Use of satellite in precision viticulture: the Franciacorta experience

Aims: The optimization of nitrogen use efficiency (NUE, i.e. uptake, assimilation and partitioning) is a solution towards the sustainable production of premium wines, while reducing fertilization and environmental impact. The influence of crop load on the accumulation of N compounds in fruits is still poorly understood. The present study assesses the impacts of bunch thinning on NUE and the consequences on the free amino N (FAN) profile in fruits.

Sixty five % of the agricultural area of the Basque Country located in the DO Ca Rioja corresponds to vineyards. More than 40% of it has an average slope greater than 10%, which makes it sensitive to erosive processes. Furthermore, it is foreseeable that extreme weather events (storms, hail, extreme heat and cold, etc.) will be favored due to climate change. Cover cropping can mitigate this risk, and therefore the objective of this work is to evaluate the impact that a vegetable cover has on the agronomic behavior of the vineyard, the quality of the grape and soil erosion. For this, a trial has been carried out with a Graciano variety vineyard with a slope between 10% -20% during the years 2020 and 2021. Conventional tillage management in the area has been compared (4-6 passes per year of tillage machinery) versus spontaneous vegetation cover management in the vineyard. This implies not tilling and allowing the grass of the land to colonize the range between the lines of vines, controlling their height through 1-3 mowing passes per year, always trying to affect the surface of the land as little as possible. The vegetative growth, yield and quality of the grape and wine was measured. Furthermore, erosion has been measured using Gerlasch boxes. The yield was lower in the second year of the trial in the cover crop treatment, but erosion was significantly reduced.

The aim of this work was to study the trapping capacity of four polyaniline polymers towards phenolic compounds in wine-like model solutions. METHODS: The model wine solution was composed of 12% (v/v) and 4 g/L of tartaric acid adjusted to pH = 3.6. A series of centrifuge tubes (15 mL) were filled with 10 mL of model solution enriched with 50 mg/L of five phenolic compounds (i.e., Gallic acid, caffeic acid, (+)-catechin, (-)-epicatechin, and rutin), and treated with different doses of PANI polymer (i.e., 0, 2, 4 and 8 g/L). After the addition of the polymer, the samples were stirred using a platform shaker at room temperature (20 ºC) for 2, 8, 16 and 24 h. All treatments included three replications.

In grape berry pedicel, xylem hydraulic conductance can be impaired by blockage deposition in the lumen of xylem elements. However, the varietal difference of the interruptions has not yet been characterized. In this preliminary work, we utilized synchrotron x-ray computed microtomography experiments performed at MOGNO beamline (LNLS – Brazil) to identify possible blockage sites in natural grape pedicel xylem. For this, we imaged dehydrated pedicel’s stem portion from the Niagara Rosada variety in three different phenological stages (Pre-veraison (PreV), veraison (V) and post-veraison (PostV). The reconstructed tridimensional images with a voxel size of 1.16 µm were segmented for the identification of xylem vessel lumens. After analysing one pedicel stem per stage, we identified 658 vessels without occlusion throughout his axial plane and 41 in which we could identify possible interruptions.

Implementing artificial intelligence (AI) in viticulture and enology is a rapidly growing field of research with an essential number of potential practical applications.