Macrowine 2021
IVES 9 IVES Conference Series 9 Use of computational modelling for selecting adsorbents for improved fining of wine

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

Abstract

The occurrence of faults and taints in wine, such as those caused by microbial spoilage or various taints, have resulted in significant financial losses to wine producers. The wine industry commits significant financial resources towards fining and taint removal processes each year. Fining involves the addition of one or more adsorptive substrates to juice or wine to bind certain components, thus reducing their concentration [1]. However, these processes are often not selective and can also remove desirable flavour and aroma compounds. Computational modelling techniques have not previously been exploited by the wine sector but have been used in other fields to predict the behaviour of target compounds with selected substrates. This study aimed to better elucidate the binding interactions between wine components (both desirable and undesirable) and common adsorbents through computational modelling and laboratory scale fining trials in order to improve the selection of adsorbents for specific fining or taint removal applications. The binding energies for a range of volatile compounds associated with common wine faults and taints, including guaiacol, 4-methylguaiacol, cresols and syringol (smoke taint), 4-ethylguaiacol and 4-ethylphenol (Brettanomyces spoilage), 3-isobutyl-2-methoxypyrazine (IBMP; ladybird taint), geosmin and methylisoborneol (fungal taint) and trichloroanisole (cork taint), as well as volatiles associated with varietal aroma and flavour, including esters, C13-norisoprenoids and monoterpenes, or oak maturation, including cis- and trans-oak lactone, vanillin and eugenol, were calculated against a range of adsorbent substrates, including bentonite, polyvinylpolypyrrolidone (PVPP) and α-cyclodextrin (α-CD) using the density functional theory as implemented in FHI-aims, a software package for atomic scale materials modelling. The computational data suggests that α-CD could be used to selectively remove a variety of different molecules but it is less suitable for removal of IBMP. In fact, the strongest interaction comes from materials with strong hydrogen bonding systems, such as eugenol and vanillin. PVPP is a purely hydrogen-bonding sponge. It actively excludes substrates which do not hydrogen bond very well; thus, it has a very high selectivity for vanillin, and other molecules with pendant hydroxyl functionalities in a non-sterically limited environment (such as certain phenols). This presentation will comprise results from computational modelling experiments and fining experiments conducted in the laboratory. Quantitative chemical analysis of wine volatiles before and after fining treatment enables predictions based on computational approaches to be evaluated.

1. Castellari, M., Versari, A., Fabiani, A., Parpinello, G.P. and Galassi, S. (2001) Removal of ochratoxin A in red wines by means of absorption treatments with commercial fining agents. Journal of Agricultural and Food Chemistry, 49, 3917–3921.

Publication date: May 17, 2024

Issue: Macrowine 2016

Type: Article

Authors

Julie Culbert*, Christopher Hendon, Kerry Wilkinson

*University of Adelaide

Contact the author

Tags

IVES Conference Series | Macrowine | Macrowine 2016

Citation

Related articles…

Dissecting the polysaccharide‐rich grape cell wall matrix during the red winemaking process, using high‐throughput and fractionation methods

Limited information is available on grape wall-derived polymeric structure/composition and how this changes during fermentation. Commercial winemaking operations use enzymes that target the polysaccharide-rich polymers of the cell walls of grape tissues to clarify musts and extract pigments during the fermentations. In this study we have assessed changes in polysaccharide composition/ turnover throughout the winemaking process by applying recently developed cell wall profiling approaches to both wine and pomace polysaccharides. The methods included gas chromatography for monosaccharide composition (GC-MS), infra-red (IR) spectroscopy and comprehensive microarray polymer profiling
(CoMPP) using cell wall probes.

Impact of varying ethanol and carbonation levels on the odor threshold of 1,1,6-trimethyl-1,2-dihydronaphtalene (petrol off-flavor) and role of berry size and Riesling clones

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.

Analysis of voltammetric fingerprints of different white grape musts reveals genotype-related oxidation patterns

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.

Full automation of oenological fermentations and its application to the processing of must containing high sugar or acetic acid concentrations

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

Elicitors used as a tool to increase stilbenes in grapes and wines

The economic importance of grapevine as a crop plant makes Vitis vinífera a good model system to study the improvement of the nutraceutical properties of food products (Vezulli et al. 2007). Stilbenes in general, and trans-resveratrol in particular, have been reported to be responsible for various beneficial effects. Resveratrol´s biological properties include antibacteria and antifungal effects, as well as cardioprotective, neuroprotective and anticâncer actions (Guerrero et al. 2010 ). Stilbenes can be induced by biotic and abiotic elicitors since they are phytoalexins (Bavaresco et al. 2001).