Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines

Detalhes bibliográficos
Autor(a) principal: Rizzardi, Diego Ary
Data de Publicação: 2017
Outros Autores: Contreras-Soto, Rodrigo Ivan, Figueiredo, Alex Sandro Torre, Andrade, Carlos Alberto de Bastos, Santana, Rosangela Geritana, Scapim, Carlos Alberto
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.
id EMBRAPA-4_0c360911e5cb4bbb4c580bc07dea9831
oai_identifier_str oai:ojs.seer.sct.embrapa.br:article/25387
network_acronym_str EMBRAPA-4
network_name_str Pesquisa Agropecuária Brasileira (Online)
repository_id_str
spelling 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
_version_ 1793416680999747584