Phenological characterization of a wide range of Vitis Vinifera varieties

Dans le vignoble champenois, le risque thermique associé au gel des bourgeons au printemps et en hiver est très mal connu et ne peut être envisagé qu’à l’échelle locale, en raison d’une variabilité spatiale forte. L’objectif de l’étude est d’appréhender ce risque de façon fiable et pluri locale en utilisant le réseau de stations météos récemment implanté.

The metabolomics era started about 22 years ago, and wine was one of the first foodstuff subjects of analysis and investigation by this technique.

Condensed tannins (CTs), polymers of flavan-3-ols, are a class of polyphenolic compounds that play a significant role in the organoleptic qualities of red wines, particularly influencing color, astringency and bitterness. These properties are highly dependent on size and structure of these compounds.

this research investigates the impact of early oxygen exposure, also during malolactic fermentation (MLF), on pigments and color of a red wine from Sangiovese grapes

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.