Reconocimiento geoedafológico para la zonificación vitivinícola de la D.O. Montilla-Moriles

Wine viticulture, being firmly linked to the vine-terroir relationship, has always encountered significant bottlenecks to genetic innovation. Nonetheless, the development of new breeding strategies leading to the selection of stress resilient genotypes is urgent, especially in viticulture, where it would allow reducing the use of chemical treatments adopted to control fungal diseases. Genome editing represents an extremely promising breeding technique. Unfortunately, the well-known recalcitrance of several wine grape cultivars to in vitro regeneration strongly limits the exploitation of this approach, which to our knowledge has so far been developed on table grape genotypes with high regeneration potential.

 The manipulation of the genetic basis controlling grapevine adaptation and phenotypic plasticity can be performed either by classical genetics or biotechnologies.

Dans la tradition classique, les vins mousseux sont le produit d’assemblage des vins d’origine différent. La choix de la typologie du moussage (brut, extra-brut, dosage zéro, etc.) généralement est une conséquence des résultats organoleptiques atteints à la fin de le période d’affinement en bouteille.

Wine grapes breeding has been concentrating a lot of efforts within the grape research community over the last decade. The quick phenotyping of genotype quality traits including aroma composition remains challenging. Selected Ion Flow Tube Mass Spectrometry (SIFT-MS), a technology first available in 2008 and developing rapidly, could be particularly valuable for this usage. The aims of this study were i) to use SIFT-MS, to analyze the whole volatilome from different grape varieties, ii) to assess the ability of this technology to discriminate varieties according to their grape aroma composition, and iii) to study the stability of SIFT-MS signal over maturation to define a sampling strategy.

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.