Analyse climatique à l’échelle des Coteaux du Layon

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.

Grapevine yield and fruit quality are two major drivers of input allocation and, ultimately, revenue for grape producers. Because yield and fruit quality vary substantially from year-to-year and within a single block, opportunities exist for optimization via precision management activities that could lead to more profitable and sustainable grape production. Here, we review recent advances in the techniques and technology used to measure, estimate, and forecast grapevine yield and fruit quality. First, we discuss direct “measurement” of yield and quality (i.e. ground-truth data generation), with an emphasis on potential for scalability and automation. Second, we discuss technology and techniques that do not directly measure yield and quality, but use correlated measurements for their estimation.

A Visual Information eNvironment for Effective agricultural management and Sustainability (VINES) is under development, which can provide significant competitive advantages to winegrowers by sustaining their appellation-specific grape and wine qualities and yields while measurably conserving water resources.

Quercetin (Q) is present in grape in form of glycosides and as aglycone. These compounds are extracted from grape skins during winemaking. In wines, following the hydrolysis reactions, the amount of quercetin aglycon can exceed its solubility value. Unfortunately, a threshold solubility concentration for quercetin in wine is not easy to determine because it depends on wine matrix (Gambuti et al., 2020).

Dans des travaux précédents sur le zonage, on a traité de la « Grande Filière », du « terroir », du « territoire », de la «″Terra »″ (« Terre »”), des « Petits zonages ou sub-zonages », du « Grand Zonage », de la qualité (nous en avons classifié plus de quatre-vingt-dix), des « Grands Objectifs » (GO) de l’activité vitivinicole et des moyens utilisés pour les atteindre. Dans le « GRAND ZONAGE » (GZ) nous avons précisé que pour zoner, nous partons des aspects