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

Sparkling wine (SW) production entails a two-steps process where grape must undergoes a primary fermentation to produce a base wine (BW) which is then refermented to become a SW. This process allows for the development of a new physicochemical profile characterized by the presence of foam and a different organoleptic profile.

A method of suspect screening analysis to study grape metabolomics, was developed [1]. By performing ultra-high performance liquid chromatography (UHPLC) – high-resolution mass spectrometry (HRMS) analysis of the grape extract, averaging 320-450 putative grape compounds are identified which include mainly polyphenols. Identification of metabolites is performed by a new HRMS-database of putative grape and wine compounds expressly constructed (GrapeMetabolomics) which currently includes around 1,100 entries.

Throughout the growing season, grapevine frequently encounters environmental challenges associated with heat and light radiation stress, especially during the ripening stage, thereby constraining the yield and quality of berries. MYB24 has been previously proposed to control light responses during late fruit ripening stages, and it has been found to require the co-factor MYC2. We have generated transcriptomic data from grapevine leaves transiently co-transformed with MYB24 and MYC2. Differential expression analysis revealed 179 up-regulated genes (URGs). Considering tissue specificity, where MYB24 is specifically and highly expressed in flowers and late-ripening berries, the expression of these URGs was explored using a previously published Berry Development Atlas gathering berry development data of cv. ‘Pinot Noir’ and ‘Cabernet Sauvignon’ in different vintages.

In this video recording of the IVES science meeting 2023, Stéphanie Marchand (University of Bordeaux, ISVV, INRAE, UMR 1366 OENOLOGIE, Villenave d’Ornon, France) speaks about the aromatic maturity as a cornerstone of terroir expression in red wine. This presentation is based on an original article accessible for free on OENO One.

This paper aims to (i) identify the state of the art regarding digital transformation in the transition to sustainability in the wine industry, (ii) analyze the adoption of digital technologies at different stages of the winemaking process and their contribution to the triple bottom line of sustainability, and (iii) present a research agenda that facilitates the development of the field, providing contributions to both literature and managerial practice.