Study of the effect of native vineyard bacteria on the expression of Plasmopara viticolaeffectors

New pathogen resistant varieties allow an efficient and greatly reduced use of fungicides. These new varieties promise, therefore, an enormous potential to reach the European Green Deal aim of a 50% reduction of pesticides in EU agriculture by 2030.

n the last years, viticulture precision tools have been made available for farmers for different crops. The feeling that these tools are mandatory on an agriculture of the future have been disseminated by commercial entities but also from policy makers.

Nowadays, the trend is to reduce the use of chemical inputs in the food sector, including in oenology. One of the inputs widely used in the wine making process are sulfites, for its several properties: antimicrobial and antioxidiant. This use isn’t without consequences on consumer’s health and environment, it can lead for example to allergic reactions and pollution. To limit the addition of chemical inputs, microbial alternatives are used. It consists to inoculate in grape must, a micro-organism able to inhibit the growth of the negative indigenous flora during the phase before the fermentation and to guarantee the sensory qualities of wines.

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.

Recurring heat and drought episodes during the growing season can produce adverse impacts on grape production in many wine regions around the world.