Identification of loci associated with specialised metabolites in Vitis vinifera

Viticulture is globally important for socioeconomic and environmental reasons. The EU is globally leading grape and wine production, and Spain is among the top grape and wine producers. As climate change affects viticulture, mitigation and adaptation are crucial for protecting grape production. In this research work, data on viticultural management practices such as soil cultivation, irrigation, energy, machinery, plant protection and the use of fertilizers from vineyards located in Logroño (La Rioja) have been obtained.

Climate emergency is going to affect the agricultural suistainability, wine grapes being probably one of the crops more sensitive to environmental constraints. In this context, mitigation strategies such as the revalorization of agricultural wastes are paramount to cope with the current challenges. The use of organic mulches has been reported to reduce soil water evaporation and improve vine water status, reduce soil erosion, and increase soil organic matter with little impact on berry quality. However, less is known about their effects on the microbiote of vineyards.

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.

The Mediterranean basin is one of the most vulnerable regions to Climate Change effects. According to unanimous forecasts, the vineyards of Castilla-La Mancha will be among the most adversely affected by rising temperatures and water scarcity during the vine’s vegetative period. One potential strategy to mitigate the negative impacts of these changes involves the identification of grapevine varieties with superior water use efficiency, while ensuring satisfactory yields and grape quality.

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).