A zoning study of the viticultural territory of a cooperative winery in Valpolicella

The global consumption of wine has undergone significant changes after several years of covid-19, which was the beginning of a global crisis of the current century. This pushed some people to start looking for comfort and security as they felt that the world around them was losing these benefits. In most cases, this has led to them to idea of rethinking their lives in an attempt to live better or continuing to stay true to their habits and lifestyles despite the pressure of changes. Alcohol in any form is a part of these reactions, leading to increased consumption in the early stages of a crisis, particularly in relation to anxiety.

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.

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.

The vineyards placed in the municipal areas of Fuente de Piedra, Humilladero and Mollina constitute a wine-growing important area of the “Zona Norte” of the province of Málaga.

The wine industry is increasingly focused on carbon accounting due to consumer’s demand and the industry’s goal of reducing carbon emissions.