A DNA-free editing approach to help viticulture sustainability: dual editing of DMR6-1 and DMR6-2 enhances resistance to downy mildew 

The wine industry currently relies on a limited number of grapevine cultivars, comprised of numerous clones with slight differences in their viticultural, oenological, or stress-tolerance traits.

Microbiomes have crucial roles in maintaining life on Earth, and their functions drive human, animal, plant and environmental health. The microbiome research landscape is developing rapidly and is performed in many different science fields using similar concepts but mostly one (eco)system at-a-time. Thus, we are only starting to unravel and understand the interconnectedness of microbiomes across the (eco)systems.

Grapevines have traditionally been grown in semi-arid areas, but viticulture is now compromised by climate change. Therefore, it is necessary to implement environmentally friendly viticulture practices to adapt grapevines to current climatic conditions. In this context, organic mulches offer many benefits, such as reduced soil erosion and increased organic matter, soil water content and crop productivity. However, these practices must not compromise grape and wine quality. Therefore, the objective of this study was to evaluate the effect on wine physicochemical and phenolic composition and sensorial properties of different soil management practices on the vine row. Over four years, five soil treatments were examined in two different vineyards.

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.

In this video recording of the IVES science meeting 2021, Fulvio Mattivi (Fondazione Edmund Mach, Centro Ricerca ed Innovazione, San Michele all’Adige, Italy) speaks about the effects of water deficit on secondary metabolites in grapes and wines. This presentation is based on an original article accessible for free on OENO One.