Techniques of delimitation in France

The above-ground parts of plants, which constitute the phyllosphere, have long been considered devoid of bacteria and fungi, at least in their internal tissues and microbial presence there was long considered a sign of disease. However, recent studies have shown that plants harbour complex bacterial communities, the so-called “microbiome”[1]. We are only beginning to unravel the origin of these bacterial plant inhabitants, their community structure and their roles, which in analogy to the gut microbiome, are likely to be of essential nature. Among their multifaceted metabolic possibilities, bacteria have been recently demonstrated to emit a wide range of volatile organic compounds (VOCs), which can greatly impact the growth and development of both the plant and its disease-causing agents.

A critical aspect of wine quality is the overall expression of wine flavour, which is formed by the interplay of volatile aroma compounds, their precursors, and taste and matrix components.
Grapes directly contribute to wine only a small number of potent aroma compounds, and the unique
sensory attributes and perceived quality of a wine result from combining 100s of metabolites of grapes, yeast and bacteria, and oak wood.

Fermentative aromas (especially esters and higher alcohols) highly impact the organoleptic profile of young and white wines. The production of these volatile compounds depends mainly on temperature and Yeast Available Nitrogen (YAN) content in the must. Available dynamic models predict the main reaction
(bioconversion of sugar into ethanol and CO2 production) but none of them considers the production kinetics of fermentative aroma compounds during the process of fermentation. We determined the production kinetics of the main esters and higher alcohols for different values of initial YAN content and temperature, using an innovative online monitoring Gas Chromatography device.

Random sampling is often considered to be the best protocol for fruit sampling because it is assumed to produce a sample that best represents the vineyard population.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65