Development of analytical sampling technique to study the aroma profile of Pinot Noir wine

The root and shoot abscisic acid (ABA) accumulation in response to water deficit and its relation with stomatal conductance is longtime known in grapevine. ABA-dependent and ABA-independent signalling response to osmotic stress coexist in sessile plants. In grapevine, the signaling role of ABA in response to water stress conditions and its influence on berry quality is critical to manage grapevine acclimation to climate change.

In 2004, at its general assembly, the oiv adopted the transfer of its scientific and technical heritage from the office to the international organisation of vine and wine. Unesco defines heritage as “our legacy from the past, what we live with today, and what we pass on to future generations.”

The presence of unstable proteins in wines can affect their stability and clarity. Before bottling, winemakers need to be sure that the wine is stable. A large number of stability tests have been proposed, usually based on heating a sample with a specific time-temperature couple. In practice, none is effective to accurately assess the risk of instability. Moreover, the interpretation of the results of these tests changes according to the region.

Aims: The aims of this study are to determine the influences of the local geology, mineralogy and geochemistry of surroundings, substrate and soil on the cultivation of vines, these as an additional factor of specificity and locality in the production of wine and definition of terroir, as well as for the discrimination of local variance of substrate and soil properties for the strategic management of cultivation plots and/or the evaluation of new cultivation regions, necessary within a scope of global climate change.

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.