Effects of mesoclimate on the yield, quality and phenolic maturity of Grenache

Effects of climate change on viticulture systems and winemaking processes are being felt across the world. The IPCC 6thAssessment Report concluded widespread and rapid changes have occurred, the scale of recent changes being unprecedented over many centuries to many thousands of years. These changes will continue under all emission scenarios considered, including increases in frequency and intensity of hot extremes, heatwaves, heavy precipitation and droughts. Wine companies need tools and models allowing to peer into the future and identify the moment for intervention and measures for mitigation and/or avoidance. Previously, we presented conceptual guidelines for a 5-stage framework for defining adaptation strategies for wine businesses. That framework allows for direct comparison of different solutions to mitigate perceived climate change risks. Recent global climatic evolution and multiple reports of severe events since then (smoke taint, heatwave and droughts, frost, hail and floods, rising sea levels) imply urgency in providing effective tools to tackle the multiple perceived risks. A coordinated drive towards a higher level of resilience is therefore required. Recent publications such as the Australian Wine Future Climate Atlas and results from projects such as H2020 MED-GOLD inform on expected climate change impacts to the wine sector, foreseeing the climate to expect at regional and vineyard scale in coming decades. We present examples of practical application of the Climate Change Adaptation Framework (CCAF) to impacts affecting wine production in two wine regions: Barossa (Australia) and Douro (Portugal). We demonstrate feasibility of the framework for climate adaptation from available data and tools to estimate historical climate-induced profitability loss, to project it in the future and to identify critical moments when disruptions may occur if timely measures are not implemented. Finally, we discuss adaptation measures and respective timeframes for successful mitigation of disruptive risk while enhancing resilience of wine systems.

Marselan wines have an unusual high proportion of seed derived tannins from grapes having high proportions of skins, which are rich in tannins. But the causes behind this characteristic have not yet been identified. In vintage 2023 wines were made at experimental scale (9 kg by experimental unit) from Arinarnoa, Marselan and Tannat Vitis vinifera grape cultivars by traditional maceration, and by techniques aimed to increase the wine content in skin derived tannin: addition of extraction enzymes, addition at vatting of grape-skin enological tannins, or by extended maceration, known to increase the seed derived tannin contents of wines. Macerations were of 7 days, except in the extended macerations that were of 15 days.

In a context of reducing herbicide use, the most part of French vineyards are developing permanent grass cover crops on inter-rows alleys, while under the row chemical weeding remains the general case. The setting up of a controlled grass cover crop under the vine row could be a complementary alternative to mechanical weeding – which one is very restrictive – interesting from a technical and economical point of view. The present study aimed at assessing agronomic impacts of grass cover crop under the row in different climatic conditions and production objectives.

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

The AOC Saint-Emilion, one of the most prestigious in Bordeaux, is located on the right bank of the Dordogne upstream from Libourne. The vineyard is planted on Tertiary (Oligocene) and Quaternary geological formations, on which very varied soils have developed. Numerous studies have taken account of this heterogeneity and made it possible to better understand the functioning and viticultural potential of these soils (Duteau et al. 1981, Van Leeuwen, 1991).