Red Grenache variety in Rhône Valley : impact of “terroir” and vintages on the aromatic potential of the grapes

Vitis vinifera L. is the most widely cultivated Vitis species which includes numerous cultivars. Owing to their superior quality of grapes, these cultivars were long considered the only suitable for the production of fine wines. However, the lack of resistance genes in V. vinifera against major grapevine pathogens, requires for its cultivation frequent spraying with large amount of fungicides. Thus, the search for alternative and more sustainable methods to control the grapevine pathogens have brought the breeders to focus their attention on other Vitis species. In fact, wild Vitis genotypes present multiple resistance traits against pathogens, such as powdery mildew, downy mildew and phylloxera.

One of the major determinants of wine quality is the aroma. Wine aroma is the human perception of the matrix of grape and yeast derived volatiles and their interaction that contribute to flavour wine. Most common are higher alcohols, ester and aldehydes. In previous studies the formation of characteristic volatile compounds have been linked to the metabolism of branched-chain and aromatic amino acids
(BCAAs) in synthetic grape must. Here we report on an investigation to assess the impact of the initial amino acid concentration on the production of aroma compounds by the industrial yeast VIN13 grown in both synthetic and real grape musts.

One of the main challenges in the wine industry is to understand how different wine processing techniques and practices can influence the overall quality of the final product.

Yeast protein extracts (ypes) have flocculating properties, allowing clarification of musts and wines. They are already authorized by oiv for fining purposes with a maximum dosage limit of 60 g/hl for red wines, and 30 g/hl for musts, white and rosè wines. The extraction of ypes from the cytoplasm of yeasts (saccharomyces spp) cells is defined by the resolution oiv oeno 452-2012, that indicate also some specification of the final product.

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.