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IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Optimization and validation of a fully automated HS-SPME method for determination of VCCs and its application in wines submitted to accelerated ageing

Optimization and validation of a fully automated HS-SPME method for determination of VCCs and its application in wines submitted to accelerated ageing

Abstract

Wine aroma is a complex gaseous mixture composed of various compounds; some of these molecules derive directly from the grapes while most of them are released and synthetized during fermentation or are due to ageing reactions. Among the latter class of compounds, carbonyls are the principal products of oxidation reactions which take place during the storing time. Volatile carbonyl compounds (VCCs) are related to aromatic nuances of vanilla, caramel, butter, honey, potato, orange, lemon, violets, cider and plum, which are pleasant scents characteristics of oxidized wines. However, apart from cases where it is a deliberate process, oxidation is commonly undesired and the presence of a relevant content of carbonyls is related to aroma defects. Because of that, monitoring the concentration of VCCs could be added as a quality control for the evaluation of a complete fermentation, correct winemaking style, and proper bottling and storage. In this research an HS-SPME method1 was optimized and validated with the aim to be used as a tool to achieve this goal. The use of a solvent-free extraction allowed to maximize the coherence to the Green Analytical Chemistry principles with a simultaneous achievement in performance, reliability and robustness. In this method, all sample preparation steps were automated using the autosampler minimizing the human time consumption to enhance the scalability to routine analysis. As many as 46 VCCs (mainly linear aldehydes, Strecker aldehydes, unsaturated aldehydes, ketones, and many other) were the analytes under investigation. All compounds showed a good linearity spanning from approximately 0.1 to 100 µg/L (R2>0.99). Intra-day and 5 days inter-days repeatability showed an RSD

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Article

Authors

Piergiovanni Maurizio1, Carlin Silvia2, Lotti Cesare2, Vhrovsek Urska2 and Mattivi Fulvio1,2

1Center Agriculture Food Environment (C3A), University of Trento, via Edmund Mach 1, San Michele all’Adige (TN) Italy
2Center Research and Innovation, Edmund Mach Foundation, Italy3Affiliation of the third 

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Carbonyls, oxidation, accelerated ageing, HS-SPME, quality control

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IVAS 2022 | IVES Conference Series

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Effect of one-year cover crop and arbuscular mycorrhiza inocululation in the microbial soil community of a vineyard

The microbial composition of the soil is an important factor to consider in viticulture, since its influence on the “terroir” and on the organoleptic properties of the wine have been demonstrated. Different agronomic techniques have the potential to modify the composition and functionality of the soil microbial community. Maintaining green covers is known to increase soil microbial diversity. The direct application of inoculum of beneficial microorganisms to the soil has also been used to increase their abundance. However, the environmental conditions of each site seem to have a determining weight in the result of these practices. In this study, we compared the effect on the microbial community of a cover crop with legumes in autumn and the inoculation of grapevines with commercial inoculum bases on Rhizophagus irregularis and Funeliformis mosseae in the previous spring. The study has been carried out in a vineyard in Binissalem, Mallorca, Spain. After applying the treatments, we will analyze the soil microbial communities using the data obtained from Illumina amplification of soil DNA from the 16S and ITS regions to analyze bacteria and fungi community, respectively. In addition, we will record the physicochemical characteristics of the soil at each sampling point. The result showed that agronomic management, in the short term, has less influence than soil characteristics on the composition of the soil microbiome. With these results, we can conclude that in a vineyard, agricultural techniques should focus on improving the characteristics of the soil to improve the biodiversity of the soil microbiota.

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.

Better understand the soil wet bulb formation with subsurface or aerial drip irrigation in viticulture

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IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Optimization and validation of a fully automated HS-SPME method for determination of VCCs and its application in wines submitted to accelerated ageing

Optimization and validation of a fully automated HS-SPME method for determination of VCCs and its application in wines submitted to accelerated ageing

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Publication date: June 23, 2022

Issue: IVAS 2022

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Co-design and evaluation of spatially explicit strategies of adaptation to climate change in a Mediterranean watershed

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

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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