Characterization of non-cultivated wild grapevines in Extremadura (Spain) 

Reducing sugar accumulation in grape (Vitis vinifera L.) berries may be a way to mitigate the effect of climate change. Managing canopy and crop load is an effective way to do so, however, reducing canopy size has been demonstrated to induce undesirable effects on anthocyanins. The aim of this study was to test if an application of exogenous ABA on the grape berries of defoliated vines (⅔ of the leaves removed) can result in slower sugar accumulation while maintaining grape and wine quality. An experiment with defoliation and exogenous ABA application on directly on clusters (factorial design 2×2) was performed with ‘Tempranillo’ fruit-bearing cuttings.

Traditional drought tolerant varieties such as Cabernet Sauvignon, Monastrell, and Syrah [1], have been used as parents in the grapevine breeding program initiated by the Instituto Murciano de Investigación y Desarrollo Agrario y Medioambiental (IMIDA) in 1997 [2]. This work presents the results of evaluating three new genotypes obtained from crosses between ‘Monastrell’ and ‘Cabernet Sauvignon’ (MC16 and MC80) and between ‘Monastrell’ and ‘Syrah’ (MS104), comparing their performance under conditions of water scarcity and high temperatures with that of their respective parental varieties. For this purpose, the six genotypes were cultivated under controlled irrigation conditions (60% ETc) and rainfed conditions.

Controlling the development of the bacterial population during the winemaking process is essential for obtaining correct wines[1]. Carbonic Maceration (CM) wines are recognised as high-quality young wines. However, due to its particularities, CM winemaking implies a higher risk of bacterial growth: lower SO2 levels, enrichment of the must in nutrients, oxygen trapped between the clusters… Therefore, wines produced by CM have slightly higher volatile acidity values than those produced by the destemming/crushing method[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).

The projected rise in mean air temperatures together with the frequency, intensity, and length of heat waves in many wine-growing regions worldwide will deeply impact grape berry development and quality. Several studies have been conducted and a large set of molecular data was produced to better understand the impact of high temperatures on grape berry development and metabolism[1]. According to these data, it is highly likely that the metabolomic dynamics could be strongly modulated by heat stress (HS).