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Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images

The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies light interception. Previous studies have indicated how maize ge...

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Autores principales: Serouart, Mario, Lopez-Lozano, Raul, Daubige, Gaëtan, Baumont, Maëva, Escale, Brigitte, De Solan, Benoit, Baret, Frédéric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204743/
https://www.ncbi.nlm.nih.gov/pubmed/37228515
http://dx.doi.org/10.34133/plantphenomics.0046
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author Serouart, Mario
Lopez-Lozano, Raul
Daubige, Gaëtan
Baumont, Maëva
Escale, Brigitte
De Solan, Benoit
Baret, Frédéric
author_facet Serouart, Mario
Lopez-Lozano, Raul
Daubige, Gaëtan
Baumont, Maëva
Escale, Brigitte
De Solan, Benoit
Baret, Frédéric
author_sort Serouart, Mario
collection PubMed
description The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies light interception. Previous studies have indicated how maize genotypes may adapt leaves orientation to avoid mutual shading with neighboring plants as a plastic response to intraspecific competition. The goal of the present study is 2-fold: firstly, to propose and validate an automatic algorithm (Automatic Leaf Azimuth Estimation from Midrib detection [ALAEM]) based on leaves midrib detection in vertical red green blue (RGB) images to describe leaves orientation at the canopy level; and secondly, to describe genotypic and environmental differences in leaves orientation in a panel of 5 maize hybrids sowing at 2 densities (6 and 12 plants.m(−2)) and 2 row spacing (0.4 and 0.8 m) over 2 different sites in southern France. The ALAEM algorithm was validated against in situ annotations of leaves orientation, showing a satisfactory agreement (root mean square [RMSE] error = 0.1, R(2) = 0.35) in the proportion of leaves oriented perpendicular to rows direction across sowing patterns, genotypes, and sites. The results from ALAEM permitted to identify significant differences in leaves orientation associated to leaves intraspecific competition. In both experiments, a progressive increase in the proportion of leaves oriented perpendicular to the row is observed when the rectangularity of the sowing pattern increases from 1 (6 plants.m(−2), 0.4 m row spacing) towards 8 (12 plants.m(−2), 0.8 m row spacing). Significant differences among the 5 cultivars were found, with 2 hybrids exhibiting, systematically, a more plastic behavior with a significantly higher proportion of leaves oriented perpendicularly to avoid overlapping with neighbor plants at high rectangularity. Differences in leaves orientation were also found between experiments in a squared sowing pattern (6 plants.m(−2), 0.4 m row spacing), indicating a possible contribution of illumination conditions inducing a preferential orientation toward east-west direction when intraspecific competition is low.
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spelling pubmed-102047432023-05-24 Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images Serouart, Mario Lopez-Lozano, Raul Daubige, Gaëtan Baumont, Maëva Escale, Brigitte De Solan, Benoit Baret, Frédéric Plant Phenomics Research Article The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies light interception. Previous studies have indicated how maize genotypes may adapt leaves orientation to avoid mutual shading with neighboring plants as a plastic response to intraspecific competition. The goal of the present study is 2-fold: firstly, to propose and validate an automatic algorithm (Automatic Leaf Azimuth Estimation from Midrib detection [ALAEM]) based on leaves midrib detection in vertical red green blue (RGB) images to describe leaves orientation at the canopy level; and secondly, to describe genotypic and environmental differences in leaves orientation in a panel of 5 maize hybrids sowing at 2 densities (6 and 12 plants.m(−2)) and 2 row spacing (0.4 and 0.8 m) over 2 different sites in southern France. The ALAEM algorithm was validated against in situ annotations of leaves orientation, showing a satisfactory agreement (root mean square [RMSE] error = 0.1, R(2) = 0.35) in the proportion of leaves oriented perpendicular to rows direction across sowing patterns, genotypes, and sites. The results from ALAEM permitted to identify significant differences in leaves orientation associated to leaves intraspecific competition. In both experiments, a progressive increase in the proportion of leaves oriented perpendicular to the row is observed when the rectangularity of the sowing pattern increases from 1 (6 plants.m(−2), 0.4 m row spacing) towards 8 (12 plants.m(−2), 0.8 m row spacing). Significant differences among the 5 cultivars were found, with 2 hybrids exhibiting, systematically, a more plastic behavior with a significantly higher proportion of leaves oriented perpendicularly to avoid overlapping with neighbor plants at high rectangularity. Differences in leaves orientation were also found between experiments in a squared sowing pattern (6 plants.m(−2), 0.4 m row spacing), indicating a possible contribution of illumination conditions inducing a preferential orientation toward east-west direction when intraspecific competition is low. AAAS 2023-05-09 /pmc/articles/PMC10204743/ /pubmed/37228515 http://dx.doi.org/10.34133/plantphenomics.0046 Text en Copyright © 2023 Mario Serouart 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
Serouart, Mario
Lopez-Lozano, Raul
Daubige, Gaëtan
Baumont, Maëva
Escale, Brigitte
De Solan, Benoit
Baret, Frédéric
Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title_full Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title_fullStr Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title_full_unstemmed Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title_short Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
title_sort analyzing changes in maize leaves orientation due to gxexm using an automatic method from rgb images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204743/
https://www.ncbi.nlm.nih.gov/pubmed/37228515
http://dx.doi.org/10.34133/plantphenomics.0046
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