Outline for the définition of “Terroirs Viticoles application to the area of El AIjarafe (Seville, Spain)

The Institut Français De La Vigne Et Du Vin (IFV) is conducting many experiments on innovative winegrowing practices, which are emerging in companies in the sector, or which are still at the R&D stage for agricultural suppliers. The purpose of these practices may be to reduce environmental impact, to adapt vineyards to climate change, or to achieve other technical, economic or social aims. Whatever the objective, it is necessary to verify the relevance of these new practices, and in particular their environmental relevance, i.e. That at the very least, the changes in practices do not increase the environmental impact of the technical itineraries.

Winemakers are increasingly experimenting with new techniques, such as spontaneous fermentation, prolonged yeast contact, higher pH, minimal sulphur dioxid, filtration and clarification or oxidative ageing. Along with this, the risk of microbial spoilage increases, and so the off-flavour mousiness, long time underestimated, is becoming more frequent. Characteristic of the mousy off-flavour is the delayed perception after swallowing the wine. After a few seconds the flavour appears, reminiscent of a dirty mouse cage. There are three known compounds that cause mousy off-flavor: 2-ethyltetrahydropyridine, 2-acetyltetrahydopyridine, and 2-acetylpyrroline. Yeasts such as Dekkera/Brettanomyces and heterofermentative lactic acid bacteria like Lactobacillus hilgardii can release these compounds.

By the end of this century, up to 90% of traditional viticulture regions in the Mediterranean, including Sicily, are projected to face extinction due to escalating climate challenges such as severe droughts, heatwaves, and unseasonal rains.

The chemistry of wine is particularly complex due to biochemical and chemical interactions that significantly modify its organoleptic characteristics and stability over time. Aging on lees is a well-known practice during which various compounds are released, ensuring wines oxidative stability and its overall sensory quality [1,2].

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).