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…

A multivariate approach using attenuated total reflectance mid-infrared spectroscopy to measure the surface mannoproteins and β-glucans of yeast cell walls during wine fermentations

Yeast cells possess a cell wall comprising primarily glycoproteins, mannans, and glucan polymers. Several yeast phenotypes relevant for fermentation, wine processing, and wine quality are correlated with cell wall properties. To investigate the effect of wine fermentation on cell wall composition, a study was performed using mid-infrared (MIR) spectroscopy coupled with multivariate methods (i.e., PCA and OPLS-DA). A total of 40 yeast strains were evaluated, including Saccharomyces strains (laboratory and industrial) and non-Saccharomyces species. Cells were fermented in both synthetic MS300 and Chardonnay grape must to stationery phase, processed, and scanned in the MIR spectrum.

Application of high power ultrasounds during red wine vinification

Wine color is one of the main organoleptic characteristics influencing its quality. It is of especial interest in red vinifications due to the economic resources that wineries have to invest for the extraction of the phenolic compounds responsible of wine color, compounds that are mainly located inside the skin cell vacuoles. Moreover, these phenolic compounds not only influence color but also other organoleptic properties such as body, mouthfeel, astringency and flavour. The transference of phenolic compounds from grapes to must during vinification is closely related with the type of grapes and the winemaking technique.

Influence of wood chips addition during alcoholic fermentation on wine phenolic composition

This study investigates the effect of wood chips addition during the alcoholic fermentation on the phenolic
composition of the produced wines. A series of wood chips, originating from American, French, Slavonia
oak and Acacia were added at the beginning of wine alcoholic fermentation. Besides, a mixture consisting
of 50% French and 50% Americal oak chips were added during the experimentation. The wine samples
were analyzed one month after the end of malolactic fermentation, examining various chemical
parameters such as total anthocyanins, total phenolic content, tannins combined with protein (BSA) and
ellagitannin content.

Evaluation of Polarized Projective Mapping as a possible tool for attributing South African Chenin blanc dry wine styles

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.

Analysis of the oenological potentials of different oak forests in Hungary

Like France, Hungary has many oak forests used for making barrels since many years. But if the differences between the woods of the North, the East and the South-West forests of France are well known, this is probably not the case of Hungarian forests. However taking into account the essential differences of climates and soils, differences must be significant and the general name “Hungarian oak” must not have any real meaning. We have studied precisely (determination of concentrations of volatile and non-volatile wood compounds, anatomical criteria, measurement of antioxidant capacity) of oaks collected from northeastern Hungary and others collected from the Danube valley in the northwest of the country.