Macrowine 2021
IVES 9 IVES Conference Series 9 Preliminar study of adsorption of unstable white wine proteins using zirconium oxide supported on activated alumina by atomic layer deposition method

Preliminar study of adsorption of unstable white wine proteins using zirconium oxide supported on activated alumina by atomic layer deposition method

Abstract

A common problem in wineries is haze formation after bottling, mainly caused by unstable proteins present in white wine. The most used material to eliminate these proteins is bentonite. This material effectively removes proteins, but it is very harmful to white wine since it removes all kinds of proteins and other essential compounds from wine. Zirconium oxide (ZrO2) has been shown to remove the proteins responsible for haze selectively, but ZrO2 must be modified to increase the active surface area that adsorbs the proteins. This work aims to use zirconium oxide properties to produce a porous material coated on the surface by a new impregnation technology such as atomic layer deposition (ALD), which is highly active and allows the selective removal of haze-causing proteins from white wine. Zirconium oxide is deposited on 6 mm alumina spheres by the ALD method. As a result, two modified materials (MM) are obtained and are compared with pure zirconium (ZP) and the control wine. Batch and continuous experiments are carried out, subsequently analysed for total protein content by Bradford and polysaccharide and protein content by HPLC. Preliminary results indicate that the spheres remove 10-20% of total proteins from white wine, where the content of proteins <25 kDa decreases and proteins of higher molecular weight are not affected. Pure zirconium in 3 mm discs removes twice as much protein as MM. However, zirconium content in MM is in the order of ~1% and has a lower surface area than ZP is 100% zirconium, but it has a higher active surface area. The polysaccharide content is slightly reduced, but pure zirconium removes more than MM. Therefore, we can conclude that there is a selective reduction of proteins, but this is not enough; this may be due to two aspects: the surface area of pure zirconium is higher than the modified material, and the content is also lower. Therefore, to improve the protein removal with the modified materials, it is proposed to increase the active surface area reducing the spheres’ size from the original 6 mm to 2-4 mm.

DOI:

Publication date: September 14, 2021

Issue: Macrowine 2021

Type: Article

Authors

Daniela Silva

Department of Chemical and Bioprocess Engineering, Pontificia Universidad Católica de Chile, Chile ,Fernando Salazar, Laboratorio de Fermentaciones Industriales, Escuela de Alimentos, Facultad de Ciencias Agronómica y de los Alimentos, Pontificia Universidad Católica de Valparaíso, Chile Francisco López, Departament d’Enginyeria Química, Facultat d’Enologia, Universitat Rovira i Virgili, España Néstor Escalona, Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Chile José Pérez-Correa, Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Chile

Contact the author

Keywords

haze, unstable proteins, protein stabilization, protein removal, zirconium oxide

Citation

Related articles…

Adaptation to soil and climate through the choice of plant material

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.

Rootstock regulation of scion phenotypes: the relationship between rootstock parentage and petiole mineral concentration

Grapevine is grown as a graft since the end of the 19th century. Rootstocks not only provide tolerance to Phylloxera but also ensure the supply of water and mineral nutrients to the scion. Rootstocks are an important mean of adaptation to environmental conditions, because the scion controls the typical features of the grapes and wine. However, among the large diversity of rootstocks worldwide, few of them are commercially used in the vineyard. The aim of this study was to investigate the extent to which rootstocks modify the mineral composition of the petioles of the scion. Vitis vinifera cvs. Cabernet-Sauvignon, Pinot noir, Syrah and Ugni blanc were grafted onto 55 different rootstock genotypes and planted in a vineyard as three replicates of 5 vines. Petioles were collected in the cluster zone with 6 replicates per combination. Petiolar concentrations of 13 mineral elements (N, P, K, S, Mg, Ca, Na, B, Zn, Mn, Fe, Cu, Al) at veraison were determined. Scion, rootstock and the interaction explained the same proportion of the phenotypic variance for most mineral elements. Rootstock genotype showed a significant influence on the petiole mineral element composition. Rootstock effect explained from 7 % for Cu to 25 % for S of the variance. The difference of rootstock conferred mineral status is discussed in relation to vigor and fertility. Rootstocks were also genotyped with 23 microsatellite markers. Data were analysed according to genetic groups in order to determine whether the petiole mineral composition could be related to the genetic parentage of the rootstock. Thanks to a highly powerful design, it is the first time that such a large panel of rootstocks grafted with 4 scions has been studied. These results give the opportunity to better characterize the rootstocks and to enlarge the diversity used in the vineyard.

A better understanding of the climate effect on anthocyanin accumulation in grapes using a machine learning approach

The current climate changes are directly threatening the balance of the vineyard at harvest time. The maturation period of the grapes is shifted to the middle of the summer, at a time when radiation and air temperature are at their maximum. In this context, the implementation of corrective practices becomes problematic. Unfortunately, our knowledge of the climate effect on the quality of different grape varieties remains very incomplete to guide these choices. During the Innovine project, original experiments were carried out on Syrah to study the combined effects of normal or high air temperature and varying degrees of exposure of the berries to the sun. Berries subjected to these different conditions were sampled and analyzed throughout the maturation period. Several quality characteristics were determined, including anthocyanin content. The objective of the experiments was to investigate which climatic determinants were most important for anthocyanin accumulation in the berries. Temperature and irradiance data, observed over time with a very thin discretization step, are called functional data in statistics. We developed the procedure SpiceFP (Sparse and Structured Procedure to Identify Combined Effects of Functional Predictors) to explain the variations of a scalar response variable (a grape berry quality variable for example) by two or three functional predictors (as temperature and irradiance) in a context of joint influence of these predictors. Particular attention was paid to the interpretability of the results. Analysis of the data using SpiceFP identified a negative impact of morning combinations of low irradiance (lower than about 100 μmol m−2 s−1 or 45 μmol m−2 s−1 depending on the advanced-delayed state of the berries) and high temperature (higher than 25oC). A slight difference associated with overnight temperature occurred between these effects identified in the morning.

Impact of climate change on the viticultural climate of the Protected Designation of Origin “Jumilla” (SE Spain)

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65