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The study was conducted in a Tempranillo (Vitis vinifera L.) vineyard, in Navarra (Spain) across three consecutive seasons. Winegrape technological (total soluble solids, pH and titratable acidity) and phenolic (anthocyanins and total phenols) variables were measured in a regular sampling mesh at harvest, covering the entire area. Grape phenolic parameters(More)
The use of new, rapid and non-invasive sensors in the field allows the collection of many observations which are necessary to assess the spatial variability of berry composition. The aim of this work was to study the spatial variability in anthocyanin content in grapes and to quantify its relationship with the vigour and yield in a commercial vineyard. The(More)
The goal of this study was to assess the water status variability of a commercial rain-fed Tempranillo vineyard (Vitis vinifera L.) by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). The relationships between aerial temperatures or indices derived from the imagery and leaf stomatal conductance (g s) and stem water potential (Ψstem)(More)
Berry size of winegrapes has often been considered to influence wine composition and quality. The measurement of the size and weight of grapevine berries may provide important information to assess differences in ripening stage, pulp/skin ratio and phenolic content. This task is usually done by hand, so that it becomes slow, tedious and inaccurate. This(More)
The identification of different grapevine varieties, currently attended using visual ampelometry, DNA analysis and very recently, by hyperspectral analysis under laboratory conditions, is an issue of great importance in the wine industry. This work presents support vector machine and artificial neural network's modelling for grapevine varietal(More)
Implementation of precision viticulture techniques requires the use of emerging sensing technologies to assess the vineyard spatial variability. This work shows the capability of multispectral imagery acquired from a remotely piloted aerial system (RPAS), and the derived spectral indices to assess the vegetative, productive, and berry composition spatial(More)
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