Development and application of CRISPR/Cas in grapevine

Aim: In recent times the export of Beaujolais wines has been jeopardised due to a limit of manganese content (Mn) in wine implemented by China (2 mg/L), related to suspicions of potassium permanganate fraud. Nevertheless, soil Mn content may be high in some soil types in Beaujolais. The aim of this study was to improve knowledge of manganese transfer from soil to vine and wine because data on this subject is scarce.

The integration of sensor systems in viticulture is significantly improving vineyard management by enabling faster, comprehensive crop data collection across the entire vineyard, supporting more informed viticultural decision-making, and as a result promoting sustainability.

Tempranillo is the most widely grown red grapevine variety in Spain, currently representing 42% of the total number of red varieties and 21% of the total vineyard area. Due to the economic importance that this variety represents in Spanish viticulture, in some areas where it is traditionally grown, there is a special concern about the viability of the future growing of this variety is being compromised by the climate change effects.

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.

Climate change and rising temperatures present a substantial challenge to viticulture, intensifying summer heat stress and accelerating berry ripening.