Use of satellite in precision viticulture: the Franciacorta experience

In vineyards, management and the surrounding landscape can have different effects on spiders. In temperate regions management (organic vs. conventional) may have less strong effects than for other crops.

Canopy-management practices are applied in viticulture to improve berries composition and quality, having a great impact on primary and secondary grape metabolism. Among these techniques, cluster zone leaf removal (defoliation) is widely used to manage air circulation, temperature and light radiation of grape bunches and close environment. Since volatiles are quantitatively and qualitatively influenced by the degree of fruit ripeness, the level of solar exposure, and the thermal environment in which grapes ripen, leaf removal has been shown to affect volatile composition of grape berries [1].

In white wines, Verdejo wine stands out because of its high content in total amino acids. The total content in biogenic amines was low in all wines analyzed and putrescine was the predominant biogenic amine.

GEOSPHERA s. r. l. e TERR.A.IN. CNS, forti della grande esperienza dei loro collaboratori nell’ambito delle scienze naturali, della geologia, della geofisica e dell’informatica, garantiscono risposte innovative alle problematiche della moderna agricoltura rivolgendosi direttamente ai viticoltori, ai commercianti vinicoli ed ai liberi professionisti.

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.