Heat-stress responses regulated via a MYB24-MYC2 complex

Grape stalks are a byproduct of the winemaking process and represent a valuable and inexpensive source of bioactive compounds. While their direct use in whole bunch fermentation is known, the majority of grape stalks are discarded, posing environmental and economic challenges.

Plusieurs caves coopératives de l’AOC Côtes du Rhône se servent des informations du zonage pour la sélection des vendanges en fonction du terroir d’origine, afin d’élaborer des «cuvées terroir» et d’exploiter ainsi le potentiel qualitatif de leurs secteurs.

The influences of quality compost A+ and of a commercial organic fertilizer based on dry mash from bioethanol production, blackstrap molasses, vinasse, PNC (potato nitrogen concentrate) and CSL (corn steep liquor) on the humus content, on the mineral nitrogen content in the soil, in the must and in the vine leaves, on pruning wood

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.

Accurate and early yield estimation in vineyards is essential for the effective management of resources and informed decision-making in viticulture.