New tools for a visual analysis of vineyard landscapes?

There is a growing interest in the exploitation of vine-shoots waste, since they are often left or burned. Sánchez-Gómez et al. [1] have shown that vines-shoots aqueous extracts have significant contents of bioactive compounds, among which several polyphenols and volatiles are highlighted. Recent studied had demonstrated that the chemical composition of vine-shoots is enhanced when vine-shoots are toasted
[2,3]. The application of vegetable products in the vineyards has led to significant changes towards a more “Sustainable Viticulture”. An innovative foliar application for Airén vine-shoot extracts have been carried out to the vineyard. It has been shown that they act as grape biostimulants, improving certain wine quality characteristics [4].

A two years trial was carried out in Chianti (Central Italy) to assess at the detailed scale the viticultural and oenological suitability for Sangiovese of different pedoclimatic conditions, by means of the ΔC13 measured in the must sugars

The evaluation of new grapevine genotypes regarding their potential to produce high quality wines is the time limiting factor in the process of grapevine breeding. Hence, the development of quality-related markers useable in marker-assisted selection (MAS) as well as in prediction models for this bottleneck trait will tremendously enhance breeding efficiency. In extensive studies a training set of a segregating white wine F1 population (150 F1 genotypes = POP150; `Calardis Musqué´ x `Villard Blanc´) was deeply phenotyped and genotyped for model development and QTL analysis.

Viticultural management regimes influence the soil elemental profile of a vineyard, determining the microbial community distribution, insect life, and plant biochemistry and physiology

Aim: Downy mildew is a crucial disease in viticulture. In-field evaluation of downy mildew has been classically based on visual inspection of leaves and fruit. Nevertheless, non-invasive sensing technologies could be used for disease detection in grapevine. The aim of this study was to assess downy mildew severity in grapevine leaves using machine vision.