Modelos de crescimento de cultivares de centeio
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
dARK ID: | ark:/26339/001300000qsc0 |
Texto Completo: | http://repositorio.ufsm.br/handle/1/15938 |
Resumo: | The objectives of this study were to adjust the nonlinear models, Gompertz and Logistic, to describe the plant height, fresh matter of aerial and dry matter of aerial and indicate the model that best describes the growth of two rye cultivars, BRS Progresso and Temprano, in five sowing seasons. Ten uniformity trials were conducted with the rye crop in the 2016 harvest. Ten plants weekly were evaluated from the first leaf to be fully expanded, randomly chosen within each assay. In each plant were evaluated the characters of plant height, fresh matter of aerial and dry matter of aerial. For the adjustment of the Gompertz and Logistic models as a function of the accumulated thermal sum, the mean value of each character in each evaluation was considered. Were estimated parameters a, b and c for each model. The confidence interval for each parameter, inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration was calculated. The quality of fit of the models was verified by the coefficient of determination, Akaike's information criterion and residual standard deviation. For analysis of the behavior of the models, the nonlinearity present in the models was quantified through the intrinsic nonlinearity and the nonlinearity of the parameter effect. Both models satisfactorily describe the behavior of the characters in rye cultivars at sowing times. The model that best describes the growth behavior of rye cultivars is the Logistic model. |
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Modelos de crescimento de cultivares de centeioGrowth models of rye cultivarsSecale cereale L.Modelos não linearesPlanta de cobertura de soloCereais de invernoNon-linear modelsGround cover plantWinter cerealsCNPQ::CIENCIAS AGRARIAS::AGRONOMIAThe objectives of this study were to adjust the nonlinear models, Gompertz and Logistic, to describe the plant height, fresh matter of aerial and dry matter of aerial and indicate the model that best describes the growth of two rye cultivars, BRS Progresso and Temprano, in five sowing seasons. Ten uniformity trials were conducted with the rye crop in the 2016 harvest. Ten plants weekly were evaluated from the first leaf to be fully expanded, randomly chosen within each assay. In each plant were evaluated the characters of plant height, fresh matter of aerial and dry matter of aerial. For the adjustment of the Gompertz and Logistic models as a function of the accumulated thermal sum, the mean value of each character in each evaluation was considered. Were estimated parameters a, b and c for each model. The confidence interval for each parameter, inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration was calculated. The quality of fit of the models was verified by the coefficient of determination, Akaike's information criterion and residual standard deviation. For analysis of the behavior of the models, the nonlinearity present in the models was quantified through the intrinsic nonlinearity and the nonlinearity of the parameter effect. Both models satisfactorily describe the behavior of the characters in rye cultivars at sowing times. The model that best describes the growth behavior of rye cultivars is the Logistic model.Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqOs objetivos deste estudo foram ajustar os modelos não lineares, Gompertz e Logístico, para altura de planta, massa de matéria fresca de parte aérea e massa de matéria seca de parte aérea e indicar o modelo que melhor descreve o crescimento de duas cultivares de centeio, BRS Progresso e Temprano, em cinco épocas de semeadura. Foram conduzidos dez ensaios de uniformidade com a cultura de centeio na safra 2016. Avaliaram-se dez plantas semanalmente a partir da primeira folha estar completamente expandida, escolhidas de forma aleatória dentro de cada ensaio. Em cada planta foram avaliados os caracteres altura de planta, massa de matéria fresca de parte aérea e massa de matéria seca de parte aérea. Para o ajuste dos modelos Gompertz e Logístico em função da soma térmica acumulada, foi considerado o valor médio de cada caractere em cada avaliação. Foram estimados os parâmetros a, b e c para cada modelo. Calculou-se o intervalo de confiança para cada parâmetro, os pontos de inflexão, aceleração máxima, desaceleração máxima e desaceleração assintótica. A qualidade do ajuste dos modelos foi verificada pelo coeficiente de determinação, critério de informação de Akaike e desvio padrão residual. Para análise do comportamento dos modelos foi quantificada a não linearidade presente nos modelos, através da não linearidade intrínseca e da não linearidade do efeito do parâmetro. Ambos os modelos, descrevem satisfatoriamente o comportamento dos caracteres, nas cultivares de centeio, em épocas de semeadura. O modelo que melhor descreve o comportamento de crescimento das cultivares de centeio é o modelo Logístico.Universidade Federal de Santa MariaBrasilAgronomiaUFSMPrograma de Pós-Graduação em AgronomiaCentro de Ciências RuraisCargnelutti Filho, Albertohttp://lattes.cnpq.br/0233728865094243Lorentz, Leandro Homrichhttp://lattes.cnpq.br/3133075693356442Storck, Lindolfohttp://lattes.cnpq.br/7538496041313334Kleinpaul, Jéssica Andiara2019-03-20T14:42:51Z2019-03-20T14:42:51Z2018-07-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/15938ark:/26339/001300000qsc0porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2019-03-21T06:00:25Zoai:repositorio.ufsm.br:1/15938Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2024-07-29T10:50:50.789061Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Modelos de crescimento de cultivares de centeio Growth models of rye cultivars |
title |
Modelos de crescimento de cultivares de centeio |
spellingShingle |
Modelos de crescimento de cultivares de centeio Kleinpaul, Jéssica Andiara Secale cereale L. Modelos não lineares Planta de cobertura de solo Cereais de inverno Non-linear models Ground cover plant Winter cereals CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Modelos de crescimento de cultivares de centeio |
title_full |
Modelos de crescimento de cultivares de centeio |
title_fullStr |
Modelos de crescimento de cultivares de centeio |
title_full_unstemmed |
Modelos de crescimento de cultivares de centeio |
title_sort |
Modelos de crescimento de cultivares de centeio |
author |
Kleinpaul, Jéssica Andiara |
author_facet |
Kleinpaul, Jéssica Andiara |
author_role |
author |
dc.contributor.none.fl_str_mv |
Cargnelutti Filho, Alberto http://lattes.cnpq.br/0233728865094243 Lorentz, Leandro Homrich http://lattes.cnpq.br/3133075693356442 Storck, Lindolfo http://lattes.cnpq.br/7538496041313334 |
dc.contributor.author.fl_str_mv |
Kleinpaul, Jéssica Andiara |
dc.subject.por.fl_str_mv |
Secale cereale L. Modelos não lineares Planta de cobertura de solo Cereais de inverno Non-linear models Ground cover plant Winter cereals CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
topic |
Secale cereale L. Modelos não lineares Planta de cobertura de solo Cereais de inverno Non-linear models Ground cover plant Winter cereals CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
The objectives of this study were to adjust the nonlinear models, Gompertz and Logistic, to describe the plant height, fresh matter of aerial and dry matter of aerial and indicate the model that best describes the growth of two rye cultivars, BRS Progresso and Temprano, in five sowing seasons. Ten uniformity trials were conducted with the rye crop in the 2016 harvest. Ten plants weekly were evaluated from the first leaf to be fully expanded, randomly chosen within each assay. In each plant were evaluated the characters of plant height, fresh matter of aerial and dry matter of aerial. For the adjustment of the Gompertz and Logistic models as a function of the accumulated thermal sum, the mean value of each character in each evaluation was considered. Were estimated parameters a, b and c for each model. The confidence interval for each parameter, inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration was calculated. The quality of fit of the models was verified by the coefficient of determination, Akaike's information criterion and residual standard deviation. For analysis of the behavior of the models, the nonlinearity present in the models was quantified through the intrinsic nonlinearity and the nonlinearity of the parameter effect. Both models satisfactorily describe the behavior of the characters in rye cultivars at sowing times. The model that best describes the growth behavior of rye cultivars is the Logistic model. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-19 2019-03-20T14:42:51Z 2019-03-20T14:42:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/15938 |
dc.identifier.dark.fl_str_mv |
ark:/26339/001300000qsc0 |
url |
http://repositorio.ufsm.br/handle/1/15938 |
identifier_str_mv |
ark:/26339/001300000qsc0 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Agronomia UFSM Programa de Pós-Graduação em Agronomia Centro de Ciências Rurais |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Agronomia UFSM Programa de Pós-Graduação em Agronomia Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
_version_ |
1814439830286761984 |