Incidence de la nature du sol et du cépage sur la maturation du raisin, à Saint Emilion, en 1995

Red grape pomace, a waste from wine production, can be valorised by extracting polyphenols, high-added value compounds used in cosmetics or oenology. For use at an industrial level, using green extraction techniques, pomace need to be stored before being processed. The aim of this study is to test various storage conditions in order to maintain high level of polyphenols over 180 days, while keeping storage cost economically interesting. In a first step, different storage conditions (ambient temperature or cooled (4°C) temperature, anaerobic (saturation with N2) or aerobic conditions, and addition of sulphur dioxide (SO2)) were compared on small samples (1 kg) packed in plastic pockets. The quality of storage was assessed by following the optical density of the pomace extract at 280 nm (DO 280 expressed as mg/l eq gallic acid), which is an indication of the amount of remaining extractable polyphenols.

Grapevine faces multiple biotic and/or abiotic stresses, which are interrelated. Depending on their incidence, they can have a negative impact on the development and production of the plant, but also on its longevity, leading to vine dieback. One of the consequences of vine dieback on production is the increased replacement rate of dead or missing vines within a parcel.

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.

The professional winegrower usually selects the harvest date considering several elements, such as the vine stem and berry colour, the flavour, appearance and grain elasticity. Nowadays these elements have turned old fashioned.

Aim: To identify the sensory attributes responsible for the typicity of Cabernet Sauvignon wines from three Australian Geographical Indications (GIs) and to explore consumer purchase behaviour and preference with regard to regional wines.