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

High concentration of sugars in grapes and alcohols in wines is one of the consequences of climate change on viticulture production in several wine regions. One of the options to alleviate this potential problem is to perform severe shoot trimming of the vines to limit the production of carbohydrates. Two different studies were performed in order to investigate the effects of severe shoot trimming on the composition of Merlot grapes; in a first study severe shoot trimming was performed at three different phenological stages (at berry set, at the beginning of veraison and at the end of veraison), while in a second study two trimming treatments (standard shoot trimming and severe shoot trimming performed at the end of veraison) were combined with two shoot densities in order to evaluate the relative impact of these treatments on Merlot grape composition.

Cet exposé présente une caractérisation générale de la Région Délimitée du Douro (RDD), productrice des appellations Porto (vins généreux), et Douro pour des vins de qualité VQPRD.

The use of next-generation sequencing (NGS) has helped understand microbial genetics in oenology. Current studies mainly focus on barcoded amplicon NGS but not shotgun sequencing, which is useful for functional analyses. Since the high percentage of grapevine DNA conceals the microbial DNA in must, the majority of sequencing data is wasted in bioinformatic analyses. Here we present capture depletion of grapevine whole genome DNA.

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.

Cannonau variety is historically grown in a large Sardinia area (Jerzu district) and the vineyards are planted both in the plane and in the sloped hills reaching also 650 m of altitude a.s.l. Thus, in order to discover how climate, soil diversity and growing traditions could account for differences in grape and wine quality, this trial was carried out.