Optimization of a tool to determine the oxygen avidity of a wine through the kinetics of consumption by its phenolic and aromatic fractions (PAFs)

AIM: Metabolomics in food science has been increasingly used over the last twenty years. Among the tools used for wine, qNMR has emerged as a powerful tool to discern wines based on environmental factors such as geographical origin, grape variety and vintage (Gougeon et al., 2019a).

Nowadays, the trend is to reduce the use of chemical inputs in the food sector, including in oenology. One of the inputs widely used in the wine making process are sulfites, for its several properties: antimicrobial and antioxidiant. This use isn’t without consequences on consumer’s health and environment, it can lead for example to allergic reactions and pollution. To limit the addition of chemical inputs, microbial alternatives are used. It consists to inoculate in grape must, a micro-organism able to inhibit the growth of the negative indigenous flora during the phase before the fermentation and to guarantee the sensory qualities of wines.

Proteins play a significant role in the colloidal stability and clarity of white wines [1]. However, under conditions of high temperatures during storage or transportation, the proteins themselves can self-aggregate into light-dispersing particles causing the so-called protein haze [2]. Formation of these unattractive precipitates in bottled wine is a common defect of commercial wines, making them unacceptable for sale [3]. Previous studies identified the presence of phenolic compounds in the natural precipitate of white wine [4], contributing to the hypothesis that these compounds could be involved in the mechanism of protein haze formation.

Identification and characterisation of terroirs depends on knowledge of environmental parameters, functioning of the grapevine and characteristics of the final product. A network of plots of Sauvignon blanc was delimited in commercial vineyards in proximity to weather stations at 20 localities and their viticultural and oenological response was monitored for a period of seven years. These experimental plots were further characterised with respect to climate, soil and topography.

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.