A combined phenolic extraction and fermentation reactor engineering model for multiphase red wine fermentation

Red wine production begins with a simultaneous fermentation and solid-phase extraction process. Red wine color and mouthfeel is the result of the extraction of phenolics from grape skins and seeds during fermentation, where extraction is a strong function of temperature and ethanol concentration. During fermentation, grape solids form a porous “cap” at the top of the fermentor, resulting in a heterogeneous fermentation system with significant temperature and concentration gradients. In this work, we present a spatial, time-variant reactor engineering model for phenolic extraction during red wine fermentation, incorporating fermentation kinetics, mass transfer, heat transfer, compressible fluid flow, and phenolic extraction kinetics. The temperature and ethanol concentration profiles predicted by this model allow for the calculation of phenolic extraction rates over the course of fermentation. Phenolic extraction predictions were validated against prior experimental data to good agreement and compared to a well-mixed model's predictions to show the utility of a spatial model over well-mixed models.     

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.     

Simultaneous saccharification and co‐fermentation of paper sludge to ethanol by Saccharomyces cerevisiae RWB222. Part II: Investigation of discrepancies between predicted and observed performance at high solids concentration

The simultaneous saccharification and co‐fermentation (SSCF) kinetic model described in the companion paper can predict batch and fed batch fermentations well at solids concentrations up to 62.4 g/L cellulose paper sludge but not in batch fermentation at 82.0 g/L cellulose paper sludge. Four hypotheses for the discrepancy between observation and model prediction at high solids concentration were examined: ethanol inhibition, enzyme deactivation, inhibition by non‐metabolizable compounds present in paper sludge, and mass transfer limitation. The results show that mass transfer limitation was responsible for the discrepancy between model and experimental data. The model can predict the value of high paper sludge SSCF in the fermentation period with no mass transfer limitation. The model predicted that maximum ethanol production of fed‐batch fermentation was achieved when it was run as close to batch mode as possible with the initial solids loading below the mass transfer limitation threshold. A method for measuring final enzyme activity at the end of fermentation was also developed in this study. Biotechnol. Bioeng. 2009; 104: 932–938. © 2009 Wiley Periodicals, Inc.     

Temperature-Dependent Kinetic Model for Nitrogen-Limited Wine Fermentations

A physical and mathematical model for wine fermentation kinetics was adapted to include the influence of temperature, perhaps the most critical factor influencing fermentation kinetics. The model was based on flask-scale white wine fermentations at different temperatures (11 to 35°C) and different initial concentrations of sugar (265 to 300 g/liter) and nitrogen (70 to 350 mg N/liter). The results show that fermentation temperature and inadequate levels of nitrogen will cause stuck or sluggish fermentations. Model parameters representing cell growth rate, sugar utilization rate, and the inactivation rate of cells in the presence of ethanol are highly temperature dependent. All other variables (yield coefficient of cell mass to utilized nitrogen, yield coefficient of ethanol to utilized sugar, Monod constant for nitrogen-limited growth, and Michaelis-Menten-type constant for sugar transport) were determined to vary insignificantly with temperature. The resulting mathematical model accurately predicts the observed wine fermentation kinetics with respect to different temperatures and different initial conditions, including data from fermentations not used for model development. This is the first wine fermentation model that accurately predicts a transition from sluggish to normal to stuck fermentations as temperature increases from 11 to 35°C. Furthermore, this comprehensive model provides insight into combined effects of time, temperature, and ethanol concentration on yeast (Saccharomyces cerevisiae) activity and physiology.     

Temperature-dependent kinetic model for nitrogen-limited wine fermentations

A physical and mathematical model for wine fermentation kinetics was adapted to include the influence of temperature, perhaps the most critical factor influencing fermentation kinetics. The model was based on flask-scale white wine fermentations at different temperatures (11 to 35 degrees C) and different initial concentrations of sugar (265 to 300 g/liter) and nitrogen (70 to 350 mg N/liter). The results show that fermentation temperature and inadequate levels of nitrogen will cause stuck or sluggish fermentations. Model parameters representing cell growth rate, sugar utilization rate, and the inactivation rate of cells in the presence of ethanol are highly temperature dependent. All other variables (yield coefficient of cell mass to utilized nitrogen, yield coefficient of ethanol to utilized sugar, Monod constant for nitrogen-limited growth, and Michaelis-Menten-type constant for sugar transport) were determined to vary insignificantly with temperature. The resulting mathematical model accurately predicts the observed wine fermentation kinetics with respect to different temperatures and different initial conditions, including data from fermentations not used for model development. This is the first wine fermentation model that accurately predicts a transition from sluggish to normal to stuck fermentations as temperature increases from 11 to 35 degrees C. Furthermore, this comprehensive model provides insight into combined effects of time, temperature, and ethanol concentration on yeast (Saccharomyces cerevisiae) activity and physiology.     

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.     

Field-flow fractionation as analytical technique for the characterization of dry yeast: correlation with wine fermentation activity

Important oenological properties of wine depend on the winemaking yeast used in the fermentation process. There is considerable controversy about the quality of yeast, and a simple and cheap analytical methodology for quality control of yeast is needed. Gravitational field flow fractionation (GFFF) was used to characterize several commercial active dry wine yeasts from Saccharomyces cerevisiae and Saccharomyces bayanus and to assess the quality of the raw material before use. Laboratory-scale fermentations were performed using two different S. cerevisiae strains as inocula, and GFFF was used to follow the behavior of yeast cells during alcoholic fermentation. The viable/nonviable cell ratio was obtained by flow cytometry (FC) using propidium iodide as fluorescent dye. In each experiment, the amount of dry wine yeast to be used was calculated in order to provide the same quantity of viable cells. Kinetic studies of the fermentation process were performed controlling the density of the must, from 1.071 to 0.989 (20/20 density), and the total residual sugars, from 170 to 3 g/L. During the wine fermentation process, differences in the peak profiles obtained by GFFF between the two types of commercial yeasts that can be related with the unlike cell growth were observed. Moreover, the strains showed different fermentation kinetic profiles that could be correlated with the corresponding fractograms monitored by GFFF. These results allow optimism that sedimentation FFF techniques could be successfully used for quality assessment of the raw material and to predict yeast behavior during yeast-based bioprocesses such as wine production.     

Kinetic model for nitrogen-limited wine fermentations.

A physical and mathematical model for wine fermentation kinetics has been developed to predict sugar utilization curves based on experimental data from wine fermentations with various initial nitrogen and sugar concentrations in the juice. The model is based on: (1) yeast cell growth limited by nitrogen; (2) sugar utilization rates and ethanol production rates proportional solely to the number of viable cells; and (3) a death rate for cells proportional to alcohol content. All but one parameter in the model can be estimated from existing data. However, experiments to find this final parameter, a constant describing cell death, indicate that cell death may not be the critical factor in determining fermentation kinetics as cell viability remains significant until sugar utilization has ceased. The model, nevertheless, predicts a transition from normal to sluggish to stuck fermentations as initial nitrogen levels decrease. It also predicts that fermentations with high initial Brix levels may go to completion when supplemented with nitrogen in the form of ammonia. Therefore, we hypothesize that the model is valid but that ethanol causes the yeast cells to become inactive while remaining viable. Experimental verification of the model has been performed using flask-scale experiments. The model has also been used to evaluate the possibility of using nitrogen or viable cell additions to avoid or correct problem (i.e., sluggish or stuck) fermentations.     

Prediction of problematic wine fermentations using artificial neural networks

Artificial neural networks (ANNs) have been used for the recognition of non-linear patterns, a characteristic of bioprocesses like wine production. In this work, ANNs were tested to predict problems of wine fermentation. A database of about 20,000 data from industrial fermentations of Cabernet Sauvignon and 33 variables was used. Two different ways of inputting data into the model were studied, by points and by fermentation. Additionally, different sub-cases were studied by varying the predictor variables (total sugar, alcohol, glycerol, density, organic acids and nitrogen compounds) and the time of fermentation (72, 96 and 256 h). The input of data by fermentations gave better results than the input of data by points. In fact, it was possible to predict 100% of normal and problematic fermentations using three predictor variables: sugars, density and alcohol at 72 h (3 days). Overall, ANNs were capable of obtaining 80% of prediction using only one predictor variable at 72 h; however, it is recommended to add more fermentations to confirm this promising result.     

Influence of red wine fermentation oenological additives on inoculated strain implantation

Pure selected cultures of Saccharomyces cerevisiae starters are regularly used in the wine industry. A survey of S. cerevisiae populations during red wine fermentations was performed in order to evaluate the influence of oenological additives on the implantation of the inoculated strain. Pilot scale fermentations (500 L) were conducted with active dry yeast (ADY) and other commercial oenological additives, namely two commercial fermentation activators and two commercial tannins. Six microsatellite markers were used to type S. cerevisiae strains. The methodology proved to be very discriminating as a great diversity of wild strains (48 genotypes) was detected. Statistical analysis confirmed a high detection of the inoculated commercial strain, and for half the samples an effective implantation of ADY (over 80 %) was achieved. At late fermentation time, ADY strain implantation in fermentations conducted with commercial additives was lower than in the control. These results question the efficacy of ADY addition in the presence of other additives, indicating that further studies are needed to improve knowledge on oenological additives’ use.     

Ethanol Production and Maximum Cell Growth Are Highly Correlated with Membrane Lipid Composition during Fermentation as Determined by Lipidomic Analysis of 22 Saccharomyces cerevisiae Strains

Optimizing ethanol yield during fermentation is important for efficient production of fuel alcohol, as well as wine and other alcoholic beverages. However, increasing ethanol concentrations during fermentation can create problems that result in arrested or sluggish sugar-to-ethanol conversion. The fundamental cellular basis for these problem fermentations, however, is not well understood. Small-scale fermentations were performed in a synthetic grape must using 22 industrial Saccharomyces cerevisiae strains (primarily wine strains) with various degrees of ethanol tolerance to assess the correlation between lipid composition and fermentation kinetic parameters. Lipids were extracted at several fermentation time points representing different growth phases of the yeast to quantitatively analyze phospholipids and ergosterol utilizing atmospheric pressure ionization-mass spectrometry methods. Lipid profiling of individual fermentations indicated that yeast lipid class profiles do not shift dramatically in composition over the course of fermentation. Multivariate statistical analysis of the data was performed using partial least-squares linear regression modeling to correlate lipid composition data with fermentation kinetic data. The results indicate a strong correlation (R² = 0.91) between the overall lipid composition and the final ethanol concentration (wt/wt), an indicator of strain ethanol tolerance. One potential component of ethanol tolerance, the maximum yeast cell concentration, was also found to be a strong function of lipid composition (R² = 0.97). Specifically, strains unable to complete fermentation were associated with high phosphatidylinositol levels early in fermentation. Yeast strains that achieved the highest cell densities and ethanol concentrations were positively correlated with phosphatidylcholine species similar to those known to decrease the perturbing effects of ethanol in model membrane systems.     

The Fitness Advantage of Commercial Wine Yeasts in Relation to the Nitrogen Concentration,Temperature, and Ethanol Content under Microvinification Conditions

The effect of the main environmental factors governing wine fermentation on the fitness of industrial yeast strains has barely received attention. In this study, we used the concept of fitness advantage to measure how increasing nitrogen concentrations (0 to 200 mg N/liter), ethanol (0 to 20%), and temperature (4 to 45°C) affects competition among four commercial wine yeast strains (PDM, ARM, RVA, and TTA). We used a mathematical approach to model the hypothetical time needed for the control strain (PDM) to out-compete the other three strains in a theoretical mixed population. The theoretical values obtained were subsequently verified by competitive mixed fermentations in both synthetic and natural musts, which showed a good fit between the theoretical and experimental data. Specifically, the data show that the increase in nitrogen concentration and temperature values improved the fitness advantage of the PDM strain, whereas the presence of ethanol significantly reduced its competitiveness. However, the RVA strain proved to be the most competitive yeast for the three enological parameters assayed. The study of the fitness of these industrial strains is of paramount interest for the wine industry, which uses them as starters of their fermentations. Here, we propose a very simple method to model the fitness advantage, which allows the prediction of the competitiveness of one strain with respect to different abiotic factors.     

Conversion of municipal solid waste to carboxylic acids using a mixed culture of mesophilic microorganisms

Waste biomass was anaerobically converted to carboxylate salts by using a mixed culture of acid-forming microorganisms. Municipal solid waste (MSW) was the energy source (carbohydrates) and sewage sludge (SS) was the nutrient source (minerals, metals, and vitamins). Four fermentors were arranged in series and solids and liquids were transferred countercurrently in opposite directions, which allows both high conversions and high product concentrations. Fresh biomass was added to Fermentor 1 (highest carboxylic acid concentration) and fresh media was added to Fermentor 4 (most digested biomass). All fermentations were performed at 40 degrees C. Calcium carbonate was added to the fermentors to neutralize the acids to their corresponding carboxylate salts. Iodoform was used to inhibit methane production and urea was added as a nitrogen source. Product concentrations were up to 25 g/L, with productivities up to 1.4 g total acid/(L liquid d). Mass balances with closure between 93% and 105% were obtained for all systems. Continuum particle distribution modeling (CPDM) was applied to correlate batch fermentation data to countercurrent fermentation data and predict product concentration over a wide range of solids loading rates and residence times. CPDM for lime-treated MSW/SS fermentation system predicted the experimental total acid concentration and conversion within 4% and 16% respectively.     

Biomass content governs fermentation rate in nitrogen-deficient wine musts

Problematic fermentations are common in the wine industry. Assimilable nitrogen deficiency is the most prevalent cause of sluggish fermentations and can reduce fermentation rates significantly. A lack of nitrogen diminishes a yeast's metabolic activity, as well as the biomass yield, although it has not been clear which of these two interdependent factors is more significant in sluggish fermentations. Under winemaking conditions with different initial nitrogen concentrations, metabolic flux analysis was used to isolate the effects. We quantified yeast physiology and identified key metabolic fluxes. We also performed cell concentration experiments to establish how biomass yield affects the fermentation rate. Intracellular analysis showed that trehalose accumulation, which is highly correlated with ethanol production, could be responsible for sustaining cell viability in nitrogen-poor musts independent of the initial assimilable nitrogen content. Other than the higher initial maintenance costs in sluggish fermentations, the main difference between normal and sluggish fermentations was that the metabolic flux distributions in nitrogen-deficient cultures revealed that the specific sugar uptake rate was substantially lower. The results of cell concentration experiments, however, showed that in spite of lower sugar uptake, adding biomass from sluggish cultures not only reduced the time to finish a problematic fermentation but also was less likely to affect the quality of the resulting wine as it did not alter the chemistry of the must.     

Yeast diversity and persistence in botrytis-affected wine fermentations

Culture-dependent and -independent methods were used to examine the yeast diversity present in botrytis-affected ("botrytized") wine fermentations carried out at high ( approximately 30 degrees C) and ambient ( approximately 20 degrees C) temperatures. Fermentations at both temperatures possessed similar populations of Saccharomyces, Hanseniaspora, Pichia, Metschnikowia, Kluyveromyces, and Candida species. However, higher populations of non-Saccharomyces yeasts persisted in ambient-temperature fermentations, with Candida and, to a lesser extent, Kluyveromyces species remaining long after the fermentation was dominated by SACCHAROMYCES: In general, denaturing gradient gel electrophoresis profiles of yeast ribosomal DNA or rRNA amplified from the fermentation samples correlated well with the plating data. The direct molecular methods also revealed a Hanseniaspora osmophila population not identified in the plating analysis. rRNA analysis also indicated a large population (>10(6) cells per ml) of a nonculturable Candida strain in the high-temperature fermentation. Monoculture analysis of the Candida isolate indicated an extreme fructophilic phenotype and correlated with an increased glucose/fructose ratio in fermentations containing higher populations of CANDIDA: Analysis of wine fermentation microbial ecology by using both culture-dependent and -independent methods reveals the complexity of yeast interactions enriched during spontaneous fermentations.     

Biomass Content Governs Fermentation Rate in Nitrogen-Deficient Wine Musts

Problematic fermentations are common in the wine industry. Assimilable nitrogen deficiency is the most prevalent cause of sluggish fermentations and can reduce fermentation rates significantly. A lack of nitrogen diminishes a yeast's metabolic activity, as well as the biomass yield, although it has not been clear which of these two interdependent factors is more significant in sluggish fermentations. Under winemaking conditions with different initial nitrogen concentrations, metabolic flux analysis was used to isolate the effects. We quantified yeast physiology and identified key metabolic fluxes. We also performed cell concentration experiments to establish how biomass yield affects the fermentation rate. Intracellular analysis showed that trehalose accumulation, which is highly correlated with ethanol production, could be responsible for sustaining cell viability in nitrogen-poor musts independent of the initial assimilable nitrogen content. Other than the higher initial maintenance costs in sluggish fermentations, the main difference between normal and sluggish fermentations was that the metabolic flux distributions in nitrogen-deficient cultures revealed that the specific sugar uptake rate was substantially lower. The results of cell concentration experiments, however, showed that in spite of lower sugar uptake, adding biomass from sluggish cultures not only reduced the time to finish a problematic fermentation but also was less likely to affect the quality of the resulting wine as it did not alter the chemistry of the must.     

Direct profiling of the yeast dynamics in wine fermentations

We present a method to directly characterize the yeast diversity present in wine fermentations by employing denaturing gradient gel electrophoresis (DGGE) of polymerase chain reaction (PCR)-amplified 26S ribosomal RNA (rRNA) genes. PCR-DGGE of a portion of the 26S rRNA gene was shown to distinguish most yeast genera associated with the production of wine. With this method the microbial dynamics in several model wine fermentations were profiled. PCR-DGGE provided a qualitative assessment of the yeast diversity in these fermentations accurately identifying populations as low as 1000 cells ml(-1). PCR-DGGE represents an attractive alternative to traditional plating schemes for analysis of the microbial successions inherent in the fermentation of wine.     

Chemometrics and visible-near infrared spectroscopic monitoring of red wine fermentation in a pilot scale

The modern wine industry needs tools for process control and quality assessment in order to better manage fermentation or bottling processes. During wine fermentation it is important to measure both substrate and product concentrations (e.g. sugars, phenolic compounds), however, the analysis of these compounds by traditional means requires sample preparation and in some cases several steps of purification are needed. The combination of visible/near-infrared (Vis/NIR) spectroscopy and chemometrics potentially provides an ideal solution to accurately and rapidly monitor physical or chemical changes in wine during processing without the need for chemical analysis. The aim of this study was to assess the possibility of combining spectral and multivariate techniques, such as principal component analysis (PCA), discriminant partial least squares (DPLS), or linear discriminant analysis (LDA), to monitor time-related changes that occur during red wine fermentation. Samples (n = 652) were collected at various times from several pilot scale fermentations with grapes from either Cabernet Sauvignon or Shiraz varieties, over three vintages (2001-2003) and scanned using a monochromator instrument (Foss-NIRSystems 6500, Silver Spring, MD) in transmission mode (400-2,500 nm). PCA was used to demonstrate consistent progressive spectral changes that occur through the time course of the fermentation. LDA using PCA scores showed that regardless of variety or vintage, samples belonging to a particular time point in fermentation could be correctly classified. This study demonstrates the potential of Vis/NIR spectroscopy combined with chemometrics, as a tool for the rapid monitoring of red wine fermentation.