Investigating the Ancient Egyptian wines: The wine jars database

‘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).

Crops are facing increasing biotic and abiotic stress pressures due to global changes. However, trade-off mechanisms between these stresses and the underlying physiological processes are still poorly understood, especially in perennial crop species. To better understand these trade-offs, we studied the effect of drought on grapevine (Vitis vinifera) physiology and esca-related wood fungal communities. Esca is a vascular disease caused by a community of wood-infecting pathogenic fungi, and characterized by trunk necrosis, leaf scorch symptoms, yield losses, and mortality.

In order to avoid the loss of grapevine intra-varietal diversity of DOCa Rioja grape varieties, Regional Government of La Rioja established a germplasm bank with more than 1.600 accessions, whose origin lies in the prospecting and sampling of ancient vineyards located throughout the whole region. 30 clones of Tempranillo and 13 clones of Graciano were preselected and multiplied in a new vineyard for further observations. The aim of this work is to describe the first results from the physiological characterization by an optical sensor of these preselected clones, which constitute the base of a new clonal selection that aims to increase the range of available certified clones and to improve the adaptation of these varieties to future objectives and environmental conditions.

The characterization of chemical compounds related with quality of grape must and wine is relevant for the viticulture and enology fields. Analytical methods used for these analyses require expensive instrumentation as well as a long sample preparation processes and the use of chemical solvents. On the other hand, near-infrared (NIR) spectroscopy technique is a simple, fast and non-destructive method for the detection of chemical composition showing a fingerprint of the sample. It has been reported the potential of NIR spectroscopy to measure some enological parameters such as alcohol content, pH, organic acids, glycerol, reducing sugars and phenolic compounds.

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).