Neural networks and ft-ir spectroscopy for the discrimination of single varietal and blended wines. A preliminary study.

Somló is Hungary’s smallest wine district, however one of the best producing white wines. The majority of vineyard areas are located on the slopes of Somló-hill, situated at the point where the Kisalföld meets Bakonyalja

Candida zemplinina (synonym Starmerella bacillaris) is frequently isolated in grape must in different vitivinicultural areas. The enological significance of C. zemplinina strains used in combination with S. cerevisiae has been demonstrated, being wines produced by the above-mixed starter, characterized by higher amounts of glycerol and esters.

Most vineyards are grafted and include a variety (Vitis vinifera) grafted over a wild Vitis rootstock (hybrids of V. berlandieri, riparia and rupestris). Grape berry quality at harvest depends on a subtle balance between acidity and the concentrations of sugars, polyphenols and precursors of aroma compounds. The mechanisms controlling the balance of sugars/acids/polyphenols are influenced by the abiotic environment, in particular nitrogen supply, and interact with the genotypes of both the scion variety and the rootstock. Previous work suggests that some of the effects of water stress are in fact linked to a nitrogen deficiency driven indirectly by the reduction of water absorption.

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.

Brettanomyces bruxellensis is found in various ecological niches, but particularly in fermentative processes: beer, kombucha, cider and wine. In the oenological sector, this yeast is undesirable, as it can produce ethyl phenols, thus altering wine quality. These compounds are characterized by stable or horse-sweat aromas, unpleasant for consumers.