DOSAVIÑA® A new app for a more sustainable use of plant protection products in vineyard

Un programme de recherche concernant les facteurs naturels et humains des terroirs viticoles a été développé dans le vignoble A.O.C. de l’Anjou, sur une surface d’environ 30.000 Ha

Grapevine cultivation is threatened by the global warming, which combines high temperatures and reduced rainfall, impacting in wine quality and even plant survival. Breeding for varieties resilient to these challenges must address plant traits such as tolerance to supraoptimal temperatures and optimized water use efficiency while minimizing productivity and quality losses. Stomatal abundance (SA) determines the maximum leaf potential for transpiration and thus water loss and cooling. Since SA results from a developmental process during leaf emergence and growth, knowledge on the genetic control of this process would provide specific targets for modification.

Aims: In previous work, five indigenous Pichia kluyveri strains, GS1-1, FS-2-7, HS-2-1, C730 and C732, were isolated and selected from spontaneous fermented wines from Ningxia and Gansu. The aims of this study were to 1) evaluate resistance of these strains to environmental stressors that may restrict their growth and the progress of alcoholic fermentation; 2) Investigate their fermentation dynamics; 3) Characterise aroma profiles of Cabernet Sauvignon wines made from mixed cultures of P. kluyveri and Saccharomyces cerevisiae.

The OIV[i] defines terroir as a concept referring to an area in which collective knowledge of the interactions between the physical and biological environment (soil, topography, climate, landscape characteristics and biodiversity features) and vitivinicultural practices develops, providing distinctive wine characteristics. Those are perceptible in the taste of wine, which drives consumer preference and, therefore, wine’s value in the marketplace. Geographical indications (GI) are recognized regulatory constructs formalizing and protecting the nexus between wine taste and the terroir generating it. Despite considering updates, GIs do not consider the nexus as a dynamic one and do not anticipate change, namely of climate. Being climate a fundamental feature of terroir, it strongly impacts wine characteristics, such as taste. According to IPCC[ii], many widespread, rapid and unprecedented changes of climate occurred, some being irreversible over hundreds to thousands of years. Climatic shifts and atmospheric-driven extreme events have been widely reported worldwide. Recent climatic trends are projected to strengthen in upcoming decades, whereas extremes are expected to increase in frequency and intensity, forcing wines away from GI definitions. Geographical shifts of viticultural suitability are projected, often moving into regions and countries different from current ones. Some authors propose adaptation in viticulture, winemaking and product innovation. We show evidence of climate changing wine characteristics in the Douro valley, home of 270-year-old Port GI. We discuss herein resist or adapt stances for when climate changes the nexus between terroir and wine characteristics. Using the MED-GOLD[iii] dashboard, a tool allowing for easy visual navigation of past and future climates, we demonstrate how policymakers can identify future moments, throughout the 21st century under different emission scenarios, when GI specifications will likely need updates (e.g., boundaries, varieties) to reduce climate-change impacts.

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.