Improvement of sparkling wines production by a zoning approach in Franciacorta (Lombardy, Italy)

Anthocyanins are responsible for the red wine color and their ability to condense with tannins is considered as a contributor in astringency reduction. However, recent studies showed the possibility of anthocyanins to influence directly the in-mouth perception of wines.

Context and purpose of the study. `Grüner Veltliner´ is the most important Austrian white quality wine variety, which is mainly used to produce primary fruity wines.

The pinking is a phenomenon that can occur in white wine produced with white grape causing the color change from yellow to red-salmon hue. Even if its appearance is highly variable and dependent to the vintage, the wines from certain grape varieties, such as Sauvignon blanc, Chardonnay, Riesling and Trebbiano di Lugana, have been identified to be more susceptible to the pinking.

The evaluation of new grapevine genotypes regarding their potential to produce high quality wines is the time limiting factor in the process of grapevine breeding. Hence, the development of quality-related markers useable in marker-assisted selection (MAS) as well as in prediction models for this bottleneck trait will tremendously enhance breeding efficiency. In extensive studies a training set of a segregating white wine F1 population (150 F1 genotypes = POP150; `Calardis Musqué´ x `Villard Blanc´) was deeply phenotyped and genotyped for model development and QTL analysis.

Drought and heat waves deriving from climate change have been affecting grapevine plants and altering wine characteristics in the past years, and effects are expected to get worst. Innovative approaches to address this problem have been undertaken in several varieties, that consist in exploring intravarietal variability to identify genotypes that are tolerant to abiotic stress. Such is the case of the variety Arinto, where an experimental population of 165 clones installed according to a resolvable row-column design with 6 replicates, was scanned for several parameters, including surface leaf temperature (SLT). Linear mixed models were fitted to the data of the traits evaluated, and the empirical best linear unbiased predictors (EBLUPs) of genotypic effects for each trait were obtained as well as the coefficient of genotypic variation (CVG) and broad sense heritability.