PhenoRoots: an inexpensive non-invasive phenotyping system to assess the variability of the root system architecture.
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
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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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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1794503488278888448 |