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Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling

Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole...

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Autores principales: Gosseau, Florie, Blanchet, Nicolas, Varès, Didier, Burger, Philippe, Campergue, Didier, Colombet, Céline, Gody, Louise, Liévin, Jean-François, Mangin, Brigitte, Tison, Gilles, Vincourt, Patrick, Casadebaig, Pierre, Langlade, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343525/
https://www.ncbi.nlm.nih.gov/pubmed/30700989
http://dx.doi.org/10.3389/fpls.2018.01908
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author Gosseau, Florie
Blanchet, Nicolas
Varès, Didier
Burger, Philippe
Campergue, Didier
Colombet, Céline
Gody, Louise
Liévin, Jean-François
Mangin, Brigitte
Tison, Gilles
Vincourt, Patrick
Casadebaig, Pierre
Langlade, Nicolas
author_facet Gosseau, Florie
Blanchet, Nicolas
Varès, Didier
Burger, Philippe
Campergue, Didier
Colombet, Céline
Gody, Louise
Liévin, Jean-François
Mangin, Brigitte
Tison, Gilles
Vincourt, Patrick
Casadebaig, Pierre
Langlade, Nicolas
author_sort Gosseau, Florie
collection PubMed
description Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a modeling study using measured parameters as inputs for a crop simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used a crop simulation model to predict the impact on crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological model parameters to define ideotypes adapted to different environmental conditions.
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spelling pubmed-63435252019-01-30 Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling Gosseau, Florie Blanchet, Nicolas Varès, Didier Burger, Philippe Campergue, Didier Colombet, Céline Gody, Louise Liévin, Jean-François Mangin, Brigitte Tison, Gilles Vincourt, Patrick Casadebaig, Pierre Langlade, Nicolas Front Plant Sci Plant Science Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a modeling study using measured parameters as inputs for a crop simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used a crop simulation model to predict the impact on crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological model parameters to define ideotypes adapted to different environmental conditions. Frontiers Media S.A. 2019-01-16 /pmc/articles/PMC6343525/ /pubmed/30700989 http://dx.doi.org/10.3389/fpls.2018.01908 Text en Copyright © 2019 Gosseau, Blanchet, Varès, Burger, Campergue, Colombet, Gody, Liévin, Mangin, Tison, Vincourt, Casadebaig and Langlade. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Gosseau, Florie
Blanchet, Nicolas
Varès, Didier
Burger, Philippe
Campergue, Didier
Colombet, Céline
Gody, Louise
Liévin, Jean-François
Mangin, Brigitte
Tison, Gilles
Vincourt, Patrick
Casadebaig, Pierre
Langlade, Nicolas
Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title_full Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title_fullStr Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title_full_unstemmed Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title_short Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling
title_sort heliaphen, an outdoor high-throughput phenotyping platform for genetic studies and crop modeling
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343525/
https://www.ncbi.nlm.nih.gov/pubmed/30700989
http://dx.doi.org/10.3389/fpls.2018.01908
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