The effect of soil and climate on the character of Sauvignon blanc wine

Cannonau variety is historically grown in a large Sardinia area (Jerzu district) and the vineyards are planted both in the plane and in the sloped hills reaching also 650 m of altitude a.s.l. Thus, in order to discover how climate, soil diversity and growing traditions could account for differences in grape and wine quality, this trial was carried out.

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.

Climate change is here. One of the main consequences is an increase in the frequency and severity of abiotic stresses which mostly occur in a combined manner. Grapevine, which grows in a large diversity of pedo-climatic conditions, has presumably evolved different mechanisms to allow this widespread adaptation. Harnessing the genetic diversity in these mechanisms will be central to the future of viticulture in many traditional wine growing areas. The interactions between the scion and the rootstock through grafting add an additional level of diversity and adaptive potential to explore.
At the physiological level, these mechanisms are related to processes such as root system development and functioning (water and nutrient uptake), interactions with the soil microbiome, gas exchange regulation, hydraulic properties along the soil-plant-atmosphere continuum, reserve storage, short and long distance signaling mechanisms and plasticity for some of these traits.

There has been a shift in modern industry to implement non-destructive and non-invasive process monitoring techniques (Helmdach et al., 2013).

The characterization of chemical compounds related with quality of grape must and wine is relevant for the viticulture and enology fields. Analytical methods used for these analyses require expensive instrumentation as well as a long sample preparation processes and the use of chemical solvents. On the other hand, near-infrared (NIR) spectroscopy technique is a simple, fast and non-destructive method for the detection of chemical composition showing a fingerprint of the sample. It has been reported the potential of NIR spectroscopy to measure some enological parameters such as alcohol content, pH, organic acids, glycerol, reducing sugars and phenolic compounds.