Optimization of in vitro establishment of grapevine varieties for fast micropropagation 

Climate changes are impacting viticultural regions throughout the world with temperature increases being most prevalent.1 These changes will not only impact the regions capable of growing grapes, but also
the grapes that can be grown.2 As temperatures rise the growing degree days increase and with it the sugar accumulation within the berries and subsequent alcohol levels in wine. Consequently, viticultural
practices need to be examined to decrease the levels of sugars.

The way to manage the vineyard soils has certainly changed in Spain during the last years. Traditionally, the vineyards were tilled, but this growing technique has been replaced in some vineyards by the bare soil with herbicide

Aim of the study was to investigate the metabolomic differences between Chilean Cabernet Sauvignon wines, divided according to their quality in two main groups: “Varietal” and “Premium”, and to point out metabolites tentative markers of their chemical signature and sensorial quality. Initially, 150 (50 x 3 biological replicates) experimental wines were produced by the same semi-industrial process, which covered 8 different Chilean valleys. The wine classification made by experts, divided the wines into two major groups (“Varietal” and “Premium”) and four subgroups (two for each major group). All the samples were analyzed according to a robust LC-MS based untargeted work-flow (Arapitsas et al 2018), and the proposed minimum reporting standards for chemical analysis of the Metabolomics Standards Initiative (Sumner et al 2007)

Context and Purpose of the Study. PIWI grape varieties (Pilzwiderstandsfähig, fungus-resistant) offer innovative solutions for sustainable viticulture by addressing environmental challenges faced by traditional Vitis vinifera.

The assessment of wine authenticity is of great importance for consumers, producers and regulatory agencies to guarantee the geographical origin of wines and grape variety as well. Since mid-infrared (MIR) spectroscopy with chemometrics represent a suitable tool to ascertain the wine composition, including features associated with the polyphenolic compounds, the aim of this study was to generate MIR spectra of red wines to be exploited for classification of red wines based on the relationship between grape variety and wine composition. Several multivariate data analyses were used, including Principal Component Analysis (PCA), Discriminant Analysis (DA), Support Vector Machine (SVM), and Soft Intelligent Modelling of Class Analogy (SIMCA).