INTEGRAPE guidelines and tools: an effort of COST Action CA17111

Grapevines have traditionally been grown in semi-arid areas, but viticulture is now compromised by climate change. Therefore, it is necessary to implement environmentally friendly viticulture practices to adapt grapevines to current climatic conditions. In this context, organic mulches offer many benefits, such as reduced soil erosion and increased organic matter, soil water content and crop productivity. However, these practices must not compromise grape and wine quality. Therefore, the objective of this study was to evaluate the effect on wine physicochemical and phenolic composition and sensorial properties of different soil management practices on the vine row. Over four years, five soil treatments were examined in two different vineyards.

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.

Calcium (Ca) is an important nutrient for plants which plays key signaling and structural roles. It has been observed that exogenous Ca application favors the pectin accumulation and inhibition of polygalacturonase enzymes, minimizing fruit spoilage. Silicon (Si) is a non-essential element which has been found to be beneficial for improving crop yield and quality, as well as plant tolerance to diverse abiotic and biotic stress factors. The effect of Si supply to grapevine has been assessed in few investigations, which reported positive changes in grape quality and must composition.

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).

Enzymatic browning[1] is an oxidation process that occurs in many foods that increases the brown colour[2]. This problem is especially harmful in the wine industry[3]. especially when the grapes are infected by grey rot since this fung release the oxidative enzyme laccase[4]. In the particular case of red wines, the presence of laccase implies the deterioration of the red colour and can even cause the precipitation of the coloring matter (oxidasic haze)[5].