Influenza dei fattori dell’ambiente sulla risposta della pianta, e caratteristiche dell’uva della cv tannat prodotta in vigneti di tre zone climatiche dell’Uruguay

Mediterranean viticulture is increasingly exposed to more frequent extreme conditions such as heat waves. These extreme events co-occur with low soil water content, high air vapor pressure deficit and high solar radiant energy fluxes and result in leaf and berry sunburn, lower yield, and berry quality, which is a major constraint for the sustainability of the sector. Grape growers must find ways to proper and effectively manage heat waves and extreme canopy and berry temperatures. Irrigation to keep soil moisture levels and enable adequate plant turgor, and convective and evaporative cooling emerged as a key tool to overcome this major challenge. The effects of irrigation on soil and plant water status are easily quantifiable but the impact of irrigation on soil and canopy temperature and on heat convection from soil to cluster zone remain less characterized. Therefore, a more detailed quantification of vineyard heat fluxes is highly relevant to better understand and implement strategies to limit the effects of extreme weather events on grapevine leaf and berry physiology and vineyards performance. Low-cost sensor technologies emerge as an opportunity to improve monitoring and support decision making in viticulture. However, validation of low-cost sensors is mandatory for practical applicability. A two-year study was carried in a vineyard in Alentejo, south of Portugal, using low-cost thermal cameras (FLIR One, 80×60 pixels and FLIR C5, 160×120 pixels, 8-14 µm, FLIR systems, USA) and pocket thermohygrometers (Extech RHT30, EXTECH instruments, USA) to monitor grapevine and soil temperatures. Preliminary results show that low-cost cameras can detect severe water stress and support the evaluation of vertical canopy temperature variability, providing information on soil surface temperature. All these thermal parameters can be relevant for soil and crop management and be used in decision support systems.

In wine grape production, canopy management practices are applied to control the source-sink balance and improve the cluster microclimate to enhance berry composition. The aim of this study was to identify the optimal ranges of berry solar radiation exposure (exposure) for upregulation of flavonoid biosynthesis and thresholds for their degradation, to evaluate how canopy management practices such as leaf removal, shoot thinning, and a combination of both affect the grapevine (Vitis vinifera L. cv. Cabernet Sauvignon) yield components, berry composition, and flavonoid profile under context of climate change. First experiment assessed changes in the grape flavonoid content driven by four degrees of exposure. In the second experiment, individual grape berries subjected to different exposures were collected from two cultivars (Cabernet Sauvignon and Petit Verdot). The third experiment consisted of an experiment with three canopy management treatments (i) LR (removal of 5 to 6 basal leaves), (ii) ST (thinned to 24 shoots per vine), and (iii) LRST (a combination of LR and ST) and an untreated control (UNT). Berry composition, flavonoid content and profiles, and 3-isobutyl 2-methoxypyrazine were monitored during berry ripening. Although increasing canopy porosity through canopy management practices can be helpful for other purposes, this may not be the case of flavonoid compounds when a certain proportion of kaempferol was achieved. Our results revealed different sensitivities to degradation within the flavonoid groups, flavonols being the only monitored group that was upregulated by solar radiation. Within different canopy management practices, the main effects were due to the ST. Under environmental conditions given in this trial, ST and LRST hastened fruit maturity; however, a clear improvement of the flavonoid compounds (i.e., greater anthocyanin) was not observed at harvest. Methoxypyrazine berry content decreased with canopy management practices studied. Although some berry traits were improved (i.e. 2.5° Brix increase in berry total soluble solids) due to canopy management practices (ST), this resulted in a four-fold increase in labor operations cost, two-fold decrease in yield with a 10-fold increase in anthocyanin production cost per hectare that should be assessed together as the climate continues to get hot.

Water deficit is one of the most important effects of climate change able to affect agricultural sectors. In general, it determines a reduction in biomass production, and for some plants, as in the case of grapevine, it can endorse fruit quality. The monitoring and management of plant water stress in the vineyard

Viticulture is entangled with weather and climate. Therefore, areas currently suitable for grape production can be challenged by climate change. Winegrowers in Italy already experiences the effect of climate change, especially in the form of warmer growing season, more frequent drought periods, and increased frequency of weather extremes.
The aim of this study is to investigate the impact of climate variability and change on grape yield in Italy to provide winegrowers the information needed to make their business more sustainable and resilient to climate change. We computed a specific range of bioclimatic indices, selected by the International Organisation of Vine and Wine (OIV), and correlated them to grape yield data. We have worked in collaboration with some wine consortiums in northern and central Italy, which provided grape yield data for our analysis.
Using climate variables from the E-OBS dataset we investigate how the bioclimatic indices changed in the past, and the impact of this change on grape productivity in the study areas. The climate impact on productivity is also investigated by using high-resolution convection-permitting models (CPMs – 2.2 horizontal resolution), with the purpose of estimating productivity in future emission scenarios. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of small-scale processes and features, explicitly resolve deep convection, and show an improved representation of extremes. In our study, we also compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to assess the added value of high-resolution models for impact studies. Further development of our study will lead to assessing the future suitability for vine cultivation and could lead to the construction of a statistical model for future projection of grape yield.

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.