New Insights into Wine Color Analysis: A Comparison of Analytical Methods and their Correlation with Sensory Perception

Climate change imposes increasing restrictions and risks to Mediterranean viticulture. Extreme heat and drought stress events are becoming more frequent which puts in risk sustainability of Mediterranean viticulture. Moreover row crops e.g. grapevine for wine, are increasingly prone to the impact of more intense/longer exposure time to heat stress. The amplified effects of soil surface energy reflectance and conductance on soil-atmosphere heat fluxes can be harmful for leaf and berry physiology.

The interaction between mannoproteins and wine phenolic compounds is a subject of great interest as some studies show the possible impact in color stability and an improvement in the sensory characteristics namely the reduction of red wine astringency.

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.

Italy, like all the major vine-growing and wine-producing countries, has experienced a decline in wine export volumes in recent years.

In a context of reducing herbicide use, the most part of French vineyards are developing permanent grass cover crops on inter-rows alleys, while under the row chemical weeding remains the general case. The setting up of a controlled grass cover crop under the vine row could be a complementary alternative to mechanical weeding – which one is very restrictive – interesting from a technical and economical point of view. The present study aimed at assessing agronomic impacts of grass cover crop under the row in different climatic conditions and production objectives.