Characterizing the effects of nitrogen on grapevines with different scion/rootstock combinations: agronomic, metabolomic and transcriptomic approaches

Polyphenols are present in a wide variety of plants and foods such as tea, cacao and grape1. An important sub-class of these compounds is the flavanols present in grapes and wines as monomers (e.g (+)-catechin or (-)-epicatechin), or polymers also called condensed tannins or proanthocyanidins. They have important antioxidant properties2 but their biosynthesis remains partly unknown. Some recent studies have focused on the role of glycosylated intermediates that are involved in the transport of the monomers and may serve as precursors in the polymerization mechanism3, 4. The global objective of this work is to identify flavanol glycosides in grapes or wines, describe their structure and determine their abundance during grape development and in wine.

Vitis vinifera L. is the most widely cultivated Vitis species which includes numerous cultivars. Owing to their superior quality of grapes, these cultivars were long considered the only suitable for the production of fine wines. However, the lack of resistance genes in V. vinifera against major grapevine pathogens, requires for its cultivation frequent spraying with large amount of fungicides. Thus, the search for alternative and more sustainable methods to control the grapevine pathogens have brought the breeders to focus their attention on other Vitis species. In fact, wild Vitis genotypes present multiple resistance traits against pathogens, such as powdery mildew, downy mildew and phylloxera.

Yeast cells possess a cell wall comprising primarily glycoproteins, mannans, and glucan polymers. Several yeast phenotypes relevant for fermentation, wine processing, and wine quality are correlated with cell wall properties. To investigate the effect of wine fermentation on cell wall composition, a study was performed using mid-infrared (MIR) spectroscopy coupled with multivariate methods (i.e., PCA and OPLS-DA). A total of 40 yeast strains were evaluated, including Saccharomyces strains (laboratory and industrial) and non-Saccharomyces species. Cells were fermented in both synthetic MS300 and Chardonnay grape must to stationery phase, processed, and scanned in the MIR spectrum.

Malolactic fermentation (MLF) is a secondary step in the vinification process and it follows alcoholic fermentation (AF) which is predominantly carried out by Saccharomyces cerevisiae. These two processes result in the degradation of metabolites to produce secondary metabolites which also contribute to the final wine flavour and quality. AF results in the production of ethanol and carbon dioxide from sugars and MLF stems from the degradation of L-malic acid (a dicarboxylic acid) to L-lactic acid (a monocarboxylic acid). The latter process results in a smoother texture as the acidity of the wine is reduced by the process, it also adds to the flavour complexity of the wine.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.