Soil chemistry as a measure of the distinctiveness of american viticultural areas of the Columbia basin, USA

One of the major threats to viticulture is represented by fungal pathogens. Plasmopara viticola, an oomycete causing grapevine downy mildew, is one of the principal causes of grape production losses. The most efficient management strategies are represented by a combination of agronomical practices, fungicides’ applications, and use of resistant varieties. Plant resistance is conferred by the presence of resistance (R) genes. Opposed to them, susceptibility (S) genes are encoded by plants and exploited by pathogens to promote infection. Loss or mutation of S genes can limit the ability of pathogens to infect the host. By exploiting post-transcriptional gene silencing, known as RNA intereference (RNAi), it is possible to knock-down the expression of S genes, promoting plant resistance.

1,1,6-Trimethyl-1,2-dihydronaphthalene (TDN) is a controversial aroma component found in Riesling wines. It belongs to the family of C13-norisoprenoids and is mainly associated with kerosene/petrol notes. TDN can add complexity to the wine aroma at medium – low concentrations and deteriorate the wine bouquet when its content is high. No TDN aromas are usually perceived in young Riesling wines, but they can appear after several years of aging due to the gradual formation of TDN. Management of TDN in Riesling wines is an actual task, since global warming can promote formation of this compound and compromise the aromatic composition of wine. Therefore, the aim of the current work was, firstly, to study the sensory particularities of TDN in Riesling wine at various concentrations. Secondly, to investigate the ability of bottle closures to absorb (scalp) TDN from Riesling wine under various storage conditions. These studies also include the comparative assessment of our findings with previously published data. METHODS: sensory analysis, GC-MS (SBSE), HPLC,1H-NMR and other methods related to the synthesis and determination of TDN. RESULTS: First of all, the method of the synthesis of highly purified TDN (95% and 99.5%) was optimized [1].

Mousy off-flavor is one of the defects of microbial origin in wine. It is described as a particularly unpleasant defect reminiscent of rodent urine (a “dirty mouse cage”), and grilled foods such as popcorn, rice, crackers, and bread crust. Prior to the 2010s, mousiness was very uncommon but it has been becoming more frequent in recent years. It is often associated with an increase in pH as well as certain oenological practices, which tend to significantly decrease the use of sulfur dioxide.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Aims: The aims of this study were to (i) characterize bacterial and fungal communities in selected Australian vineyard soils and (ii) determine if the soil microbiome composition and diversity varied between different zones within a vineyard.