Caratterizzazione delle produzioni vitivinicole dell’ area del Barolo: un’esperienza pluridisciplinare triennale (1)

The accession Criolla Chica Nº2 (CCN2) is catalogued as a floral mutation of cultivar Criolla Chica (synonym for cv. Listán Prieto). Contrary to what is observed in hermaphrodite-cultivated varieties like Criolla Chica, CCN2 exhibits a prevalence of masculinized flowers. Aiming to study the incidence and phenotypical implications of this mutation, CCN2 plants were deeply studied using Criolla Chica ‘Ballista’ (CCBA) as control plants. For each CCN2 plant, two inflorescences per shoot were sampled and segmented into proximal, mid and distal positions, relative to the pedicel. Flowers were observed through magnifying lens and classified according to OIV151 descriptor.

During wine production process high attention to the microbiological control from fermentation of the grape must to bottling is necessary. In fact, control of the indigenous microflora of the grape ensures correct fermentation activity of the inoculated starter, while control of the microorganisms in the finished wine is essential to prevent wine spoilage and to ensure the dominance of the desired bacteria when malolactic fermentation is required (Mas and Portillo, 2022).

Dividing agrarian exploitations into microfields is a problem that influences the modern viticulture in a very important way. The aim of this work is the study of the influence of Geology and Geomorphology in agricultural structures

Pesticide residues in Austrian wines have so far been poorly documented. In 250 wines, 33 grape musts and 45 musts in fermentation, no limit values were exceeded, but in some cases high lev-els (>0.100 mg/l) of single residues were found, meaning that a reduction of these levels before bottling could make sense. In the course of this study, a white and a red wine were spiked with a mix of 23 pesticide residues from the group of fungicides (including botryticides), herbicides and insecticides. The influence of the following treatments on residue concentrations and volatile profiles were investigated: two activated charcoal products, a bentonite clay, two commer-cial mixed fining agents made of bentonite and charcoal, two yeast cell wall products, and a plant fiber-based novel filter additive. The results of this study show that all the agents tested reduced both residues and aromavolatile compounds in wine, with activated charcoal having the strongest effect and bentonite the weakest. The mixed agents and yeast wall products showed less aroma losses than charcoal products, but also lower residue reduction. Plant fibers showed good reduction of pesticides with moderate aroma damage, but these results need to be con-firmed under practical conditions.

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.