Elaboration des cartes conseils pour une gestion du terroir à l’échelle parcellaire: utilisation d’algorithmes bases sur des paramètres physiques du milieu naturel

Sauvignon blanc was first planted in Marlborough, New Zealand in the mid-1970s. Since that time, Marlborough has gained an international reputation by producing the definitive wine style of that grape variety.

Chitin is the main structural component of a large number of organisms (i.e., mollusks, insects, crustaceans, fungi, algae), and marine invertebrates including crabs and shrimps. The main derivative of chitin is chitosan (CH), produced by N-deacetylation of chitin in alkaline solutions. Over the past decade, the OIV/OENO 338A/ 2009 resolution approved the addition of allergen-free fungoid CH to must and wine as an adjuvant for microbiological control, prevention of haziness, metals chelation and ochratoxins removal (European Commission. 2011). Despite several studies on application of CH in winemaking, there are still very limited and controversial data on its interaction with acidic components in wine (Colan-gelo et al., 2018; Castro Marin et al., 2021).

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.

All along the red winemaking process, many microorganisms develop in wine, some being beneficial and essential, others being feared spoilers. One of the most feared microbial enemy of wine all around the world is Brettanomyces bruxellensis. Indeed, in red wines, this yeast produces volatile phenols, molecules associated with a flavor described as “horse sweat”, “burnt plastic” or “leather”. To produce significant and detectable concentrations of these undesired molecules, the yeasts should first grow and become numerous enough. Even if the genetic group of the strain present and the cellar temperature may modulate the yeast growth rate¹ and thus the risk of spoilage, the main factor seems to be the wines themselves, some being much more permissive to B. bruxellensis development than others.

Reduction of sulfur dioxide during winemaking is a request from the wine industry. To replace sulfur dioxide, various alternatives exist, including bioprotection by yeast inoculation. This practice consists in adding non-Saccharomyces yeasts directly on the grapes or must.