Integrative study of Vitis biodiversity for next-generation breeding of grapevine rootstocks 

Plant roots fulfil important functions as they are responsible for the acquisition of water and nutrients, for anchorage and stability, for interaction with symbionts and, in some cases, for the storage of carbohydrates. These functions are associated with the Root System Architecture (RSA, i.e. the form and the spatial arrangement of the roots in the soil). The RSA results from several biological processes (elongation, ramification, mortality…) genetically determined but with high structural plasticity.

Grapevines have traditionally been grown in semi-arid areas, but viticulture is now compromised by climate change. Therefore, it is necessary to implement environmentally friendly viticulture practices to adapt grapevines to current climatic conditions. In this context, organic mulches offer many benefits, such as reduced soil erosion and increased organic matter, soil water content and crop productivity. However, these practices must not compromise grape and wine quality. Therefore, the objective of this study was to evaluate the effect on wine physicochemical and phenolic composition and sensorial properties of different soil management practices on the vine row. Over four years, five soil treatments were examined in two different vineyards.

Among the Moscato grapes, Moscato Giallo is a winegrape variety characterized by a high content of free and glycosylated monoterpenoids, which gives very aromatic wines. The aromatic bouquet of Moscato Giallo is strongly influenced by the high concentration of linalool, geraniol, linalool oxides, limonene, α-terpineol, citronellol, HO-trienol, HO-diols, 8-Hydroxylinalool, geranic acid and β-myrcene, that give citrus, rose, and peach notes.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

Leaf removal in the fruit-zone has been employed to improve cluster light exposure and ventilation and therefore increase metabolite accumulation and reduce botrytis incidence in berries. When applied before flowering (early defoliation – ED), it can also decrease cluster compactness and regulate yield in high-yielding varieties. This study aimed to evaluate the impact of ED on the physiology and metabolism of Aragonez (syn. Tempranillo) berries along the ripening period. The experiment was set up in 2013 at a commercial vineyard located in the Lisbon winegrowing region.