Grapevine sugar concentration model in the Douro Superior, Portugal

El tema que me corresponde tratar en esta mini conferencia sobre “Caracterización vitivinícola de las Malvasías en Canarias”, es por razones obvias la parte que atañe a la Isla de La Palma.

The zone in which the Cesanese vines are cultivated has a secular tradition of red wine­making. This zone is placed between the Simbruini mountains slopes and the surrounding hills and has pedologicai variability but a very homogeneous microclimate.

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.

La caratterizzazione della frazione volatile aromatica dei vini attraverso l’analisi quali­quantitativa dei diversi composti, ha portato corne primo risultato la netta differenziazione delle annate in prova.

Wine quality depends on grape biochemical constituents, including sugars, organic acids, amino acids, and bound and free aroma compounds, which are influenced by vineyard location and environmental factors such as temperature and precipitation [1].