Simulation of wheat biomass yield by thermal time, rainfall and nitrogen
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
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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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 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017001100763 |
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 |
institution |
UFCG |
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) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
_version_ |
1750297685631434752 |