Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Color is a key quality trait for grape berry and the producing wines. Berry color of red genotypes is mainly determined by the quantity and composition of anthocyanins accumulated in the skin and/or pulp. Both genetic and environmental factors could influence the quantity and composition of anthocyanins, while the underlying mechanisms are not fully clear. To explore the mechanisms underlying the diversity of anthocyanin accumulation in grape berry, we compared two grapevine genotypes showing distinct sensitivities to ABA-induced anthocyanin biosynthesis, where one genotype showed minor responses to exogenous ABA application while the other showed significant increase in anthocyanins after exogenous ABA application.

The present study was performed in a traditional winery located in the viticultural area of Brunello di Montalcino, Siena, Italy, in the vintage 2015. Actually, in this winery Sangiovese grape musts are fermented in large oak barrels by a single strain of Saccharomyces cerevisiae previously isolated in the same winery. Pumping over operations are carried out once or twice a day until the end of alcoholic fermentations. The aim of this work was to investigate on the oenological properties of Sangiovese wine produced with the traditional winemaking process adopted by the winery under study obtained from the fermentation of whole berries compared to that from crushed grape must. In particular, two lots of 65q of Sangiovese grapes from the same 3ha vineyard were vinified in 150hL oak barrels.

Climate change significantly impacts vine and grape physiology, leading to changes in wine composition, including reduced titratable acidity, elevated ethanol content, and higher pH levels [1].

Full understanding of grapevine responses to variable soil resources requires
assessing the grapevine root system. Grapevine root systems are expansive and examining deep roots (i.e., >40 cm)
is particularly important in conditions where grapevines increase reliance on deep soil resources, such as drought
or plant competition. Traditional methods of assessing roots rely on morphological traits associated specific
functions (e.g., root color, diameter, length), while recent methodological advances allow for estimating root
function more directly (e.g., omics). Yet, the potential of applying refined methods remains underexplored for roots
at deep depths.

Pomace is one of the main residues generated by the wine industry and represents an environmental problem. Currently, there is a growing interest in the revaluation of these products because different bioactive compounds can be obtained from them, such as polyphenols, grape seed oils and polysaccharides. Red grape pomace can be an important source of polysaccharides, but they are currently little studied and even less with viable and environmental extraction processes (green extraction), such as flash extraction. The residual amount of the fraction rich in pectin (residual pulp) and component rich in hemicellulose in the pomace and the strength of association of the pectin with the cellulose-xyloglucan network depend on the degree of extractability of the polysaccharides in red winemaking and on the winemaking conditions.