Color stabilization properties of oenological tannins

Vineyard nutrient management is crucial for reaching production-specific quality standards, yet timely evaluation of nutrient status remains challenging. The existing sampling protocol of collecting vine tissue (leaves and/or petioles) at bloom or veraison is time-consuming. Additionally, this sampling practice is too late for in-season fertilizer applications (e.g. N is applied well before bloom). Therefore alternative early-season protocols are necessary to predict the vine nutrient demand for the upcoming season. The main goals of this project are to 1) optimize existing tissue sampling protocols; 2) determine the amount of nutrients removed at the end of the growing season.

Increasing wildfire frequency in the United States has led to the indirect impact of smoke in vineyards, affecting grape quality and wine sensory attributes, commonly called “smoke taint”.

Wine lees can be a good source of yeast mannoproteins for both food and wine applications [1,2]. However, mannoprotein extraction from wine lees has not yet been scaled up to an industrial scale, mainly because of the limited cost-effectiveness ratio of the methods employed at the laboratory scale [2].

1,1,6-trimethyl-1,2-dihydronaphtelene (TDN) evokes the odor of “petrol” in wine, especially in the variety Riesling. Increasing UV-radiation due to climate change intensifies formation of carotenoids in the berry skins and an increase of TDN-precursors1. Exploring new viticultural and oenological strategies to limit TDN formation in the future requires precise knowledge of TDN thresholds in different matrices. Thresholds reported in the literature vary substantially between 2 µg/L up to 20 µg/L2,3,4 due to the use of different methods. As Riesling grapes are used for very different wine styles such as dry, sweet or sparkling wines, it is essential to study the impact of varying ethanol and carbonation levels.

This study is aimed to develop a complete tool for the winemaker with, complete and targeted “winemaking recipes” that can be adapted to criteria set by the winemaker, such as: grape variety, grape health status, degree of ripening, desired wine, redox status throughout the alcoholic fermentation.
To get such aim, specific sets of experiments using red grape juices from different varieties (Nebbiolo, Barbera, Pinot noir, etc.) collected at different technological and phenolic maturity points, will be held with “automatized 4.0 tanks” equipped with sensors for measuring: redox potential, dissolved oxygen, relative density, temperature, and color in order to collect a sufficient amount of data preparatory to the creation of operating models in the most widely winemaking situations in which the automatized 4.0 tanks “will be able to independently respond” with the right corrective actions (opening/closing aeration valve, execution/block pumping overs , etc.) if the key parameters exceed the limits of the recommended ranges set in the selected recipe.