Macrowine 2021
IVES 9 IVES Conference Series 9 Macrowine 9 Macrowine 2021 9 Chemical diversity of 'special' wine styles: fortified wines, passito style, botrytized and ice wines, orange wines, sparkling wines 9 Determination of target compounds in cava quality using liquid chromatography. Application of chemometric tools in data analysis

Determination of target compounds in cava quality using liquid chromatography. Application of chemometric tools in data analysis

Abstract

According to the Protected Designation of Origin (PDO), Cava is protected in the quality sparkling wines made by the traditional Champenoise method were the wine realize a second fermentation inside the own bottle1. Geographical and human peculiarities of each bottle are the main way for the final quality2. The aim of this study is to find correlations and which target compounds are the most representative of the quality of two different grape varieties, Pinot Noir and Xarel·lo. The quality of these two types of grapes is being studied for each variety by a previous classification of the vineyard made by the company who provided the samples (qualities A,B,C,D, being A the better one and D the worst one). The target compounds studied are organic acids and polyphenols. The methodology for the determination of organic acids is HPLC-UV/vis and for some of them the enzymatic methodology. For polyphenols is HPLC-UV/vis. Samples of musts, monovarietal wines, stabilized blended wines and cavas with 3 and 7 months of second fermentation are being studied. Data will be treated using boxplots to see the predominant compounds and chemometric tools such as Principal Component Analysis (PCA) to establish correlations and Partial Least Squares (PLS) for predictions between samples. By the moment, results in Pinot Noir grape variety shown that quality A present high levels of tartaric, malic, citric and succinic acids in musts and wines and there is observed a decrease in citric acid and an increase of succinic acid during the second fermentation. The results of Xarel·lo grape variety shown lower levels of tartaric acid than in Pinot Noir grape variety. Nevertheless, quality A present high amounts of this acid. Qualities A and B present similar levels of malic acid but in quality A slightly higher. For citric acid no noticeable changes are observed from must to cava of 7 month. Quality A present higher levels of succinic acid. Lower values of malic acid and higher values of lactic acid are observed in qualities C and D, due to, the malolactic fermentation in both varieties and there is observed a decrease of tartaric acid from wines to cavas, due to, the tartaric stabilization. In conclusion, malic and tartaric acids are the most important compounds in the quality of cavas. This involves that the futures cavas will be able to age more time.

DOI:

Publication date: September 16, 2021

Issue: Macrowine 2021

Type: Article

Authors

Anaïs Izquierdo Llopart 

Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain.,Javier, SAURINA, Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain.

Contact the author

Keywords

cava, wine quality, grape varieties, pinot noir, xarel·lo, vineyards, second fermentation, malolactic fermentation, organic acids, polyphenols, hplc, chemometric tools

Citation

Related articles…

Heatwaves and grapevine yield in the Douro region, crop model simulations

Heatwaves or extreme heat events can be particularly harmful to agriculture. Grapevines grown in the Douro winemaking region are particularly exposed to this threat, due to the specificities of the already warm and dry climatic conditions. Furthermore, climate change simulations point to an increase in the frequency of occurrence of these extreme heat events, therefore posing a major challenge to winegrowers in the Mediterranean type climates. The current study focuses on the application of the STICS crop model to assess the potential impacts of heatwaves in grapevine yields over the Douro valley winemaking region. For this purpose, STICS was applied to grapevines using high-resolution weather, soil and terrain datasets over the Douro. To assess the impact of heatwaves, the weather dataset (1989-2005) was artificially modified, generating periods with anomalously high temperatures (+5 ºC), at certain onset dates and with specific durations (from 5 to 9 days). The model was run with this modified weather dataset and results were compared to the original unmodified runs. The results show that heatwaves can have a very strong impact on grapevine yields, strongly depending on the onset dates and duration of the heatwaves. The highest negative impacts may result in a decrease in the yield by up to -35% in some regions. Despite some uncertainties inherent to the current modelling assessment, the present study highlights the negative impacts of heatwaves on viticultural yields in the Douro region, which is critical information for stakeholders within the winemaking sector for planning suitable adaptation measures.

Frost risk projections in a changing climate are highly sensitive in time and space to frost modelling approaches

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.

Short-term relationships between climate and grapevine trunk diseases in southern French vineyards

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

A multidisciplinary approach to evaluate the effects of the training system on the performance of “Aglianico del Vulture” vineyards

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

A predictive model of spatial Eca variability in the vineyard to support the monitoring of plant status

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...