Cargando…

LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci

The strong societal demand to reduce pesticide use and adaptation to climate change challenges the capacities of phenotyping new varieties in the vineyard. High-throughput phenotyping is a way to obtain meaningful and reliable information on hundreds of genotypes in a limited period. We evaluated tr...

Descripción completa

Detalles Bibliográficos
Autores principales: Chedid, Elsa, Avia, Komlan, Dumas, Vincent, Ley, Lionel, Reibel, Nicolas, Butterlin, Gisèle, Soma, Maxime, Lopez-Lozano, Raul, Baret, Frédéric, Merdinoglu, Didier, Duchêne, Éric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655830/
https://www.ncbi.nlm.nih.gov/pubmed/38026470
http://dx.doi.org/10.34133/plantphenomics.0116
_version_ 1785147990828122112
author Chedid, Elsa
Avia, Komlan
Dumas, Vincent
Ley, Lionel
Reibel, Nicolas
Butterlin, Gisèle
Soma, Maxime
Lopez-Lozano, Raul
Baret, Frédéric
Merdinoglu, Didier
Duchêne, Éric
author_facet Chedid, Elsa
Avia, Komlan
Dumas, Vincent
Ley, Lionel
Reibel, Nicolas
Butterlin, Gisèle
Soma, Maxime
Lopez-Lozano, Raul
Baret, Frédéric
Merdinoglu, Didier
Duchêne, Éric
author_sort Chedid, Elsa
collection PubMed
description The strong societal demand to reduce pesticide use and adaptation to climate change challenges the capacities of phenotyping new varieties in the vineyard. High-throughput phenotyping is a way to obtain meaningful and reliable information on hundreds of genotypes in a limited period. We evaluated traits related to growth in 209 genotypes from an interspecific grapevine biparental cross, between IJ119, a local genitor, and Divona, both in summer and in winter, using several methods: fresh pruning wood weight, exposed leaf area calculated from digital images, leaf chlorophyll concentration, and LiDAR-derived apparent volumes. Using high-density genetic information obtained by the genotyping by sequencing technology (GBS), we detected 6 regions of the grapevine genome [quantitative trait loci (QTL)] associated with the variations of the traits in the progeny. The detection of statistically significant QTLs, as well as correlations (R(2)) with traditional methods above 0.46, shows that LiDAR technology is effective in characterizing the growth features of the grapevine. Heritabilities calculated with LiDAR-derived total canopy and pruning wood volumes were high, above 0.66, and stable between growing seasons. These variables provided genetic models explaining up to 47% of the phenotypic variance, which were better than models obtained with the exposed leaf area estimated from images and the destructive pruning weight measurements. Our results highlight the relevance of LiDAR-derived traits for characterizing genetically induced differences in grapevine growth and open new perspectives for high-throughput phenotyping of grapevines in the vineyard.
format Online
Article
Text
id pubmed-10655830
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher AAAS
record_format MEDLINE/PubMed
spelling pubmed-106558302023-11-17 LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci Chedid, Elsa Avia, Komlan Dumas, Vincent Ley, Lionel Reibel, Nicolas Butterlin, Gisèle Soma, Maxime Lopez-Lozano, Raul Baret, Frédéric Merdinoglu, Didier Duchêne, Éric Plant Phenomics Research Article The strong societal demand to reduce pesticide use and adaptation to climate change challenges the capacities of phenotyping new varieties in the vineyard. High-throughput phenotyping is a way to obtain meaningful and reliable information on hundreds of genotypes in a limited period. We evaluated traits related to growth in 209 genotypes from an interspecific grapevine biparental cross, between IJ119, a local genitor, and Divona, both in summer and in winter, using several methods: fresh pruning wood weight, exposed leaf area calculated from digital images, leaf chlorophyll concentration, and LiDAR-derived apparent volumes. Using high-density genetic information obtained by the genotyping by sequencing technology (GBS), we detected 6 regions of the grapevine genome [quantitative trait loci (QTL)] associated with the variations of the traits in the progeny. The detection of statistically significant QTLs, as well as correlations (R(2)) with traditional methods above 0.46, shows that LiDAR technology is effective in characterizing the growth features of the grapevine. Heritabilities calculated with LiDAR-derived total canopy and pruning wood volumes were high, above 0.66, and stable between growing seasons. These variables provided genetic models explaining up to 47% of the phenotypic variance, which were better than models obtained with the exposed leaf area estimated from images and the destructive pruning weight measurements. Our results highlight the relevance of LiDAR-derived traits for characterizing genetically induced differences in grapevine growth and open new perspectives for high-throughput phenotyping of grapevines in the vineyard. AAAS 2023-11-17 /pmc/articles/PMC10655830/ /pubmed/38026470 http://dx.doi.org/10.34133/plantphenomics.0116 Text en Copyright © 2023 Elsa Chedid et al. https://creativecommons.org/licenses/by/4.0/Exclusive licensee Nanjing Agricultural University. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Chedid, Elsa
Avia, Komlan
Dumas, Vincent
Ley, Lionel
Reibel, Nicolas
Butterlin, Gisèle
Soma, Maxime
Lopez-Lozano, Raul
Baret, Frédéric
Merdinoglu, Didier
Duchêne, Éric
LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title_full LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title_fullStr LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title_full_unstemmed LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title_short LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci
title_sort lidar is effective in characterizing vine growth and detecting associated genetic loci
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655830/
https://www.ncbi.nlm.nih.gov/pubmed/38026470
http://dx.doi.org/10.34133/plantphenomics.0116
work_keys_str_mv AT chedidelsa lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT aviakomlan lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT dumasvincent lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT leylionel lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT reibelnicolas lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT butterlingisele lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT somamaxime lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT lopezlozanoraul lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT baretfrederic lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT merdinogludidier lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci
AT ducheneeric lidariseffectiveincharacterizingvinegrowthanddetectingassociatedgeneticloci