Evaluation de différents clones du Chardonnay pendant la maturation dans un terroir viticole du Friuli-Venezia Glulia (Nord-Est de l’Italie)

Seven plots located in the commune of Montigny-lès-Arsures (Jura, 39), planted with grapevine varieties Trousseau and Savagnin, were chosen for a study of soil pits and a distribution of major and trace chemical elements in soils and wines. It was shown that the mineral matrix of the soil reflects the geological substratum and the sub-surface alteration process, while the organic soil matrix depends on agro-viticultural practices.

The ongoing climate change implies an increasing mean air temperature, which is signified by weather extremes or sudden changes between drought and local heavy rainfalls. These changing conditions are especially challenging for the established grapevine varieties growing under cool climate conditions due to an increased risk for fungal diseases like downy mildew (DM) and Botrytis bunch rot (BBR) as well as for grape sunburn. To meet that demand, the scope of most grapevine breeding programs is the selection of mildew fungus-resistant and climatic adapted grapevines with balanced, healthy yield and outstanding wine quality.

The chemical composition of grape berries at harvest is one of the most important factors that should be considered to produce high quality wines. Among the different chemical classes which characterize the grape juice, the polyphenolic compound, such as flavonoids, contribute to the final taste and color of wines. Recently, an innovative non-destructive method, based on chlorophyll fluorescence, was developed to estimate the phenolic maturity of red grape varieties through the evaluation of anthocyanins accumulated in the berry skin. To date, only few data are available about the application of this method on white grape varieties.

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.

Agriculture plantations are complex systems whose performance critically depends on the execution of several types of tasks with precise timing and efficiency to respond to different external factors. This is particularly true for orchards like vineyards, which need to be strictly monitored and regulated, as they are sensitive to diverse types of pests, and climate conditions. In these environments, managing and optimally scheduling the available work force and resources is not trivial and is usually done by teams of senior managers based on their experience. In this regard, having a baseline schedule could help them in the decision process and improve their results, in terms of time and resources spent.