Untargeted LC-HRMS analysis to discover new taste-active compounds in spirits.

The sensory properties of a wine depends on its colours, aromas and flavors. Regarding red wines, the gustatory part consists of the acid, bitter and sweet tastes

Wine is an intrinsically complex aromatic product. To formalize this aromatic diversity and the hierarchical structure of the aromas, it is common to present them in the form of a wheel of aromas. These are used for learning and communication purposes but never for the acquisition of sensory characteristics.

During recent years, carbonic maceration (CM) wines are increasingly demanded by consumers. The Spanish Rioja Qualified Designation of Origin (D.O.Ca. Rioja) is a winemaking area

As is well known, Champagne is a product of the highest quality recognized in the international market. Champagne is a type of sparkling wine made in the Champagne region

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.