Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | https://www.revistas.usp.br/sa/article/view/135407 |
Resumo: | Maize plants can be N-use efficient or N-stress tolerant. The first have high yields in favorable environments but is drastically affected under stress conditions; whereas the second show satisfactory yields in stressful environments but only moderate ones under optimal conditions. In this context, our aim was to assess the possibility of selecting tropical maize lines that are simultaneously N-stress tolerant and N-use efficient and check for differences between simultaneous selection statistical methods. Sixty-four tropical maize lines were evaluated for Nitrogen Agronomic Efficiency (NAE) and Low Nitrogen Tolerance (LNTI) response indices and two per se selection indices, Low Nitrogen Agronomic Efficiency (LNAE) and Harmonic Mean of Relative Performance (HMRP). We performed eight selection scenarios: LNAE; HMRP; Additive index; Mulamba-Mock index; and Independent culling levels. The last three was predicted by REML/BLUP single-trait and multi-trait using genotypic values of NAE and LNTI. The REML/BLUP multi-trait analysis was superior to the single-trait analysis due to high unfavorable correlation between NAE and LNTI. However, the accuracy and genotypic determination coefficient of NAE and LNTI were too low. Thus, neither single- nor multi-trait analysis achieved a good result for simultaneous selection nor N-use efficiency nor N-stress tolerance. LNAE obtained satisfactorily accurate values and genotypic determination coefficient, but its performance in selection gain was worse than HMRP, particularly in terms of N-use efficiency. Therefore, because of the superior performance in accuracy, genotypic determination coefficient and selection, HMRP was considered the best simultaneous selection methodology of the scenarios tested for N-use efficiency and N-stress tolerance. |
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Scientia Agrícola (Online) |
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Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical linesabiotic stresscorrelation between traitswinter maizemixed models Maize plants can be N-use efficient or N-stress tolerant. The first have high yields in favorable environments but is drastically affected under stress conditions; whereas the second show satisfactory yields in stressful environments but only moderate ones under optimal conditions. In this context, our aim was to assess the possibility of selecting tropical maize lines that are simultaneously N-stress tolerant and N-use efficient and check for differences between simultaneous selection statistical methods. Sixty-four tropical maize lines were evaluated for Nitrogen Agronomic Efficiency (NAE) and Low Nitrogen Tolerance (LNTI) response indices and two per se selection indices, Low Nitrogen Agronomic Efficiency (LNAE) and Harmonic Mean of Relative Performance (HMRP). We performed eight selection scenarios: LNAE; HMRP; Additive index; Mulamba-Mock index; and Independent culling levels. The last three was predicted by REML/BLUP single-trait and multi-trait using genotypic values of NAE and LNTI. The REML/BLUP multi-trait analysis was superior to the single-trait analysis due to high unfavorable correlation between NAE and LNTI. However, the accuracy and genotypic determination coefficient of NAE and LNTI were too low. Thus, neither single- nor multi-trait analysis achieved a good result for simultaneous selection nor N-use efficiency nor N-stress tolerance. LNAE obtained satisfactorily accurate values and genotypic determination coefficient, but its performance in selection gain was worse than HMRP, particularly in terms of N-use efficiency. Therefore, because of the superior performance in accuracy, genotypic determination coefficient and selection, HMRP was considered the best simultaneous selection methodology of the scenarios tested for N-use efficiency and N-stress tolerance.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2017-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/13540710.1590/1678-992x-2016-0313Scientia Agricola; v. 74 n. 6 (2017); 481-488Scientia Agricola; Vol. 74 Núm. 6 (2017); 481-488Scientia Agricola; Vol. 74 No. 6 (2017); 481-4881678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/135407/131262Copyright (c) 2017 Scientia Agricolainfo:eu-repo/semantics/openAccessMendonça, Leandro de FreitasGranato, Ítalo Stefanine CorreiaAlves, Filipe CoutoMorais, Pedro Patric PinhoVidotti, Miriam SuzaneFritsche-Neto, Roberto2017-08-10T18:04:42Zoai:revistas.usp.br:article/135407Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2017-08-10T18:04:42Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
title |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
spellingShingle |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines Mendonça, Leandro de Freitas abiotic stress correlation between traits winter maize mixed models |
title_short |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
title_full |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
title_fullStr |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
title_full_unstemmed |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
title_sort |
Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines |
author |
Mendonça, Leandro de Freitas |
author_facet |
Mendonça, Leandro de Freitas Granato, Ítalo Stefanine Correia Alves, Filipe Couto Morais, Pedro Patric Pinho Vidotti, Miriam Suzane Fritsche-Neto, Roberto |
author_role |
author |
author2 |
Granato, Ítalo Stefanine Correia Alves, Filipe Couto Morais, Pedro Patric Pinho Vidotti, Miriam Suzane Fritsche-Neto, Roberto |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Mendonça, Leandro de Freitas Granato, Ítalo Stefanine Correia Alves, Filipe Couto Morais, Pedro Patric Pinho Vidotti, Miriam Suzane Fritsche-Neto, Roberto |
dc.subject.por.fl_str_mv |
abiotic stress correlation between traits winter maize mixed models |
topic |
abiotic stress correlation between traits winter maize mixed models |
description |
Maize plants can be N-use efficient or N-stress tolerant. The first have high yields in favorable environments but is drastically affected under stress conditions; whereas the second show satisfactory yields in stressful environments but only moderate ones under optimal conditions. In this context, our aim was to assess the possibility of selecting tropical maize lines that are simultaneously N-stress tolerant and N-use efficient and check for differences between simultaneous selection statistical methods. Sixty-four tropical maize lines were evaluated for Nitrogen Agronomic Efficiency (NAE) and Low Nitrogen Tolerance (LNTI) response indices and two per se selection indices, Low Nitrogen Agronomic Efficiency (LNAE) and Harmonic Mean of Relative Performance (HMRP). We performed eight selection scenarios: LNAE; HMRP; Additive index; Mulamba-Mock index; and Independent culling levels. The last three was predicted by REML/BLUP single-trait and multi-trait using genotypic values of NAE and LNTI. The REML/BLUP multi-trait analysis was superior to the single-trait analysis due to high unfavorable correlation between NAE and LNTI. However, the accuracy and genotypic determination coefficient of NAE and LNTI were too low. Thus, neither single- nor multi-trait analysis achieved a good result for simultaneous selection nor N-use efficiency nor N-stress tolerance. LNAE obtained satisfactorily accurate values and genotypic determination coefficient, but its performance in selection gain was worse than HMRP, particularly in terms of N-use efficiency. Therefore, because of the superior performance in accuracy, genotypic determination coefficient and selection, HMRP was considered the best simultaneous selection methodology of the scenarios tested for N-use efficiency and N-stress tolerance. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/135407 10.1590/1678-992x-2016-0313 |
url |
https://www.revistas.usp.br/sa/article/view/135407 |
identifier_str_mv |
10.1590/1678-992x-2016-0313 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/135407/131262 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Scientia Agricola info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Scientia Agricola |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
dc.source.none.fl_str_mv |
Scientia Agricola; v. 74 n. 6 (2017); 481-488 Scientia Agricola; Vol. 74 Núm. 6 (2017); 481-488 Scientia Agricola; Vol. 74 No. 6 (2017); 481-488 1678-992X 0103-9016 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1800222793299656704 |