Development and application of CRISPR/Cas in grapevine

The wine industry is currently shifting toward more sustainable production systems. There are many reasons for this as the interest of people over climate change and, consequently the wine consumer’s choice toward organic and biodynamic, reduced carbon-footprint, vegan and other environmentally friendly wines. While the viticultural effects of biodynamic and organic practices on wine grapes have been investigated, there is a lack in literature on the general effect on the final quality of wine

Wine quality is a complex concept determined by multiple factors, including vineyard management, winemaking operations, and the sensory perception of key attributes.

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Mannoproteins are released at the end of alcoholic fermentation due to yeast autolysis [1]. It has been described a positive effect of these molecules on lactic acid bacteria growth [2]. The main objective of this work was the characterization of different mannoproteins extracted from active dry yeast (ADY) and the assessment of their effect on Oenococcus oeni and malolactic fermentation (MLF).

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous real-field genetic pool Vitis vinifera cultivars by combining high-fidelity long-read sequencing (HiFi) and high‐throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar.