Use of computational modelling for selecting adsorbents for improved fining of wine

There is a growing interest in the exploitation of vine-shoots waste, since they are often left or burned. Sánchez-Gómez et al. [1] have shown that vines-shoots aqueous extracts have significant contents of bioactive compounds, among which several polyphenols and volatiles are highlighted. Recent studied had demonstrated that the chemical composition of vine-shoots is enhanced when vine-shoots are toasted
[2,3]. The application of vegetable products in the vineyards has led to significant changes towards a more “Sustainable Viticulture”. An innovative foliar application for Airén vine-shoot extracts have been carried out to the vineyard. It has been shown that they act as grape biostimulants, improving certain wine quality characteristics [4].

Polysaccharides and more specifically pectins, make up a significant portion of the cell wall material of the plant cells including the grapes. During the fruit ripening the associated softening is related to the breakdown of the cell wall polysaccharides. During this process, it is expected that polysaccharides that are soluble in red wine will be formed influencing its texture. Anthocyanins are responsible for the wine color and tannins for the astringency, body and bitterness of the wine. In the skins, these compounds are located in the cell vacuoles and the barrier that conditions their extractability is the skin cell wall that may determine the mechanical resistance, the texture and the ease of processing berries. The aim of this work was study the evolution of the polysaccharides and the anthocyanin and tannin extractability during the ripening period in Cabernet Sauvignon grapes, trying to correlate these variables.

The color of a red wine is one of the most important parameters of its quality, giving much information on its status, such as the grape variety used or the winemaking style. As the result of a complex equilibrium between different forms of anthocyanins and polymerization reactions which occur over the course of time, color can also serve as an indication of a wines’ age. For this purpose the “chemical age” i and ii indexes have been introduced by Somers in 1977. The chemical age index i measures the color absorbance after the addition of acetaldehyde while chemical index ii provides an indication of how much of the total red pigments are resistant to SO2 bleaching.

Must oxidation is a complex process involving multiple enzymatic transformations, including the oxidation of phenolics containing an ortho-diphenol function. The latter process has a primary influence on wine aroma characteristics and stability, due to the central role of ortho-diphenols in the non-enzymatic oxidative reactions taking place during winemaking and in finished wine. Although oxidation of must is traditionally avoided, in recent years its contribution to wine quality has been revisited, and in some cases improvements to wine aroma have been observed with the application of controlled must oxidation. Nowadays there is a great interest in the wine industry towards the identification of specific markers or patterns to characterize and classify the response of grape must to oxidation.

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.