What triggers the decision to ripen 

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 projected rise in mean air temperatures together with the frequency, intensity, and length of heat waves in many wine-growing regions worldwide will deeply impact grape berry development and quality. Several studies have been conducted and a large set of molecular data was produced to better understand the impact of high temperatures on grape berry development and metabolism[1]. According to these data, it is highly likely that the metabolomic dynamics could be strongly modulated by heat stress (HS).

In this study two different compost types and two application methods were studied over 5 years (2009-2013) on mature Cabernet Sauvignon vines grown in a commercial vineyard in the AOC Piave area, northeastern Italy.

In 2001, the Hungarian Ministry of Agriculture and Rural Development designated the Institute of Geodesy, Cartography and Remote Sensing (FÖMI) to elaborate a Geographic Information System (GIS) supported Vineyard Register (VINGIS) in Hungary. The basis of this work was a qualification methodology (vineyard and wine cellar cadastre system) dating back to several decades, however, in the 1980s and 1990s the available geographical maps and information technology did not provide enough accuracy for an overall evaluation of viticultural areas. The reason for the VINGIS elaboration and development was an obligation resulting from the EU membership to ensure the agricultural subsidies for the wine–viticulture sector.

Fifteen nepoviruses are able to induce fanleaf degeneration in grapes. Grapevine fanleaf virus (GFLV) is the main causal agent of this disease