Functional characterisation of genetic elements regulating bunch morphology in grapevine

In the O Ribeiro Denomination of Origin, there is a winemaking tradition of growing vines under a high-density plantation framework (8,920 vines/ha) and maintaining its vegetative cycle under rainfed conditions.
Currently, viticulture is advancing to plantation frames in which the density is considered medium (5,555 vines/ha), thus allowing mechanized work to be carried out for vineyard management operations. Although, the application of irrigation applied proportionally to the needs of the vegetative cycle of the vine, is a factor that increasingly helps a good development of the vine compared to the summer period, with increasingly uncertain weather forecasts.

Developing a tractable genetic engineering and gene editing system is an essential tool for grapevine. We initiated a plant transformation and biotechnology program at Oregon State University using the grape microvine system (V. vinifera) in 2018 to interrogate gene-to-trait relationships using traditional genetic engineering and gene editing. The microvine model is also used for nanomaterial-assisted RNP, DNA, and RNA delivery. Most reference genomes and annotations for grapevine are collapsed assemblies of homologous chromosomes and do not represent the specific microvine cultivar ‘043023V004’ under study at our institution.

The aim of this communication is the study of the Ronda and Arriate municipal territories environment in order to define and to establish the main physical factors in relation to vine-growing land use. The vine-growing zoning proposed is based on geopedological and climatic features.

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.

Currently, to consistently ensure the maintenance of a wine-style while benefiting from the utmost rigor made possible by the winemaking process, the composition of the wine blend is made using sensory control. This is performed after the wine is made with no real possibility of deterministic intervention.