Observed and estimated leaf appearance of landrace and improved maize cultivars

Detalhes bibliográficos
Autor(a) principal: Langner,Josana Andreia
Data de Publicação: 2018
Outros Autores: Streck,Nereu Augusto, Durigon,Angelica, Silva,Stefanía Dalmolin da, Lago,Isabel, Dalmago,Genei Antonio, Reiniger,Lia Rejane Silveira, Scheffel,Lúcio Gabriel, Poersch,Anderson Haas
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100201
Resumo: ABSTRACT: The objective of this study was to compare the simulations of leaf appearance of landrace and improved maize cultivars using the CSM-CERES-Maize (linear) and the Wang and Engel models (nonlinear). The coefficients of the models were calibrated using a data set of total leaf number collected in the 11/04/2013 sowing date for the landrace varieties ‘Cinquentinha’ and ‘Bico de Ouro’ and the simple hybrid ‘AS 1573PRO’. For the ‘BRS Planalto’ variety, model coefficients were estimated with data from 12/13/2014 sowing date. Evaluation of the models was with independent data sets collected during the growing seasons of 2013/2014 (Experiment 1) and 2014/2015 (Experiment 2) in Santa Maria, RS, Brazil. Total number of leaves for both landrace and improved maize varieties was better estimated with the Wang and Engel model, with a root mean square error of 1.0 leaf, while estimations with the CSM-CERES-Maize model had a root mean square error of 1.5 leaf.
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spelling Observed and estimated leaf appearance of landrace and improved maize cultivarsZea mays L.vegetative developmentair temperaturesowing timemodelABSTRACT: The objective of this study was to compare the simulations of leaf appearance of landrace and improved maize cultivars using the CSM-CERES-Maize (linear) and the Wang and Engel models (nonlinear). The coefficients of the models were calibrated using a data set of total leaf number collected in the 11/04/2013 sowing date for the landrace varieties ‘Cinquentinha’ and ‘Bico de Ouro’ and the simple hybrid ‘AS 1573PRO’. For the ‘BRS Planalto’ variety, model coefficients were estimated with data from 12/13/2014 sowing date. Evaluation of the models was with independent data sets collected during the growing seasons of 2013/2014 (Experiment 1) and 2014/2015 (Experiment 2) in Santa Maria, RS, Brazil. Total number of leaves for both landrace and improved maize varieties was better estimated with the Wang and Engel model, with a root mean square error of 1.0 leaf, while estimations with the CSM-CERES-Maize model had a root mean square error of 1.5 leaf.Universidade Federal de Santa Maria2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100201Ciência Rural v.48 n.1 2018reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20160775info:eu-repo/semantics/openAccessLangner,Josana AndreiaStreck,Nereu AugustoDurigon,AngelicaSilva,Stefanía Dalmolin daLago,IsabelDalmago,Genei AntonioReiniger,Lia Rejane SilveiraScheffel,Lúcio GabrielPoersch,Anderson Haaseng2018-01-19T00:00:00ZRevista
dc.title.none.fl_str_mv Observed and estimated leaf appearance of landrace and improved maize cultivars
title Observed and estimated leaf appearance of landrace and improved maize cultivars
spellingShingle Observed and estimated leaf appearance of landrace and improved maize cultivars
Langner,Josana Andreia
Zea mays L.
vegetative development
air temperature
sowing time
model
title_short Observed and estimated leaf appearance of landrace and improved maize cultivars
title_full Observed and estimated leaf appearance of landrace and improved maize cultivars
title_fullStr Observed and estimated leaf appearance of landrace and improved maize cultivars
title_full_unstemmed Observed and estimated leaf appearance of landrace and improved maize cultivars
title_sort Observed and estimated leaf appearance of landrace and improved maize cultivars
author Langner,Josana Andreia
author_facet Langner,Josana Andreia
Streck,Nereu Augusto
Durigon,Angelica
Silva,Stefanía Dalmolin da
Lago,Isabel
Dalmago,Genei Antonio
Reiniger,Lia Rejane Silveira
Scheffel,Lúcio Gabriel
Poersch,Anderson Haas
author_role author
author2 Streck,Nereu Augusto
Durigon,Angelica
Silva,Stefanía Dalmolin da
Lago,Isabel
Dalmago,Genei Antonio
Reiniger,Lia Rejane Silveira
Scheffel,Lúcio Gabriel
Poersch,Anderson Haas
author2_role author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Langner,Josana Andreia
Streck,Nereu Augusto
Durigon,Angelica
Silva,Stefanía Dalmolin da
Lago,Isabel
Dalmago,Genei Antonio
Reiniger,Lia Rejane Silveira
Scheffel,Lúcio Gabriel
Poersch,Anderson Haas
dc.subject.por.fl_str_mv Zea mays L.
vegetative development
air temperature
sowing time
model
topic Zea mays L.
vegetative development
air temperature
sowing time
model
description ABSTRACT: The objective of this study was to compare the simulations of leaf appearance of landrace and improved maize cultivars using the CSM-CERES-Maize (linear) and the Wang and Engel models (nonlinear). The coefficients of the models were calibrated using a data set of total leaf number collected in the 11/04/2013 sowing date for the landrace varieties ‘Cinquentinha’ and ‘Bico de Ouro’ and the simple hybrid ‘AS 1573PRO’. For the ‘BRS Planalto’ variety, model coefficients were estimated with data from 12/13/2014 sowing date. Evaluation of the models was with independent data sets collected during the growing seasons of 2013/2014 (Experiment 1) and 2014/2015 (Experiment 2) in Santa Maria, RS, Brazil. Total number of leaves for both landrace and improved maize varieties was better estimated with the Wang and Engel model, with a root mean square error of 1.0 leaf, while estimations with the CSM-CERES-Maize model had a root mean square error of 1.5 leaf.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100201
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100201
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20160775
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.48 n.1 2018
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
repository.name.fl_str_mv
repository.mail.fl_str_mv
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