Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/25387 |
Resumo: | The objective of this work was to compare distributions for the modeling of the number and dry matter weight of nodules (DWN) of Rhizobium from different inoculants in common bean (Phaseolus vulgaris) inbred lines subjected to nitrogen doses, as well as to identify the best inoculant for those lines. The experiment was carried out in a randomized complete block design, arranged in split-split plots, with three factors – four inbred lines, five nitrogen doses (0, 20, 40, 60, and 80 kg ha-1), and three inoculants (CIAT 899, UFLA 02-100, and peat) – and four replicates. The number of nodules and their dry matter weight were analyzed with the generalized linear mixed modeling approach. The highest number of nodules was obtained with the CIAT 899 inoculant, at the dose of 20 kg ha-1 N (260 nodules), followed by UFLA 02-100, at 80 kg ha-1 (109 nodules), and peat alone at 20 kg ha-1 (98 nodules). The DWN with CIAT 899 exceeded in 0.66 g the DWN with UFLA 02-100, and in 0.95 g the DWN obtained without inoculation (inoculated with peat alone). The use of the negative binomial distribution and of the gamma distribution is a simple way to control data overdispersion of the nodule number and data underdispersion of DWN, respectively. |
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Generalized mixed linear modeling approach to analyze nodulation in common bean inbred linesAbordagem de modelos lineares generalizados mistos para analisar nodulação em linhagens de feijoeiro-comumPhaseolus vulgaris; Rhizobium; symbiotic nitrogen fixation; inoculant; overdispersion; underdispersionPhaseolus vulgaris; Rhizobium; fixação simbiótica de nitrogênio; inoculantes; superdispersão; subdispersãoThe objective of this work was to compare distributions for the modeling of the number and dry matter weight of nodules (DWN) of Rhizobium from different inoculants in common bean (Phaseolus vulgaris) inbred lines subjected to nitrogen doses, as well as to identify the best inoculant for those lines. The experiment was carried out in a randomized complete block design, arranged in split-split plots, with three factors – four inbred lines, five nitrogen doses (0, 20, 40, 60, and 80 kg ha-1), and three inoculants (CIAT 899, UFLA 02-100, and peat) – and four replicates. The number of nodules and their dry matter weight were analyzed with the generalized linear mixed modeling approach. The highest number of nodules was obtained with the CIAT 899 inoculant, at the dose of 20 kg ha-1 N (260 nodules), followed by UFLA 02-100, at 80 kg ha-1 (109 nodules), and peat alone at 20 kg ha-1 (98 nodules). The DWN with CIAT 899 exceeded in 0.66 g the DWN with UFLA 02-100, and in 0.95 g the DWN obtained without inoculation (inoculated with peat alone). The use of the negative binomial distribution and of the gamma distribution is a simple way to control data overdispersion of the nodule number and data underdispersion of DWN, respectively.O objetivo deste trabalho foi comparar distribuições para a modelagem do número e da massa de matéria seca de nódulos (MSN) de Rhizobium de diferentes inoculantes em linhagens de feijoeiro-comum (Phaseolus vulgaris) submetidas a diferentes doses de nitrogênio, bem como identificar o melhor inoculante para essas linhagens. O experimento foi instalado em blocos completos ao acaso, arranjados em parcelas subsubdivididas, com três fatores – quatro linhagens, cinco doses de nitrogênio (0, 20, 40, 60 e 80 kg ha-1) e três inoculantes (CIAT 899, UFLA 02-100 e turfa) – e quatro repetições. O número de nódulos e sua massa de matéria seca foram avaliados com a abordagem de modelos lineares generalizados mistos. O maior número de nódulos foi obtido com o inoculante CIAT 899 à dose de 20 kg ha-1 de N (260 nódulos), seguido do UFLA 02-100 a 80 kg ha-1 (109 nódulos) e de turfa sozinha (98 nódulos) a 20 kg ha-1. A MSN com o inoculante CIAT 899 excedeu em 0,66 g a MSN com o UFLA 02-100, e em 0,95 g a MSN obtida sem inoculação (inoculação com turfa apenas). O uso das distribuições bionomial negativa e gama é uma maneira simples de controlar a superdispersão dos dados do número de nódulos e a subdispersão dos dados de MSN, respectivamente.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Rizzardi, Diego AryContreras-Soto, Rodrigo IvanFigueiredo, Alex Sandro TorreAndrade, Carlos Alberto de BastosSantana, Rosangela GeritanaScapim, Carlos Alberto2017-12-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/25387Pesquisa Agropecuaria Brasileira; v.52, n.12, dez. 2017; 1178-1184Pesquisa Agropecuária Brasileira; v.52, n.12, dez. 2017; 1178-11841678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://seer.sct.embrapa.br/index.php/pab/article/view/25387/14040https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/25387/17162https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/25387/17165Direitos autorais 2017 Pesquisa Agropecuária Brasileirainfo:eu-repo/semantics/openAccess2017-12-21T10:21:52Zoai:ojs.seer.sct.embrapa.br:article/25387Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2017-12-21T10:21:52Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines Abordagem de modelos lineares generalizados mistos para analisar nodulação em linhagens de feijoeiro-comum |
title |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
spellingShingle |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines Rizzardi, Diego Ary Phaseolus vulgaris; Rhizobium; symbiotic nitrogen fixation; inoculant; overdispersion; underdispersion Phaseolus vulgaris; Rhizobium; fixação simbiótica de nitrogênio; inoculantes; superdispersão; subdispersão |
title_short |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
title_full |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
title_fullStr |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
title_full_unstemmed |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
title_sort |
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines |
author |
Rizzardi, Diego Ary |
author_facet |
Rizzardi, Diego Ary Contreras-Soto, Rodrigo Ivan Figueiredo, Alex Sandro Torre Andrade, Carlos Alberto de Bastos Santana, Rosangela Geritana Scapim, Carlos Alberto |
author_role |
author |
author2 |
Contreras-Soto, Rodrigo Ivan Figueiredo, Alex Sandro Torre Andrade, Carlos Alberto de Bastos Santana, Rosangela Geritana Scapim, Carlos Alberto |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) |
dc.contributor.author.fl_str_mv |
Rizzardi, Diego Ary Contreras-Soto, Rodrigo Ivan Figueiredo, Alex Sandro Torre Andrade, Carlos Alberto de Bastos Santana, Rosangela Geritana Scapim, Carlos Alberto |
dc.subject.por.fl_str_mv |
Phaseolus vulgaris; Rhizobium; symbiotic nitrogen fixation; inoculant; overdispersion; underdispersion Phaseolus vulgaris; Rhizobium; fixação simbiótica de nitrogênio; inoculantes; superdispersão; subdispersão |
topic |
Phaseolus vulgaris; Rhizobium; symbiotic nitrogen fixation; inoculant; overdispersion; underdispersion Phaseolus vulgaris; Rhizobium; fixação simbiótica de nitrogênio; inoculantes; superdispersão; subdispersão |
description |
The objective of this work was to compare distributions for the modeling of the number and dry matter weight of nodules (DWN) of Rhizobium from different inoculants in common bean (Phaseolus vulgaris) inbred lines subjected to nitrogen doses, as well as to identify the best inoculant for those lines. The experiment was carried out in a randomized complete block design, arranged in split-split plots, with three factors – four inbred lines, five nitrogen doses (0, 20, 40, 60, and 80 kg ha-1), and three inoculants (CIAT 899, UFLA 02-100, and peat) – and four replicates. The number of nodules and their dry matter weight were analyzed with the generalized linear mixed modeling approach. The highest number of nodules was obtained with the CIAT 899 inoculant, at the dose of 20 kg ha-1 N (260 nodules), followed by UFLA 02-100, at 80 kg ha-1 (109 nodules), and peat alone at 20 kg ha-1 (98 nodules). The DWN with CIAT 899 exceeded in 0.66 g the DWN with UFLA 02-100, and in 0.95 g the DWN obtained without inoculation (inoculated with peat alone). The use of the negative binomial distribution and of the gamma distribution is a simple way to control data overdispersion of the nodule number and data underdispersion of DWN, respectively. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-21 |
dc.type.none.fl_str_mv |
|
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://seer.sct.embrapa.br/index.php/pab/article/view/25387 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/25387 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/25387/14040 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/25387/17162 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/25387/17165 |
dc.rights.driver.fl_str_mv |
Direitos autorais 2017 Pesquisa Agropecuária Brasileira info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Direitos autorais 2017 Pesquisa Agropecuária Brasileira |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; v.52, n.12, dez. 2017; 1178-1184 Pesquisa Agropecuária Brasileira; v.52, n.12, dez. 2017; 1178-1184 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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1793416680999747584 |