PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.

Detalhes bibliográficos
Autor(a) principal: MARTINS, S. M.
Data de Publicação: 2020
Outros Autores: BRITO, G. G. de, GONCALVES, W. da C., TRIPODE, B. M. D., LARTAUD, M., DUARTE, J. B., MORELLO, C. de L., GIBAND, M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1118821
Resumo: The root system architecture (RSA) of plants and its functioning play a fundamental role in a number of plant growth mechanisms including water and nutrient uptake. Optimization of the RSA is important for stable and increased plant productivity under adverse conditions. Despite its great importance, studying the RSA is notoriously laborious because of the difficulty of accessing the rooting system of plants. We developed a root phenotyping platform, PhenoRoots, which allows for the non-invasive study of plant RSA. The system was built using inexpensive material and was designed to provide medium throughput. Substrate-or soil-filled rhizotrons are used to grow plantlets, whose roots are directly visible through a glass plate. An experiment conducted on a panel of twenty Upland cotton (Gossypium hirsutum L.) varieties demonstrated the usefulness of the platform in assessing RSA traits. A number of traits, destructive and nondestructive, related to the RSA were measured and statistically analyzed. The non-destructive traits based on image analysis of roots were more accurate and showed high correlation with the time-consuming destructive measurements. The platform allowed for capturing the phenotypic and genetic variability found in the panel of cotton varieties, and to define three contrasting RSA patterns. PhenoRoots provides an inexpensive alternative to the medium throughput analysis of RSA traits in plants.
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spelling PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.RhizotronRoot traitsMedium-throughputImage analysisCottonThe root system architecture (RSA) of plants and its functioning play a fundamental role in a number of plant growth mechanisms including water and nutrient uptake. Optimization of the RSA is important for stable and increased plant productivity under adverse conditions. Despite its great importance, studying the RSA is notoriously laborious because of the difficulty of accessing the rooting system of plants. We developed a root phenotyping platform, PhenoRoots, which allows for the non-invasive study of plant RSA. The system was built using inexpensive material and was designed to provide medium throughput. Substrate-or soil-filled rhizotrons are used to grow plantlets, whose roots are directly visible through a glass plate. An experiment conducted on a panel of twenty Upland cotton (Gossypium hirsutum L.) varieties demonstrated the usefulness of the platform in assessing RSA traits. A number of traits, destructive and nondestructive, related to the RSA were measured and statistically analyzed. The non-destructive traits based on image analysis of roots were more accurate and showed high correlation with the time-consuming destructive measurements. The platform allowed for capturing the phenotypic and genetic variability found in the panel of cotton varieties, and to define three contrasting RSA patterns. PhenoRoots provides an inexpensive alternative to the medium throughput analysis of RSA traits in plants.Saulo Muniz Martins, Universidade Federal de Goiás - UFG/Setor de Genética e Melhoramento de Plantas; GIOVANI GREIGH DE BRITO, CNPA; WASHINGTON DA CONCEICAO GONCALVES, CNPA; BRUNA MENDES DINIZ TRIPODE, CNPA; Marc Lartaud, Cirad/UMR AGAP; João Batista Duarte, Universidade Federal de Goiás - UFG/Setor de Genética e Melhoramento de Plantas; CAMILO DE LELIS MORELLO, CNPA; Marc Giband, Cirad/UMR AGAP.MARTINS, S. M.BRITO, G. G. deGONCALVES, W. da C.TRIPODE, B. M. D.LARTAUD, M.DUARTE, J. B.MORELLO, C. de L.GIBAND, M.2020-01-16T00:35:54Z2020-01-16T00:35:54Z2020-01-1520202020-01-20T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleScientia Agricola, v. 77, n. 5, e20180420, 2020.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1118821enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2020-01-16T00:36:00Zoai:www.alice.cnptia.embrapa.br:doc/1118821Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542020-01-16T00:36falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542020-01-16T00:36Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
title PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
spellingShingle PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
MARTINS, S. M.
Rhizotron
Root traits
Medium-throughput
Image analysis
Cotton
title_short PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
title_full PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
title_fullStr PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
title_full_unstemmed PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
title_sort PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
author MARTINS, S. M.
author_facet MARTINS, S. M.
BRITO, G. G. de
GONCALVES, W. da C.
TRIPODE, B. M. D.
LARTAUD, M.
DUARTE, J. B.
MORELLO, C. de L.
GIBAND, M.
author_role author
author2 BRITO, G. G. de
GONCALVES, W. da C.
TRIPODE, B. M. D.
LARTAUD, M.
DUARTE, J. B.
MORELLO, C. de L.
GIBAND, M.
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Saulo Muniz Martins, Universidade Federal de Goiás - UFG/Setor de Genética e Melhoramento de Plantas; GIOVANI GREIGH DE BRITO, CNPA; WASHINGTON DA CONCEICAO GONCALVES, CNPA; BRUNA MENDES DINIZ TRIPODE, CNPA; Marc Lartaud, Cirad/UMR AGAP; João Batista Duarte, Universidade Federal de Goiás - UFG/Setor de Genética e Melhoramento de Plantas; CAMILO DE LELIS MORELLO, CNPA; Marc Giband, Cirad/UMR AGAP.
dc.contributor.author.fl_str_mv MARTINS, S. M.
BRITO, G. G. de
GONCALVES, W. da C.
TRIPODE, B. M. D.
LARTAUD, M.
DUARTE, J. B.
MORELLO, C. de L.
GIBAND, M.
dc.subject.por.fl_str_mv Rhizotron
Root traits
Medium-throughput
Image analysis
Cotton
topic Rhizotron
Root traits
Medium-throughput
Image analysis
Cotton
description The root system architecture (RSA) of plants and its functioning play a fundamental role in a number of plant growth mechanisms including water and nutrient uptake. Optimization of the RSA is important for stable and increased plant productivity under adverse conditions. Despite its great importance, studying the RSA is notoriously laborious because of the difficulty of accessing the rooting system of plants. We developed a root phenotyping platform, PhenoRoots, which allows for the non-invasive study of plant RSA. The system was built using inexpensive material and was designed to provide medium throughput. Substrate-or soil-filled rhizotrons are used to grow plantlets, whose roots are directly visible through a glass plate. An experiment conducted on a panel of twenty Upland cotton (Gossypium hirsutum L.) varieties demonstrated the usefulness of the platform in assessing RSA traits. A number of traits, destructive and nondestructive, related to the RSA were measured and statistically analyzed. The non-destructive traits based on image analysis of roots were more accurate and showed high correlation with the time-consuming destructive measurements. The platform allowed for capturing the phenotypic and genetic variability found in the panel of cotton varieties, and to define three contrasting RSA patterns. PhenoRoots provides an inexpensive alternative to the medium throughput analysis of RSA traits in plants.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-16T00:35:54Z
2020-01-16T00:35:54Z
2020-01-15
2020
2020-01-20T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Scientia Agricola, v. 77, n. 5, e20180420, 2020.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1118821
identifier_str_mv Scientia Agricola, v. 77, n. 5, e20180420, 2020.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1118821
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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