Etude des effets millésime, situation et sol à partir d’un observatoire du Gamay en beaujolais

Geospatial technologies have significant contribution to viticulture, especially in small-scale vineyards, which require precise management. Geospatial data collected by modern technologies, such as Unmanned Aerial Vehicle (UAV) and satellite imagery, can be processed by modern software and easily be stored and transferred to GIS environments, highlighting important information about the health of vine plants, the yield of grapes and the wine, especially in wine-making varieties. The identification of field variability is very important, particularly for the production of high quality wine. Modern geospatial data management technologies are used to achieve an easy and effortless localization of the fields’ variability.

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.

Viticulture is facing two major changes – climate change and agroecological transition. In both cases, soil quality is seen as a lever to move towards a more sustainable viticulture. However, soil biological quality is little considered in the implementation of viticultural practices. Gascogn’Innov (2017-2022) is an Operational Group funded by the European Innovation Partnership for Agriculture. As such, it brings together winegrowers from the south-west of France, scientists, advisors and technicians, around a project focused on viticultural soil biological functioning and the design of technical routes more respectful toward soil heritage. To achieve this, the project aims to acquire references on the impact of viticultural practices on soil biology from a dynamic way, and to test a methodology to integrate information provided by the soil bioindicators to manage farming systems. A set of indicators of soil biological quality are evaluated in the project: microorganisms (bacteria and fungi abundance and diversity), fauna (abundance and diversity of nematodes and earthworms), physico-chemical characteristics, soil structure assessment and degradation rate of organic matter. Based on a network of 13 plots that have been subject to an initial diagnosis in 2017, several agronomical practices to restore soil fertility are experimented to redesign the cropping system (for instance plant cover, organic matter inputs, reduction of herbicides, mineral fertilizers). System redesign was made in collaboration by winegrowers and an interdisciplinary group of experts (agronomists, biologists). Several indicators are measured on vine and soil at each vintage to assess vine health and productivity. At the end of the project (2021), a final diagnosis was carried out. Gascogn’Innov allowed to create a regional database on the quality of wine-growing soils, which permitted to evaluate the effect of practices according to soil types. Especially, decreasing the intensity of tillage and increasing the duration and diversity of grass coverage tends to increase the abundance of all the organisms studied. This project confirmed the value of soil biological quality indicators to drive the sustainability of practices, but also highlighted the key-role of expertise, in both agronomy and soil biology, to help winegrowers understand and appropriate their soil quality diagnoses.

Sulphur dioxide has long been considered an irreplaceable additive due to its numerous significant positive effects during winemaking and beyond.

Color is one of the key elements in the marketing of rosé wines[1]. Their broad range of color is due to the presence of red pigments (i.e. anthocyanins and their derivatives) and yellow pigments, likely including polyphenol oxidation products. Clarifying agents are widely used in the winemaking industry to enhance wine stability and to modulate wine color by binding and precipitating polyphenols[2]. During this study, the impact of four different fining agents (i.e. two vegetal proteins, potatoe and pea proteins, an animal protein, casein, and a synthetic polymer, polyvinylpolypyrrolidone, PVPP) on Syrah Rose wine color and phenolic composition (especially pigments) was investigated. Color was characterized by spectrophotometry analysis using the CIELab system in addition to absorbance data. Fining using PVPP had the highest impact on redness (a*) and lightness (L*) parameters, whereas patatin strongly reduced the yellow component (b*) of the wine color. In parallel, the concentration of 125 phenolic compounds including 85 anthocyanins and derived pigments was determined by Ultra High Performance Liquid Chromatography coupled to elestrospray ionisaion triple-quadrupole Mass Spectrometry (UHPLC-QqQ-ESI-MS) in the Multiple Reaction Monitoring mode[3] .