Delaying irrigation initiation linearly reduces yield with little impact on maturity in Pinot noir

The objective of the work described here is the elaboration of a map of the different types of vineyard soils that to guide the famers in the choice of the most productive vine rootstocks and varieties. 90 vineyard soils profiles were analysed in the entire territory of the Origen Denominations of Valdepeñas. The sampling was carried out in 2018 (June to October) by making a sampling grid, followed by photointerpretation and control in the field. The studied soils can be grouped into 9 different soil types (according to FAO 2006 classification): Leptosols, Regosols, Fluvisols, Gleysols, Cambisols, Calcisols, Luvisols and Anthrosols. A map showing the soil distribution with different type of soils has been made with the ArcGIS program. Regarding to the choice of rootstock, Calcisoles are soils with a high active limestone content, so the rootstocks used in these soils must be resistant to this parameter; Luvisols are deep soils with high clay content, so they will support vigorous rootstocks. Because the cartographic units are composed of two or more subgroups, with are associated in variable proportions, 9 different soil associations have been established; Unit 1: Leptosols, Cambisols and Luvisols (80%, 15% and 5% respectively); Unit 2: Cambisols with Regosols and Luvisols (40%, 30% and 30% respectively); Unit 3: Cambisols and Gleysols with Regosols (40%, 40% and 20% respectively); Unit 4: Regosols with Cambisols, Leptosols and Calcisols (40%, 30%, 15% and 15% respectively); Unit 5: Cambisols, Leptosols, Calcisols and Regosols (25% each of them); Unit 6: Luvisols with Cambisol and Calcisols (80%, 10% and 10% respectively); Unit 7: Luvisols and Calcisols with Cambisols (40%, 40% and 20% respectively); Unit 8: Calcisols with, Cambisols and Luvisols (80%, 10% and 10% respectively); Unit 9: Anthrosols. These study allow to elaborate the first map of vineyard soils of this Protected Designation of Origin in Castilla-La Mancha.

Sixty five % of the agricultural area of the Basque Country located in the DO Ca Rioja corresponds to vineyards. More than 40% of it has an average slope greater than 10%, which makes it sensitive to erosive processes. Furthermore, it is foreseeable that extreme weather events (storms, hail, extreme heat and cold, etc.) will be favored due to climate change. Cover cropping can mitigate this risk, and therefore the objective of this work is to evaluate the impact that a vegetable cover has on the agronomic behavior of the vineyard, the quality of the grape and soil erosion. For this, a trial has been carried out with a Graciano variety vineyard with a slope between 10% -20% during the years 2020 and 2021. Conventional tillage management in the area has been compared (4-6 passes per year of tillage machinery) versus spontaneous vegetation cover management in the vineyard. This implies not tilling and allowing the grass of the land to colonize the range between the lines of vines, controlling their height through 1-3 mowing passes per year, always trying to affect the surface of the land as little as possible. The vegetative growth, yield and quality of the grape and wine was measured. Furthermore, erosion has been measured using Gerlasch boxes. The yield was lower in the second year of the trial in the cover crop treatment, but erosion was significantly reduced.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

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.

Grapevine yield has been historically overlooked, assuming a strong trade-off between grape yield and wine quality. At present, menaced by climate change, many vineyards in Southern France are far from the quality label threshold, becoming grapevine yield-gaps a major subject of concern. Although yield-gaps are well studied in arable crops, we know very little about grapevine yield-gaps. In the present study, we analysed the environmental component of grapevine yield-gaps linked to climate and soil resources in the Languedoc Roussillon. We used SAFRAN data and IGP Pays d’Oc wine yields from 2010 to 2018. We selected climate and soil indicators proving to have a significant effect on average wine yield-gaps at the municipality scale. The most significant factors of grapevine yield were the Soil Available Water Capacity; followed by the Huglin Index and the Climatic Dryness Index. The Days of Frost; the Soil pH; and the Very Hot Days were also significant. Then, we clustered geographical zones presenting similar indicators, facilitating the identification of resources yield-gaps. We discussed the number of zones with the experts of IGP Pays d’Oc label, obtaining 7 zones with similar limitations for grapevine yield. Finally, we analysed the main resources causing yield-gaps and the grapevine varieties planted on each zone. Mapping grapevine resource yield-gaps are the first stage for understanding grapevine yield-gaps at the regional scale.