REVINE project : regenerative agricultural approaches to improve ecosystem services in Mediterranean vineyards

In winemaking, several antimicrobial peptides (AMPs) produced by different strains of Saccharomyces cerevisiae were found to be responsible for the inhibition of malolactic fermentation (MLF) carried out by some strains of Oenococcus oeni. However, only two AMPs produced by one of the yeast strains studied were totally identified and their mechanism of action was described. In an attempt to identify new AMPs, a 5-10 kDa peptidic fraction produced by an oenological strain of S. cerevisiae and previously shown to strongly inhibit MLF carried out by a strain of O. oeni was further purified.

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Aim: to elucidate if it is possible to detect variations in the source of nitrogen (organic vs. inorganic) measuring nitrogen isotope ratio (δ15N) in berries and to examine the degree of variation occurring for this parameter naturally within a vineyard.

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

The need to classify the vineyards of an area according to the quality of its wines is not recent, but it is only in the last ten years that studies on the suitability of different areas for the cultivation of vineyard take on an integrated and interdisciplinary character (Boselli, 1991). The definition of the suitability of the environment is thus obtained by making the climatic, pedological, topographical and cultural information interact with the vegetative, productive and qualitative expression of the grape varieties.