Exploring high throughput secondary trait phenomics to improve grapevine breeding

Red grape pomace can be an important source of polysaccharides, but currently they are little studied and even less with viable and environmental extraction processes (green extraction). These green techniques must be able to break the cell wall so that the compounds contained in the cells, including polysaccharides, are released and can have a great influence on extraction yields, the chemical structure of polysaccharides and applications in wines. Amongst the emerging green techniques most applied to the extraction of bioactive compounds, such as polysaccharides, high-power ultrasound (US) and enzyme-assisted extraction stand out.

Grapevine Red Blotch disease (RB) is a recently discovered disease that has become a major concern for the viticulture and winemaking industry in California, USA. The causal
agent, Grapevine Red Blotch Virus (GRBV) was identified in 2011 and its presence was confirmed in several states in the US, in Canada, and in Switzerland. It has been demonstrated that RB compromised the regulation of ripening by suppressing specific ripening events, altering the expression patterns of transcription factors and causing hormonal imbalances in Zinfandel.

In the context of sustainable viticulture, modern and efficient techniques to determine water status are required to optimize irrigation practices. Proximal techniques such as thermography and spectroscopy have shown promising results. When these techniques are incorporated into mobile systems is possible to evaluate the water status on-the-go, offering the possibility to generate variability maps. However, in most cases, complex protocols of data acquisition and analysis are required. Also, the inherent physiological behaviour of the plants under certain water stress conditions needs to be considered. Therefore, the aim of this study was to evaluate the effect of scion-rootstock combinations on the performance of a predefined plant-based method based on proximal near-infrared (NIR) spectroscopy.

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Considerable advances have been made in the chemical characterization of wine metabolites through its holistic study using both targeted and untargeted metabolomics approach. The metabolite pool is subject to an intense molecular dialogue which reinforces the wine complexity even after bottling.