La superficie vitata della provincia di Modena é per circa il 70% interessata dai Lambruschi, famiglia di vitigni tipica dei territori pianeggianti emiliani. Tra questi, i più rappresentativi sono il Lambrusco di Sorbara, il Lambrusco salamino e il Lambrusco grasparossa che, unico esempio, predilige gli ambienti collinari della provincia. Nel quinquennio 2001-2005 la Provincia di Modena ed il C.R.P.V. hanno coordinato la zonazione viticola di tutto il territorio dei Lambruschi modenesi, i cui risultati hanno consentito di individuare, in ciascuna zona D.O.C., alcune Terre in cui cias.

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.

Sulfonated monomeric and dimeric flavan-3-ols are recently discovered in wine and proved to have great importance in understanding wine chemistry and quality [1, 2].

This study explores and analyzes the socio-environmental implications associated with the cultivation of the “brs-vitoria” table grape variety. Focusing on its adoption by farmers in the vale do submédio São Francisco region in Brazil, this study delves into the diverse impacts and changes brought about since its introduction, encompassing both the social and environmental dimensions of agricultural practices in the area. Embrapa, brazil’s federal agricultural research institution, encompasses a network of 43 thematic research centers spread across the nation.

Understanding the impact of rootstocks on grapevine water relations is crucial to face climate change maintaining vineyard productivity and sustainability.