2018 updates on the agronomic performances of fungus resistant wine grapes in Trentino (Italy)

Oenococcus oeni is the predominant lactic acid bacteria species in wine and cider, where it performs the malolactic fermentation (MLF) (Lonvaud-Funel, 1999). The O. oeni strains analyzed to date form four major genetic lineages named phylogroups A, B, C and D (Lorentzen et al., 2019). Most of the strains isolated from wine, cider, or kombucha belong to phylogroups A, B+C, and D, respectively, although B and C strains were also detected in wine (Campbell-Sills et al., 2015; Coton et al., 2017; Lorentzen et al., 2019;

The Maule region hosts up to a third of the total area of vineyards in Chile, in an environment where ancient practices inherited from the colonial past coexist with modernity and dynamism that include technified irrigation and fine vines. In the dry land of Maule there is a viticulture that has subsisted with ancient vines and traditions transmitted over generations, and there is little clarity about the origin and classification of the Maule viticulture, giving rise to the use of different concepts as synonyms to describe the ancient, minority, patrimonial or Criollas vines. In order to characterize and protect the ancient material, we studied the genetic diversity of a territorial collection that covers 80% of the communes of the region, prioritizing plants established more than 40-60 years ago.

In view of sustainability and zero-waste initiatives, the valorisation of sidestreams is a key emerging topic in the wine industry.

INTRODUCTION: Oenological tannins are widely used in winemaking to improve some characteristics of wines [1] being the antioxidant properties probably one of the main reasons [2]. However, commercial tannins have different botanical sources and chemical composition [3] which probably determines different antioxidant potential. There are some few references about the antioxidant properties of commercial tannins [4] but none of them have really measured the direct oxygen consumption by them. The aim of this work was to measure the kinetics of oxygen consumption by different commercial tannins in order to determine their real capacities to protect wine against oxygen. MATERIAL AND METHODS: 4 different commercial tannins were used: T1: condensed tannin from grape seeds, T2: gallotannin from chinese gallnuts, T3: ellagitannin from oak and T4: tannin from quebracho containing condensed tannins and ellagitannins.

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.