Towards a relationship between institutional clonal selection, mass selection and private clonal selection of grapevine cultivars

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

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.

Traditional viticulture areas have experienced in the last decades an intensification of field practices, linked to an increased use of fertilisers and phytosanitary products, and to a more intensive mechanization and uniformization of the landscape. This change in management has sometimes led to higher rates of soil erosion andloss of soil structure, fertility decline, groundwater contamination, and to an increased pressure of pests and diseases. Additionally, intensification usually leads to a simplification of landscapes, of particular concern in prestigious wine grape regions where the economical revenue encourages the conversion of land use from natural habitats to high value wine grape production. To revert this trend, it is necessary that growers implement actions that promote biodiversity in their vineyards. The aim of this study is to assess the impact of the implementation of cover crops, vegetational corridors, dry stone walls and vineyard biodiversity hotspots estimated through the study of arthropods. The work has been carried out in four vineyards in Rioja Alavesa belonging to Ostatu winery, where these infrastructures were implemented in 2020. The presence and diversity of arthropods was studied by capturing them at different times in the season and at different distances from the infrastructure using pit-fall traps in the soil and yellow, white and blue chromatic traps at the canopy level. This is a preliminary study in which all adult insects were sorted to the taxonomic level of order and Coleoptera were classified to morphospecies. The results obtained show that there is a relationship between the basic characteristics of the vineyard and the arthropods captured, with a positive effect, although also dependent on the vineyard, of the presence of infrastructure.

Serbian autochthonous vine varieties Smederevka (for white wines) and Prokupac (for rosé and red wines) are the primary representatives of typical characteristics of wines and terroir of numerous wine-growing areas in Serbia. In the past, these varieties were the leading vine varieties, however, as the result of globalization of winemaking and the trend of consumption of wines from widely prevalent vine varieties, they were replaced by introduced international varieties. Smederevka and Prokupac vine varieties are characterized by later time of grape ripening, and relative sensitivity to low temperatures. Climate conditions can be a restrictive factor for production of high-quality grapes and wine and for the spatial spreading of these varieties in hilly continental wine-growing areas.
This paper focuses on the spatial analysis of changes of main climate parameters, in particular, analysis of viticultural bioclimatic indices that were determined for the purposes of viticulture zoning of wine-growing areas in the period 1961-2010, and those same parameters determined for the current, that is, referential climate period (1988-2017). Results of the research, that is, analysis of climate changes indicate that the majority of examined climate parameters in the Oplenac wine-growing district improved from the perspective of Smederevka and Prokupac vine varieties. These studies of climate conditions indicate that changes of analyzed climate parameters, that is, bioclimatic indices will be favorable for cultivation of varieties with later grape ripening times and those more sensitive to low temperatures, such as the autochthonous vine varieties Smederevka and Prokupac, therefore, it is recommended to producers to more actively plant vineyards with these varieties in the territory of the Oplenac wine-growing district.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.