Learning from remote sensing data: a case study in the Trentino region 

AIM. Grape seeds (Vitis vinifera) are among the main constituents of grape pomace, also exploited in ingredients for nutraceutics and cosmeceutics, particularly regarding the phenolic fraction. The macromolecules of grape/wine include polyphenols, proteins and polysaccharides.

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Eugenol has been identified as a quality marker in armagnac white spirits. In particular, those produced from the Baco blanc variety, the only hybrid variety authorised in a French PDO, bred since 1898 from noah (vitis labrusca x v.riparia) and folle blanche (v. Vinifera). The varietal compound of Baco blanc, eugenol has many original properties.

Context and purpose of the study. Climate change is a major challenge in wine production. It results in erratic weather conditions which may lead to a reduction in grape yield and the subsequent grape and wine quality.

AIM: Grape withering is an oenological post-harvest process used for production of reinforced and sweet wines. Drying can be carried out by keeping the ripe grape in traditional large, well-aired rooms (non-controlled environment) or, more and more often, in a warehouse under controlled conditions of airflow and relative humidity (controlled environment)[1].