Soil and Climate Interactions with Grapevines

Proteins play a significant role in the colloidal stability and clarity of white wines [1]. However, under conditions of high temperatures during storage or transportation, the proteins themselves can self-aggregate into light-dispersing particles causing the so-called protein haze [2]. Formation of these unattractive precipitates in bottled wine is a common defect of commercial wines, making them unacceptable for sale [3]. Previous studies identified the presence of phenolic compounds in the natural precipitate of white wine [4], contributing to the hypothesis that these compounds could be involved in the mechanism of protein haze formation.

The observation of Earth by satellites has demonstrated the feasibility of establishing differences between plant species, from their spectral features. The reflectance spectrum of vine plants follows this trend, being possible to identify vineyards in satellite images, among other species.

The main objective of this study was to establish if beet sugar produces a different concentration of “fruity” volatile aroma compounds (VOCs), compared to cane sugar when used for second alcoholic fermentation of Auxerrois sparkling wines. Auxerrois base wine from the 2020 vintage was separated into two lots; half was fermented with cane sugar and half with beet sugar (both sucrose products and tested for sugar purity). These sugars were used in yeast acclimation (IOC 2007), and base wines for the second fermentation (12 bottles each). Base wines were manually bottled at the Cool Climate Oenology and Viticulture Institute (CCOVI) research winery. The standard chemical analysis took place at intervals of 0, 4 weeks, and 8 weeks post-bottling. Acidity and pH measurements were carried out by an auto-titrator. Residual Sugar (g/L) (glucose (g/L), fructose (g/L)), YAN (mg N/L), malic acid, and acetic acid (g/L) were analyzed by Megazyme assay kits. parameters were analyzed by Megazyme assay kits. Alcohol (% v/v) was assessed by GC-FID. VOC analysis of base wines, finished sparkling wines, as well as the two sugars in model sparkling wine solutions, was carried out by GC-MS. VOCs included ethyl octanoate, ethyl hexanoate, ethyl butanoate, ethyl decanoate, ethyl-2-methylbutyrate, ethyl-3-methylbutyrate, ethyl 2-methyl propanoate, ethyl 2- hydroxy propanoate, 1-hexanol, 2-phenylethan-1-ol, ethyl acetate, hexyl acetate, isoamyl acetate and 2-phenylethyl acetate.

The first demonstration of the interest of carbon isotope composition of sugars in grapevine, as an integrated indicator of vineyard water status, dates back to 2000 (Gaudillère et al., 1999; Van Leeuwen et al., 2001). Thanks to the isotopic discrimination of Carbon that takes place during plant photosynthesis, under hydric stress conditions, it is possible to accurately estimate the photosynthetic activity. Ever since, δ13C has been widely applied with success to zonation, terroir studies and vine physiology research, but is still not widely used by viticulturists. This is quite astonishing by considering the impact of global warming on viticulture and the need to improve water management, that would justify a widespread use of δ13C.
The lack of private laboratories proposing the analysis, the cost of the technology, as well as the long analytical delays, have been detrimental to its development. Some laboratories tried to overcome the analytical difficulties of isotopic analysis by using fourier transformed infrared spectroscopy, as a fast and cheap alternative to the official OIV method (IRMS). These claimed FTIR models have never been published or peer reviewed and cannot be considered robust. In this work, thanks to the recent acquisition of IRMS technology, new modern and robust applications of δ13C for viticulture are proposed. This includes the use of the analysis to make parcel separations at harvesting, the possibility to increase the precision of hydric stress cartography and the potential cost reduction when compared with Scholander pressure bomb analysis.

In this study we have compared the predictive ability of two phenological models: a traditional Thermal Time (TT) and a version of the more recently develop Unified Model (UM).