The effects of calcite silicon-mediated particle film application on leaf temperature and grape composition of Merlot (Vitis vinifera L.) vines under different irrigation conditions

Il lavoro si prefigge di esaminare la propensione alla modernizzazione della viticoltura del Veneto Occidentale, letto attraverso la diffusione di forme di allevamento a sviluppo contenuto.

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.

Tannin and polysaccharide concentration and composition is important in defining the texture of red wines, but can vary due to factors such as cultivar, region, grape ripeness, viticultural practices and winemaking techniques. However, the concentration and composition of these macromolecules is dependent not only on grape tannin and polysaccharide concentration and composition, but also their extractability and, in the case of polysaccharides, their formation by yeast. Through studies into the influence of grape maturity, winemaking and sensory impacts of red grape polysaccharides, seed and skin tannins, recent research in our laboratory has shown that the processes involved in the extraction of these macromolecules from grapes and their retention in wine are very complex.

Extracellular substances (ECS) represent all molecules outside the cytoplasmic membrane, which are not directly anchored to the cell wall of microorganisms living through a planktonic or biofilm phenotype. They are the high-biomolecular-weight secretions from microorganisms (i.e. extracellular polymeric substances – EPS – proteins, polysaccharides, humic acid, nucleic acid), and the products of cellular lysis and hydrolysis of macromolecules. In addition, some high- and low-molecular-weight organic and inorganic matters from environment can also be adsorbed to the EPS. All can be firmly bound to the cell surface, associated with the EPS matrix of biofilm, or released as being freely diffusing throughout the medium.

the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.