Can yeast cells sense other yeasts beyond competition interactions?

‘Tempranillo Tinto’ is a black-berried Iberian cultivar that originated from a hybridization between cvs. ‘Benedicto’ and ‘Albillo Mayor’ [1]. Today, it is the third most widely grown wine grape cultivar worldwide with more than 200,000 hectares of vineyards mostly distributed along the Iberian Peninsula, where it is also known as ‘Cencibel’, ‘Tinta de Toro’, ‘Tinta Roriz’, and ‘Aragonez’, among other synonyms. Here, we quantified the intra-varietal genomic diversity in this cultivar through the study of 35 clones or ancient vines from seven different Iberian wine-making regions. A comparative analysis after Illumina whole-genome sequencing revealed the presence of 1,120 clonal single nucleotide variants (SNVs).

Xylotrechus arvicola (Coleoptera: Cerambycidae) is a pest in vineyards (Vitis vinifera) in the main Spain wine-producing regions with Protected Denomination of Origin (PDO). The action of the larvae, associated to the spreading of wood fungi, causes damage especially in important varieties of V. vinifera. X. arvicola females lay eggs concentrated in cracks or under the rhytidome in the wood vines, which allows the emerging larvae to get into the wood and make galleries inside the plant being then necessary to prune intensively or to pull up the bored plants (1). The objective of the study was to evaluate captures of X. arvicola insects in five varieties of V. vinifera in PDO León.

The nitrogen composition of the grapes directly affects the developments of alcoholic fermentation and influences the final aromatic composition of the wines. The aim of this study was to determine the effect and efficiency of foliar applications of urea on the nitrogen composition of grapes. This study was carried out during 2023 vintage and in the Chenin vineyard located in Estacion Experimental Mendoza (Argentina). Three urea concentrations 3, 6 and 9 Kg N/ha (C1, C2, and C3, respectively) and control (T) were applied in this vineyard at veraison.

The presence of undesirable compounds in wines, such as OTA, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity. To avoid these problems, the use of plant fibers may be an alternative, such as those from grape pomace[1] or other plant origins.

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).