Long-Term impact of elevated CO2 exposure on grapevine physiology (Vitis vinifera L. cvs. Riesling & Cabernet Sauvignon)

The strategy of single berry phenotyping is a recently rediscovered research tool that has gained great attention. The latest studies have indicated that previous physiological models based on pooling asynchronous populations of berries provided biased or blurred information on berry development key players. The possibility of monitoring and sampling single synchronized berries to study their development sequentially has opened new lines of research aimed at unraveling the genes that regulate grapevine fruit development. This study aimed to decipher the gene pathways responsible for the activation/deactivation of physiological processes involved in the green phase of growth, the onset of ripening, and the second growth phase.

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.

L’étude porte sur trois terroirs du Roussillon, classés dans l’A.O.C. Muscat de Rivesaltes et concerne les 2 cépages de cette appellation : le muscat à petits grains et le muscat d’Alexandrie. Elle a pour objectif de connaître pour un terroir donné le meilleur choix de cépage.

Une étude préliminaire des situations météorologiques journalières a été réalisée pour l’Afrique du Sud et pour les mois de février (période de maturation des raisins dans la Province occidentale du Cap), à l’image de la classification synoptique réalisée aux latitudes tempérées en France (Jones & Davis, 2000), afin d’étudier les relations entre le climat et la viticulture à des latitudes plus basses.

We compared 68 aroma compounds in wines from 5 vineyards in order to see similarities among the wine aroma and the scent of some of the main native plants from the respective vineyards.