Phenolic extraction is a critical part of red wine making. Though empirical models of phenolic extraction kinetics exist, the current level of mechanistic understanding does not allow for accurate predictions. In this work, we propose a mechanistic model for the extraction of phenolics from grape skins and seeds as a function of temperature and ethanol. This model examines the release of phenolics, the adsorption of phenolics onto grape material, and the disappearance of anthocyanins from solution. Additionally, we performed epifluorescence microscopy to explore our finding that seed tannins’ release rate appears independent of concentration, and found that the grape seed appears to ablate over fermentation. We also determined the activation energy of anthocyanin disappearance, in good agreement with similar systems. The proposed model results in an excellent fit, and increases the understanding of phenolic extraction and the ability to predict and optimize product outcome in red wine making.

Desorption of proanthocyanidins (PA) from grape cell wall material (CWM) was investigated in solutions of varying ethanol concentrations and increasing temperature. The results reveal the reversibility of PA-CWM interactions and the role that temperature and ethanol concentration play in the extent of PA desorption. Sequentially raising temperature from 15 to 35 °C resulted in desorption of up to 48% of the initial adsorbed PA. A comparison to a phenolic extraction model showed significant differences between the predicted and actual amount of PA that desorbed from the CWM. This suggests that the initial conditions of temperature and ethanol concentration must be considered when estimating PA extraction in red wine production. Under typical winemaking conditions, a significant amount of PA may be irreversibly adsorbed if exposed to CWM at low temperature (i.e., cold soak). A compositional analysis suggests the selective desorption of large molecular weight PA from CWM under all experimental conditions. Additionally, a preferential desorption of skin-derived PA over seed-derived PA was noted in the absence of ethanol.

The quantitative and qualitative impacts of anthocyanins on proanthocyanidin adsorption to grape-derived cell wall material were investigated in fifteen unique systems of varying temperatures, ethanol concentrations, and proanthocyanidin concentrations. Proanthocyanidin solutions were exposed to cell wall material and monitored for changes in concentration over 24 h. Increases in both temperature and ethanol resulted in a larger retention of proanthocyanidins in solution and typically faster adsorption kinetics. Analysis of the solution after exposure to cell wall revealed a significant reduction in the molecular weight of proanthocyanidins present in solution, suggesting that anthocyanins do not alter a previously described mechanism of preferentially binding large molecular weight molecules. Additionally, a reduction in polymeric pigment abundance was noted in most conditions, suggesting rapid formation of polymeric pigment in the model solution and preferential adsorption of the polymeric pigment to cell wall material. Compared to a previous study of proanthocyanidin adsorption in the absence of anthocyanins, a significantly larger percentage of proanthocyanidin material was lost via adsorption—up to 70% of available material. In a winemaking context, this may suggest a preferential loss of polymeric pigment via adsorption to cap cell wall material compared to non-pigmented proanthocyanidins and free anthocyanins.

A key first step in the production of beer is the mashing process, which enables the solubilization and subsequent enzymatic conversion of starch to fermentable sugars. Mashing performance depends primarily on temperature, but also on a variety of other process parameters, including pH and mash thickness (known as the “liquor-to-grist” ratio). This process has been studied for well over 100 years, and yet essentially all predictive modeling efforts are alike in that only the impact of temperature is considered, while the impacts of all other process parameters are largely ignored. A set of statistical and mathematical methods collectively known as Response Surface Methodology (RSM) is commonly applied to develop predictive models of complex processes such as mashing, where performance depends on multiple parameters. For this study, RSM was used to design and test a set of experimental mash conditions to quantify the impact of four process parameters—temperature (isothermal), pH, aeration, and the liquor-to-grist ratio—on extract yield (total and fermentable) and extract composition in order to create a robust, yet simple, predictive model. In contrast to previous models of starch hydrolysis in a mash, a unique aspect of the model developed here was the quantification of significant parameter interaction effects, the most notable of which was the interaction between temperature and mash thickness (i.e., the liquor-to-grist ratio). This interaction had a sizeable impact on important mash performance metrics, such as the total extract yield and the fermentability of the resultant wort. The development of this model is of great future utility to brewery processing, as it permits the multi-parameter optimization of the mashing process.

White wine fermentations are typically performed in an entirely batchwise manner, with yeast nutrients only added at the beginning of fermentation. This leads to slow (2+ weeks) fermentation cycle times, with large capital expenditures required to increase winery processing capacity. Prior attempts to speed fermentations via increasing temperature have resulted in unpalatable wine, and continuous fermentation processing is uneconomical and impractical in the winery setting. In this work, we measured yeast nutrient consumption as a function of fermentation progression at the 300 mL scale, and from this derived an equation to optimize yeast nutrient concentration as a function of fermentation progression. These findings were applied at the pilot scale in 150 L fermentors, which resulted in a 60% cycle time reduction versus “best practices” control fermentations. The resultant wines were compared via GC-MS as well as by a trained sensory panel. Organoleptic analysis found statistically significant, but overall, small differences in sensory characteristics between the control and process intensified wines. This intensified fermentation process shows great promise for fermented beverage producers wishing to maximize equipment utilization and debottleneck wineries or other beverage fermentation facilities.