terclim by ICS banner
IVES 9 IVES Conference Series 9 International Congress on Grapevine and Wine Sciences 9 2ICGWS-2023 9 Model-assisted analysis of the root traits underlying RSA genotypic diversity in Vitis: a promising approach for rootstock selection?

Model-assisted analysis of the root traits underlying RSA genotypic diversity in Vitis: a promising approach for rootstock selection?

Abstract

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. Based on this principle, we provide here an overview of our original work on RSA phenotyping and model-assisted trait dissection in grapevine. First, we set up 2D imaging-based phenotyping tools and analysis pipelines for high-resolution quantification of root morphological and architectural characteristics in juvenile grapevines grown in different controlled conditions (hydroponics, rhizotrons and pots). Specific root descriptors (e.g. number of first-order roots, apical diameter, branching density, length of the unbranched apical zone, insertion angle…) were then measured to calibrate the Archisimple 3D RSA model [1] on a set of Vitis rootstock cuttings. We also investigated whether the model parameters were well conserved over time and under different environments. Finally, we characterized the genetic architecture of few parameters among the 138 individus of a mapping progeny derived from an interspecific cross between Vitis vinifera cv. Cabernet-Sauvignon × V. riparia cv. Gloire de Montpellier grown in the field for 2 years. Broad-sense heritability and QTLs analyses were carried out for model parameters and variables outputs with a consensus map, and compared with other QTLs obtained on classical used RSA descriptors. Results give new insights into the genetic control of RSA in grapevine rootstocks.

References:

1)  Pagès L. et al. (2014) Calibration and evaluation of ArchiSimple, a parsimonious model of the root system architecture. Ecol. Mod., 290: 76-84. DOI:10.1016/j.ecolmodel.2013.11.014

DOI:

Publication date: October 6, 2023

Issue: ICGWS 2023

Type: Poster

Authors

Larrey M, Tandonnet JP, Patin ER, Blois L, Marguerit E, de Miguel M, Saint Cast C, Vivin P

EGFV, University of Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, 33882 Villenave d’Ornon, France

Contact the author*

Keywords

root traits, root system architecture, phenotyping, 3D modelling, rootstock diversity

Tags

2ICGWS | ICGWS | ICGWS 2023 | IVES Conference Series

Citation

Related articles…

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

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).

Identification of a stable epi-allele associated with flower development and low bunch compactness in a somatic variant of Tempranillo Tinto

Grapevine cultivars are vegetatively propagated to preserve their varietal characteristics. However, spontaneous somatic variations that occur and are maintained during cycles of vegetative growth offer opportunities for the natural improvement of traditional grape cultivars. One advantageous trait for winegrowing is reduced bunch compactness, which decreases the susceptibility to pests and fungal diseases and favor an even berry ripening.

Effect of pH and ethanol on Lactiplantibacillus plantarum in red must fermentation: potential use of wine lees

Wine is the result of the alcoholic fermentation (AF) of grape must. Besides AF, wine can also undergo the malolactic fermentation (MLF) driven out by lactic acid bacteria (LAB). Among LAB, Oenococcus oeni and Lactiplantibacillus plantarum are the dominant species in wine. Even if O. oeni is the most common LAB undergoing MLF in wine, due to its high tolerance to wine conditions, L. plantarum can be used to undergo MLF in must. The moderate tolerance of L. plantarum to low pH and ethanol, may compromise the fermentative process in harsh wines.

Genetic study of wild grapevines in La Rioja region

Since the mid-1980s, several surveys have been carried out in La Rioja to search for populations of the sylvestris grapevine subspecies (Vitis vinifera L. subsp. sylvestris Gmelin). The banks of the Ebro River and its tributaries (Alhama, Cidacos, Leza, Iregua, Najerilla, Oja and Tirón rivers), as well as the surrounding vegetation of their valleys have been covered. So far, all the populations found are alluvial, forming part of the riparian vegetation of the Najerilla (the first reported population in La Rioja [1]), Iregua, and the vicinity of Oja valleys.

Exploring intra-vineyard variability with sensor- and molecular-based approaches 

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.