Amyndeon‐naoussa: the two faces of Xinomavro

Hail damage can have a major impact on the vine’s physiological growth (defoliation, wood and cane damage) and can lead to significant yield and economic losses.

Sfursat di Valtellina is a DOCG reinforced wine produced in Valtellina from partially withered red grapes of Vitis vinifera L. cv. Nebbiolo. The grape ripeness degree and the dehydration process strongly influence the physicochemical characteristics of grapes [1, 2, 3]. In particular, grape skin and seeds contain several classes of phenolic compounds strictly associated with red wine quality, which are significantly affected by these factors [4]. The aim of this research is to assess the combined influence of different ripeness levels and withering rates on the standard chemical composition and phenolic profile of winegrape in order to provide new insights and approaches to the management of withering, searching for the valorization of grape potentialities.

Australia is the seventh largest producer of wine and crushed 1.42 million tonnes of wine grapes in the 2001 vintage.

The Ibero-American Network of Viticulture, a component of the program of agricultural technology of the CYTED (Ibero-American Program of Science and Technology for Development), is developing the project “Zoning Methodology and Application in Viticultural Regions of Ibero-America”.

Vine diseases have a strong impact on vineyards sustainability, which in turns leads to strong economic consequences. Among those diseases, Flavescence dorée spreads quickly and is incurable, which led in France to the setup of a mandatory pest control implying the systematic use of pesticides and the prospection and uprooting of every infected plants. Remote sensing could be a very powerful tool to optimize prospection as it allows to produce quickly accurate maps over large areas. Recent studies have shown that high spatial resolution (10cm/pixel) multispectral images acquired from UAVs allow to map Flavescence dorée in vineyards using leaves discolorations [e.g. Albetis et al., Remote Sensing, 2017].