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

The recent effects on temperature and rainfall caused by global warming pose a serious threat to the wine industry worldwide, mainly in terms of a loss of quality in the wines produced.

Improving our knowledge on biotic and abiotic factors that influence the composition of the grapevine mycobiome is of great agricultural significance, due to potential effects on plant health, productivity, and wine characteristics. Among the various environmental factors affecting the morphological, physiological, biochemical and molecular attributes of grapevine, drought stress is one of the most severe, becoming increasingly an issue worldwide.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Biofilms are sessile microbial communities whose lifestyle confers specific properties. They can be defined as a structured community of bacterial cells enclosed in a self-produced polymeric matrix and adherent to a surface and considered as a method of immobilisation. Immobilised microorganisms offer many advantages for industrial processes in the production of alcoholic beverages and specially increasing cell densities for a better management of fermentation rates.

Microbial pathogens of plant have evolved to sense, interpret, and use light to direct their development. One aspect of this evolved relationship is photolyase-mediated repair of UV-induced damage to pathogen DNA. Application of germicidal UV (UV-C) at night circumvents the blue light-driven repair of pathogen DNA and allows non-phytotoxic doses of UV-C to suppress a variety of pathogenic microbes and even certain arthropod pests without damage to vines or fruit. Lamps arrays have been designed specifically for the canopy architecture of grapevines and have been deployed on both tractor-drawn and robotic carriages for partial to near-complete suppression of powdery mildew (Erysiphe necator), sour rot (fungal, bacterial, and arthropod complex), and downy mildew (Plasmopara viticola).