Three Nebbiolo clone anthocyanin profile as affected by environmental conditions

AIM: Oak wood play traditionally a huge role in making fine red wines. During wine maturation, barrel yields some of its constituents to the wine and leads to the improvement of its quality, contributing to richness and complexity [1].

Some red wines develop a “bouquet” during ageing. This complex aroma is linked to quality by wine tasters1. The presence of dimethylsulfide (DMS) in those wines is implicated

‘Tempranillo Tinto’ is one of the most relevant grapevine cultivars worldwide. Despite its early ripening and relatively short vegetative cycle, which may not be ideal for high-quality grape and wine production in warming conditions, its long-standing cultivation has led to an intense multiplication by cuttings, which originated the high level of clonal variation currently available. Now, this intra-varietal diversity provides an interesting opportunity for cultivar improvement by identifying genotypes with better adaptation potential.

Wine yeast strains Saccharomyces ellipsoideus have important applications in food industry and in this regard is sought isolation as pure cultures and selecting those strains

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.