Vine response to compost addition on a sandy-loam soil in the north-east of italy. Effects on root system, vegetative growth, yield and grape quality of Cabernet-Sauvignon cv

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.

Adopting disease-tolerant varieties is an efficient solution to limit environmental impacts linked to pesticide use in viticulture. In most breeding programs, these varieties are selected depending on their abilities to tolerate diseases, but little is known about their behaviour in response to abiotic constraints.

The quality of wine is assessed, among other things, by its color, which is mainly due to its anthocyanin content. These pigments are polyphenols that give red, purple and blue hues depending on the relative proportion of anthocyanins produced by the action of flavonoid 3’5′ hydroxylase (delphinidin-3-glucoside, petunidin-3-glucoside, malvidin-3-glucoside) or flavonoid 3′ hydroxylase (cyanidin-3-glucoside, peonidin-3-glucoside). To study the genes involved in this biosynthetic pathway, we focused on Vitis vinifera cv. Tannat, known for producing wines with higher anthocyanin content and darker purple color compared to most red grape varieties. In this work, we have performed RNA-Seq analysis of skins during berry development, taking green and red berries at 50% veraison as separate samples, as an experimental strategy to focus on the differential expression of genes of interest.

Aromatic characterization is a key issue to enhance wines knowledge. While several studies argue the importance of wine expertise in the ability of performing odor-related sensory tasks, there is still little attention paid to the influence of expertise on the semantic representation of wine odors.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.