Applicability of spectrofluorometry and voltammetry in combination with machine learning approaches for authentication of DOCa Rioja Tempranillo wines

The growing interest in minority grape varieties is due to their potential for adaptation to global warming and their oenological capabilities. However, the cultivation of these varieties has often been limited due to their low economic efficiency. One such example is Maturana Blanca, a recently recovered and authorized minority grape variety in the DOCa Rioja region, known for its remarkable oenological potential but low productivity. This study aimed to increase the yield of Maturana Blanca by implementing the vertical cordon training system, which allowed for a higher number of buds per plant and an increased cluster count per vine.

Several studies have tried to develop different methods to study the photodegradation of wine in an accelerated way, trying to elucidate the effect of light on the wine compounds[1]. In a previous study, our team developed a chamber that speeds up the photodegradation of rosé wine[2]. In the present work we have tried to establish a correlation between irradiation times in accelerated conditions and the natural exposure to the cycles of light that usually exist in markets or at home.

A large population of vines of the Mandón minority red variety (synonymous with Garró) has been located in old vineyards of the D.O. Arribes (Zamora and Salamanca) to conserve and recover this minority variety. The wines made with this variety are characterized by their good structure and color, interesting harmony, an excellently low pH, with high acidity, as well as complex aromas of blue fruits and a marked and expressive minerality.

In temperate climates, such as in the North of Spain, the use of irrigation in the vineyard has not been required, due to the usual rainfall from June to August. In some large vineyards, irrigation management has been carried out, based on occasional support irrigation, or for the application of nutrients (fertigation). Currently it is necessary to implement decision support models to manage irrigation water in real time and avoid misuse of a scarce resource. Moreover, quality standards must be achieved, as in the previous rainfed viticulture.

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.