Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Intensification is considered one of the major drivers of biodiversity loss in farmland. The more intensive management practices that have been adopted the last decades, contributed to species declines from all taxonomic groups. Moreover, agricultural intensification has led to an important change of land use. Complex, mixed agro-ecosystems with cultivated and non-cultivated habitats have been converted to simplified, intensive and homogeneous ones with severe effects on biodiversity.

The aim of this work was to reduce the alcohol content of Tempranillo wine. Tempranillo wines were produced by grapes harvested at different ripening dates (August 11 which was 21 oBrix and September 28 with 25 oBrix). At the second date, the Tempranillo wines were elaborated as follows: grapes were destemmed, crushed and collected into 50 L stainless-steel vats. Before preferementative maceration in cold, 50 % (M1) and 70 % (M2) of the must have been replaced by the same percentage of must from the first harvest. In addition, a control wine (C) was performed with only grapes from the second harvest.

In Spain, the wide diversity of red grapevine varieties represents an advantage when choosing the most suitable one for cultivation based on different climatic conditions, without implying a loss of their enological potential.

In recent years, proteins endogenous to grape have become of great interest to the wine industry because they represent a new alternative to other biopolymers subjected to more legal restrictions (i.e. animal origin and synthetics) that can be used in technological applications to modulate sensory attributes such as wine color and have a positive impact on wine quality.

Wineries may randomly reject fruit from vineyards near wild fires exposed to smoke. It is difficult to determine if fruit has been compromised in quality when exposed to smoke