The use of δ¹³C as an indicator of water use efficiency for the selection of drought tolerant grapevine varieties

Volatile phenols from wildfire smoke are absorbed by wine grapes, resulting in undesirable smoky and ashy sensory attributes in the affected wine.[1] Unfortunately the severity of wildfires is increasing, particularly when grapes are ripening on the vine. The unwanted flavors of the wine prompted a need for solutions to prevent the uptake of smoke compounds into wine grapes. Films using cellulose nanofibers as the coating forming matrix were developed as an innovative means to prevent smoke phenols from entering Pinot noir grapes. Different film formulations were tested by incorporating low methoxy pectin or chitosan.

Among the Moscato grapes, Moscato Giallo is a winegrape variety characterized by a high content of free and glycosylated monoterpenoids, which gives very aromatic wines. The aromatic bouquet of Moscato Giallo is strongly influenced by the high concentration of linalool, geraniol, linalool oxides, limonene, α-terpineol, citronellol, HO-trienol, HO-diols, 8-Hydroxylinalool, geranic acid and β-myrcene, that give citrus, rose, and peach notes.

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).

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.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.