HPLC and SEC analysis on the flavonoids and the skin cell wall material of Merlot berries reveals new insights into the study of the phenolic maturity

The aim of this work was to analyze the variability in grape composition of the Tempranillo cultivar related to climatic conditions, in La Mancha Designation of Origin. Grape composition (sugar content, total acidity, pH, malic acid, and total and extractable anthocyanins) recorded during ripening, were analysed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The relationships between grape parameters with climatic variables related to temperature and to water deficits, referring different periods between phenological events along the growing cycle, were evaluated using regression analysis. High variability in grape composition was observed in the period analysed. Total acidity varied between 3.7 and 7.3 gL-1 while malic acid varied between 1.2 and 4 gL-1. The extractable anthocyanins ranged between 526 and 972 mgL-1, and total anthocyanins ranged between 922 and 1388 mgL-1, being the lowest values recorded in the hottest year (2017). Total acidity decreased 0.77 gL-1 for an increase of 100 GDD, while malic acid decrease in 0.42 gL-1 for the same GDD increase, being the period between veraison and harvest the one that seemed to have higher influence on acidity. In addition, it was confirmed that increasing water deficits decreased acidity. Total and extractable anthocyanins increased in about 210 and 105 mgL-1, respectively, with an increase of 100 GDD from veraison to harvest, and the increase in water deficits favour the increase of anthocyanins, both total and extractable anthocyanins. Total and extractable anthocyanins concentration increased in 35 and 22 mgL-1 per an increase of 10 mm in the water deficit. These results can be of interest to understand the potential changes that grapes composition may suffer under future warmer climates.

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.

AIM: Vitis vinifera L. cv. Moscato includes different varieties, mainly white grapes with a medium-sized berry, spheroidal or slightly flattened in shape, yellow greenish color which becomes golden yellow or amber when exposed to the sun. Moscato varieties are mainly used for the production of sweet aromatic wines

According to the Food and Agriculture Organisation (FAO), 75.866 km2 of the world is dedicated to grape cultivation. About 71.0% of the world’s grape production is destined for winemaking, 27.0% for consumption as fresh fruit and 2.0% as raisin. Grape production is mainly hindered by fungal infections, that can develop both in field and post-harvest.

Soil and climate of 3 vineyards have been characterised in order to determine their influence on grape quality. These vineyards are located in Conca de Barberà (Catalonia, NE Spain) and belong to Cabernet sauvignon and Grenache noir cultivars. All 3 plots are very close, so only interannual climatic data of the nearest meteorological station have been considered.