Observatoire Grenache en Vallée du Rhône: incidence du terroir sur certains précurseurs d’arômes et substances volatiles

Global warming due to greenhouse gases (GHG) has become a serious worldwide concern. The new EU green deal aims to achieve GHG emissions reduction by at least 55% by 2030 and a climate neutral eu economy by 2050. The deal strongly encourages GHG reducing measures at local, national and european levels. The redwine project will demonstrate the technical, economic and environmental feasibility of reducing by, at least, 31% of the CO2 eq.

The European geographical indication (GI) Brandy Italiano is exclusively reserved to brandy obtained in Italy from the distillation of wine from grapes grown and vinified in the national territory [1].

Traditional methods for identifying downy mildew in commercial vineyards are often labour-intensive, subjective, and time-consuming.

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.

Changes in bioclimatic indices in wine-growing region of Serbia are analyzed under the RCP 8.5 IPCC scenario.