A first look at the aromatic profile of “Monferace” wines

Row orientation and canopy management are essential for high quality grapevine production. Microclimatic conditions of the leaves and fruits can be influenced by the canopy geometry. Remote sensing is a very promising tool to describe vegetative growth and physiological behavior of vineyards. However, the correlation between remotely sensed data and in situ field measurements has been described scarcely in the scientific literature so far. The aim of the study was to correlate remotely sensed data obtained with Unmanned Aerial Vehicle (UAV) with in situ field measurements to describe canopy structure.

Aims: The aims of this study were to (i) characterize bacterial and fungal communities in selected Australian vineyard soils and (ii) determine if the soil microbiome composition and diversity varied between different zones within a vineyard. 

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.

In this work we try to know the influence of two irrigation systems (Drip and Micro – jet ) with the same levels of water applied in an experimental vineyard in the region of Felgueiras.

The study described the effect of sensory analysis on commercial ‘Sauvignon blanc’ vineyards within the Stellenbosch Wine of Origin District. The sensorial evaluation of the berries was able to give a description of each parcel type and relate it to the cultural practices.