Simulation of wheat biomass yield by thermal time, rainfall and nitrogen

Detalhes bibliográficos
Autor(a) principal: Trautmann,Ana P. B.
Data de Publicação: 2017
Outros Autores: Silva,José A. G. da, Binelo,Manuel O., Scremin,Osmar B., Mamann,Ângela T. W De, Bandeira,Luiz M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017001100763
Resumo: ABSTRACT Wheat biomass yield focused on the production of quality silage is dependent on rainfall, temperature and nitrogen (N). The objective of the study was to validate the use of rainfall, thermal time and N as potential variables for the composition of the multiple linear regression model and simulation of wheat biomass yield for silage production under N supply conditions during the cycle, in the systems of succession. The study was conducted in 2012, 2013 and 2014, in randomized blocks with four replicates in 4 x 3 factorial, for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and forms of N supply [single application (100%) in the stage V3 (third expanded leaf); split application (70%/30%) in the stages V3/V6 (third and sixth expanded leaves); split application (70%/30%) in the stages V3/E (third expanded leaf and beginning of grain filling)], respectively, in the systems soybean/wheat and maize/wheat. Rainfall and N are potential variables in the composition of the multiple linear regression model. Multiple linear regression models are efficient in the simulation of wheat biomass yield for silage under the N supply conditions during the cycle in the succession systems.
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spelling Simulation of wheat biomass yield by thermal time, rainfall and nitrogenTriticum aestivumN dosesplit N applicationresidual NsilageABSTRACT Wheat biomass yield focused on the production of quality silage is dependent on rainfall, temperature and nitrogen (N). The objective of the study was to validate the use of rainfall, thermal time and N as potential variables for the composition of the multiple linear regression model and simulation of wheat biomass yield for silage production under N supply conditions during the cycle, in the systems of succession. The study was conducted in 2012, 2013 and 2014, in randomized blocks with four replicates in 4 x 3 factorial, for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and forms of N supply [single application (100%) in the stage V3 (third expanded leaf); split application (70%/30%) in the stages V3/V6 (third and sixth expanded leaves); split application (70%/30%) in the stages V3/E (third expanded leaf and beginning of grain filling)], respectively, in the systems soybean/wheat and maize/wheat. Rainfall and N are potential variables in the composition of the multiple linear regression model. Multiple linear regression models are efficient in the simulation of wheat biomass yield for silage under the N supply conditions during the cycle in the succession systems.Departamento de Engenharia Agrícola - UFCG2017-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017001100763Revista Brasileira de Engenharia Agrícola e Ambiental v.21 n.11 2017reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v21n11p763-768info:eu-repo/semantics/openAccessTrautmann,Ana P. B.Silva,José A. G. daBinelo,Manuel O.Scremin,Osmar B.Mamann,Ângela T. W DeBandeira,Luiz M.eng2017-11-09T00:00:00Zoai:scielo:S1415-43662017001100763Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2017-11-09T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false
dc.title.none.fl_str_mv Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
title Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
spellingShingle Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
Trautmann,Ana P. B.
Triticum aestivum
N dose
split N application
residual N
silage
title_short Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
title_full Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
title_fullStr Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
title_full_unstemmed Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
title_sort Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
author Trautmann,Ana P. B.
author_facet Trautmann,Ana P. B.
Silva,José A. G. da
Binelo,Manuel O.
Scremin,Osmar B.
Mamann,Ângela T. W De
Bandeira,Luiz M.
author_role author
author2 Silva,José A. G. da
Binelo,Manuel O.
Scremin,Osmar B.
Mamann,Ângela T. W De
Bandeira,Luiz M.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Trautmann,Ana P. B.
Silva,José A. G. da
Binelo,Manuel O.
Scremin,Osmar B.
Mamann,Ângela T. W De
Bandeira,Luiz M.
dc.subject.por.fl_str_mv Triticum aestivum
N dose
split N application
residual N
silage
topic Triticum aestivum
N dose
split N application
residual N
silage
description ABSTRACT Wheat biomass yield focused on the production of quality silage is dependent on rainfall, temperature and nitrogen (N). The objective of the study was to validate the use of rainfall, thermal time and N as potential variables for the composition of the multiple linear regression model and simulation of wheat biomass yield for silage production under N supply conditions during the cycle, in the systems of succession. The study was conducted in 2012, 2013 and 2014, in randomized blocks with four replicates in 4 x 3 factorial, for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and forms of N supply [single application (100%) in the stage V3 (third expanded leaf); split application (70%/30%) in the stages V3/V6 (third and sixth expanded leaves); split application (70%/30%) in the stages V3/E (third expanded leaf and beginning of grain filling)], respectively, in the systems soybean/wheat and maize/wheat. Rainfall and N are potential variables in the composition of the multiple linear regression model. Multiple linear regression models are efficient in the simulation of wheat biomass yield for silage under the N supply conditions during the cycle in the succession systems.
publishDate 2017
dc.date.none.fl_str_mv 2017-11-01
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=S1415-43662017001100763
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1807-1929/agriambi.v21n11p763-768
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 Departamento de Engenharia Agrícola - UFCG
publisher.none.fl_str_mv Departamento de Engenharia Agrícola - UFCG
dc.source.none.fl_str_mv Revista Brasileira de Engenharia Agrícola e Ambiental v.21 n.11 2017
reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
instname:Universidade Federal de Campina Grande (UFCG)
instacron:UFCG
instname_str Universidade Federal de Campina Grande (UFCG)
instacron_str UFCG
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reponame_str Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
collection Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
repository.name.fl_str_mv Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)
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