Effects of different soil types and soil management on greenhouse gas emissions 

In the 19th century, devastating outbreaks of phylloxera (Daktulosphaira vitifoliae Fitch), almost brought European viticulture to its knees. Phylloxera does not only take energy in form of sugars from the vine, but also affects the up- and down- regulations of genes, acts as a carbon sink and reprograms the physiology of the grapevines, including nutrient uptake and the defense system [1]. A key trait of rootstocks is the ability to perform well under high lime conditions as about 30 % of the land surface has calcareous soil. Iron deficiency not only causes the well-known problems of lime-induced chlorosis and stunted growth, but also affects the entire plant metabolism.

Leaf removal in the fruit-zone has been employed to improve cluster light exposure and ventilation and therefore increase metabolite accumulation and reduce botrytis incidence in berries. When applied before flowering (early defoliation – ED), it can also decrease cluster compactness and regulate yield in high-yielding varieties. This study aimed to evaluate the impact of ED on the physiology and metabolism of Aragonez (syn. Tempranillo) berries along the ripening period. The experiment was set up in 2013 at a commercial vineyard located in the Lisbon winegrowing region.

Rootstocks were the first sustainable and environmentally friendly strategy to cope with a major threat for Vitis vinifera cultivation. In addition to providing Phylloxera resistance, they play an important role in protecting against other soil-borne pests, such as nematodes, and in adapting V. vinifera to limiting abiotic conditions. Today viticulture has to adapt to ongoing climate change whilst simultaneously reducing its environmental impact. In this context, rootstocks are a central element in the development of agro-ecological practices that increase adaptive potential with low external inputs. Despite the apparent diversity of the Vitis genus, only few rootstock varieties are used worldwide and most of them have a very narrow genetic background. This means that there is considerable scope to breed new, improved rootstocks to adapt viticulture for the future.

The wooden barrel is a key factor in enology, since wine chemical composition and sensory properties changes significantly in contact with the barrel[1]. Today’s highly competitive market constantly demands new differentiated products and wineries search innovations continuously.
Wood selection is crucial: barrels stability to keep constant their contribution and the result on products, and additional and differentiated wood contributions to impact their new products. Oak wood selection has traditionally been carried out using parameters such as specie, location and grain, however, it goes one step further nowadays. Large cooperage work with non-destructive techniques that allow classifying oak wood quickly and easily according to their organoleptic contribution[2].

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).