Oenological tannins to prevent Botrytis cinerea damage: reduction of laccase activity

Rio grande do sul is the main grape producing state in Brazil, with the largest wine-growing area, responsible by 90% of the national production of wines and grape juices. Serra Gaúcha is the main vitivinicultural region, where around 15% of the area is destined to produce wines from vitis vinifera L. grapes. This region presents high rainfall during the grape maturation cycle, a factor that leads to great risk of attacks by fungal pathogens. the use of resistant varieties can reduce the cost and quantity of spraying, improving wine quality, focusing on a sustainable vitiviniculture.

Aim: To investigate the impact of Geographical Indications (GI) of South Australia on the rootstock/scion-mediated methoxypyrazine accumulation within the rachis of Shiraz and Cabernet Sauvignon. 

The present paper reports the development of an optimized method for simultaneous analysis of
8 biogenic amines (Histamine, Methylamine, Ethylamine, Tyramine, Putrescine, Cadaverine, Phenethylamine, and Isoamylamine). It is based on a method developed by Gomez-Alonso et al. in 2007.

Storage temperature and bottling parameters are among the most important factors, which influence the development of wine after bottling. It is well studied that higher storage temperatures speed up chemical reactions and results in faster wine aging [1,2]. It is also known that higher SO2 level and lower oxygen content provide better protection and longer shelf-life for the wine. At the same time, the mechanisms of chemical transformations of wine aromas during the aging process are not fully understood. In particular, how oxidation reactions contribute to the transformations of varietal aroma compounds.In the present study [3], we investigated the development of Riesling wine depending on a series of bottling conditions, which differed in the free SO2 level in wine (low—13 mg/L, medium—24 mg/L, high—36 mg/L), CO2 treatment of the headspace.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.