected in the anomalous behaviour of ethanol, glycerol, succinic acid and acetic acid.
Batch distillation is a traditional and widely-used technique to produce Pisco brandy, a young spirit made from Muscat wine. It is necessary to track a given ethanol composition in the distillate in ...order to obtain a reproducible spirit with a desired aromatic profile. The use of multiple ethanol sensors represents a considerable cost, which prevents many distilleries from adopting this technology. Aiming to provide practical and affordable industrial-scale distillation control technology, we developed a soft-sensor to estimate distillate ethanol concentration on-line based on four temperature measurements in the still. The soft-sensor, calibrated with laboratory and industrial experimental data, consisted of an Artificial Neural Network and involved simple data pre-processing procedures. Simplicity and good performance were the metrics adopted for testing different algorithms and network structures. Returning mean prediction errors of ±0.6% v/v with laboratory scale distillations and ±1.6% v/v in industrial trials, the resulting accuracy of the soft-sensor is sufficient to improve standard practice and reproducibility.
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