Cover crop influence on water relations, yield, grape and wine composition of Pinot noir

Castilla y León is the third longest region in the European Union, having more than 85.000 vineyard hectares.

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.

According to winemakers, wine experts and sommeliers, aromas of wet stone, mineral, struck match and flint in white wines styles, such as those produced from Vitis vinifera L. cv. Chardonnay, are considered to be hallmarks of positive reduction.1,2 In recent years, the production of Chardonnay styles defined by aroma characteristics related to positive reduction has become more desirable among wine experts and consumers. The chemical basis of positive reduction is thought to originate from the concentration of specific volatile sulfur compounds (VSCs), including methanethiol (MeSH) imparting mineral and chalk notes,3 and benzenemethanethiol (BMT) responsible for struck match and flint.1,4

To study the copigmentation between different wine flavonols (myricetin, quercetin, kaempferol, isorhamnetin and syringetin 3-O-glucosides) and malvidin

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.