Physico-chemical properties of vine pruning residues with potential as enological additive

Drought is one of the main challenges for viticulture in the context of global change. The choice of rootstock could be leveraged for vineyard adaptation to drought as we can improve plant performance without modifying the scion variety. However, most of the existing rootstocks, selected over a century ago, have a narrow genetic background which could compromise their adaptive potential.

Implementing alternative grapevine systems that incorporate sustainable strategies and innovative farming practices is essential. However, we lack tools for measuring the impact of these new practices on the overall sustainability of vineyards. DEXi PM Vigne (Gary et al., 2015) is a tool developed for ex ante assessment of the sustainability of grapevine cropping systems, from the plot to the farm scale. In the present study, we focused on implementing new strategies of integrated crop protection management with limited pesticide use in vineyards.

Inter-row soil tillage in vineyards, stimulates vigor and production due to the absence of competition for water and nutrients, however negatively affects organic matter content, soil erosion, and compaction, resulting in reduced fertility. In this study, we investigated the effects of different cover crop management approaches, including cultivation type and termination timing, on the physiological and productive responses of a Glera vineyard.
The experimental trial was conducted in Precenicco (UD) from 2019 to 2021. A commercial mixture for autumn cover cropping was sown in alternating rows, and the sowing pattern was changed each year.

Antagonistic yeasts applied to wine grapes must be compatible with the thereafter winemaking process, avoiding competition with the fermentative Saccharomyces cerevisiae or affecting wine flavour. Therefore, fifteen epiphytic yeasts (6 Metschnikowia sp., 6 Hanseniaspora uvarum, 3 Starmerella bacillaris) previously selected for its biocontrol ability against Alternaria on wine grapes were evaluate for possible competition with S. cerevisiae by the Niche Overlap Index (NOI) employing YNB agar media with 10 mM of 17 different carbonate sources present in wine grapes (proline, asparagine, alanine, glutamic acid, tirosine, arginine, lisine, methionine, glicine, malic acid, tartaric acid, fructose, melibiose, raffinose, rhamnose, sucrose, glucose).

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).