Improvement of non-Saccharomyces yeast dominance during must fermentation by using spontaneous mutants resistant to SO₂, EtOH and high pressure of CO₂

Flavescence dorée (FD) is the most serious grapevine yellows disease in Europe. It is caused by phytoplasmas which are transmitted from grapevine to grapevine by the leafhopper Scaphoideus titanus.

AIM: Organic production of wine in the past years has known an important augmentation. This type of cultivation practice switches synthetic phytosanitary product for copper-based protection as fungicide.

Il tema da trattare si riferisce ai vari ecosistemi viticoli mondiali, ovviamente non facilmente sintetizzabili in una relazione. Sostanzialmente si richiama

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.

Aroma and mouthfeel cues are the main characteristics defining red wine quality. During wine tasting, perceptual and physical-chemical phenomena leading to mutual interactions between volatiles and non-volatiles sensory active compounds, can occur. Aroma perception depends on the release of volatiles from wine, that is affected by wine constituents present in the medium (Pittari et al. 2021; Lyu et al. 2021). Our aim was to evaluate the effect of the non-volatile wine matrix composition (polyphenols, PPh) on the release and perception of red wine aromas by an experiment of matrix enrichment.