Productive traits of rye cultivars grown under different sowing seasons
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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=S1415-43662019001200937 |
Resumo: | ABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar. |
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Productive traits of rye cultivars grown under different sowing seasonsSecale cerealegrowth modelsnonlinear modelssoil cover plantABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar.Departamento de Engenharia Agrícola - UFCG2019-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001200937Revista Brasileira de Engenharia Agrícola e Ambiental v.23 n.12 2019reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v23n12p937-944info:eu-repo/semantics/openAccessKleinpaul,Jéssica A.Cargnelutti Filho,AlbertoCarini,FernandaPezzini,Rafael V.Chaves,Gabriela G.Thomasi,Rosana M.eng2019-11-22T00:00:00Zoai:scielo:S1415-43662019001200937Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2019-11-22T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false |
dc.title.none.fl_str_mv |
Productive traits of rye cultivars grown under different sowing seasons |
title |
Productive traits of rye cultivars grown under different sowing seasons |
spellingShingle |
Productive traits of rye cultivars grown under different sowing seasons Kleinpaul,Jéssica A. Secale cereale growth models nonlinear models soil cover plant |
title_short |
Productive traits of rye cultivars grown under different sowing seasons |
title_full |
Productive traits of rye cultivars grown under different sowing seasons |
title_fullStr |
Productive traits of rye cultivars grown under different sowing seasons |
title_full_unstemmed |
Productive traits of rye cultivars grown under different sowing seasons |
title_sort |
Productive traits of rye cultivars grown under different sowing seasons |
author |
Kleinpaul,Jéssica A. |
author_facet |
Kleinpaul,Jéssica A. Cargnelutti Filho,Alberto Carini,Fernanda Pezzini,Rafael V. Chaves,Gabriela G. Thomasi,Rosana M. |
author_role |
author |
author2 |
Cargnelutti Filho,Alberto Carini,Fernanda Pezzini,Rafael V. Chaves,Gabriela G. Thomasi,Rosana M. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Kleinpaul,Jéssica A. Cargnelutti Filho,Alberto Carini,Fernanda Pezzini,Rafael V. Chaves,Gabriela G. Thomasi,Rosana M. |
dc.subject.por.fl_str_mv |
Secale cereale growth models nonlinear models soil cover plant |
topic |
Secale cereale growth models nonlinear models soil cover plant |
description |
ABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 |
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=S1415-43662019001200937 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001200937 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-1929/agriambi.v23n12p937-944 |
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.23 n.12 2019 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_ |
1750297686996680704 |