Modelagem de percentuais de germinação de sementes de milho em função do tempo
Autor(a) principal: | |
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Data de Publicação: | 2009 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
Texto Completo: | http://repositorio.uem.br:8080/jspui/handle/1/1155 |
Resumo: | In 2008, the national production of grains was about 58.7 million of tonnes for which the seed quality had the most effective contribution. However, the seed quality is reduced during warehouse storage and the prediction of seed lot performance under such conditions has been a challenge for seed technologist. Therefore, research programs must always investigate the seed lots performance in which the percentage of germination during the storage could properly be described by regression models. In this context, the germination performance of aged seeds of maize was estimated by the probit P(Y=y)=C+ (1-C).F(β0+β1.log(x)) as an alternative to the simplified equation in which Vp=Vі‾p.tg(β). Seeds from three seed lots of the hybrid maize OC 705 were aged at 43 °C for 24, 48, 72, 96, 120, 144, 168 and 192 h. The seeds were stored under warehouse conditions and the experiment was replicated three times. Coefficients of determination at most of 0.92 had no goodness of fit to describe the data by the simplified equation. On the other hand, the x² of the Pearson and log-likelihood tests indicated significant goodness of fit for the same data described by the probit model. Next, another analysis was carried out to fit the logistic model y(t)=C/(1+exp(B(t-M))) to the same data. The goodness of fit was evaluated by the parameter and intrinsic curvatures and bias of Box which were important in identifying the seed lot with the best fit. Finally, data from another experiment was analyzed to describe the germination performance of hybrid seeds of maize °C 705 and CD 5501 along sampling days and during two planting times by using the nonlinear model y(t)=A-B.exp(-Ct). First, the identity of the models indicated that in the seeding time 28 Oct. 1996 the performance from both hybrid seeds were described by the same equation. The date 28 Oct. 1996 was the best planting time and 57 d after anthesis was the best harvesting time when the percentage of seed germination was 96.1%. The methodology Bayesiana made possible the study of the germination curves and it allowed to recommend, for the two hybrid, the first harvesting time, as the viable for the sown. Still, for means of credibility intervals, it was possible the comparison of the adjusted equations for the combination of hybrid and harvesting times. |
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Modelagem de percentuais de germinação de sementes de milho em função do tempoMilhoGerminação de sementesModelagemRegressão não linearRegressão probitoInferência bayesiana.Nonlinear regressionSeed germinationProbit analysesBayesian inference.Ciências AgráriasAgronomiaIn 2008, the national production of grains was about 58.7 million of tonnes for which the seed quality had the most effective contribution. However, the seed quality is reduced during warehouse storage and the prediction of seed lot performance under such conditions has been a challenge for seed technologist. Therefore, research programs must always investigate the seed lots performance in which the percentage of germination during the storage could properly be described by regression models. In this context, the germination performance of aged seeds of maize was estimated by the probit P(Y=y)=C+ (1-C).F(β0+β1.log(x)) as an alternative to the simplified equation in which Vp=Vі‾p.tg(β). Seeds from three seed lots of the hybrid maize OC 705 were aged at 43 °C for 24, 48, 72, 96, 120, 144, 168 and 192 h. The seeds were stored under warehouse conditions and the experiment was replicated three times. Coefficients of determination at most of 0.92 had no goodness of fit to describe the data by the simplified equation. On the other hand, the x² of the Pearson and log-likelihood tests indicated significant goodness of fit for the same data described by the probit model. Next, another analysis was carried out to fit the logistic model y(t)=C/(1+exp(B(t-M))) to the same data. The goodness of fit was evaluated by the parameter and intrinsic curvatures and bias of Box which were important in identifying the seed lot with the best fit. Finally, data from another experiment was analyzed to describe the germination performance of hybrid seeds of maize °C 705 and CD 5501 along sampling days and during two planting times by using the nonlinear model y(t)=A-B.exp(-Ct). First, the identity of the models indicated that in the seeding time 28 Oct. 1996 the performance from both hybrid seeds were described by the same equation. The date 28 Oct. 1996 was the best planting time and 57 d after anthesis was the best harvesting time when the percentage of seed germination was 96.1%. The methodology Bayesiana made possible the study of the germination curves and it allowed to recommend, for the two hybrid, the first harvesting time, as the viable for the sown. Still, for means of credibility intervals, it was possible the comparison of the adjusted equations for the combination of hybrid and harvesting times.No ano de 2008, a safra brasileira de milho foi de 58,7 milhões de toneladas de grãos. Essa produção dependeu, dentre outros fatores, da qualidade das sementes, que é prioridade nas unidades de beneficiamento, secagem e classificação. Nesse contexto, propõe-se realizar estudos sobre a germinação de sementes por meio de métodos de regressão. Utilizando-se nove conjuntos de sementes de milho híbrido OC 705, submetidas ao teste de envelhecimento acelerado à temperatura de 43ºC a cada 24 horas, estimou-se o percentual de germinação, por meio da análise de regressão probito, cuja equação do probito é dada por P(Y=y)=C+ (1-C).F(β0+β1.log(x)). Os testes do Chi-quadrado de Pearson e do Chi-quadrado da razão de verossimilhança indicaram que a regressão probito proporcionou bom ajuste aos dados, fornecendo valores estimados com boa precisão. Também foi possível descrever, por meio da regressão não-linear, a curva de percentuais germinativos utilizando o modelo de regressão logístico dado pela equação y(t)=C/(1+exp(B(t-M))). Esse modelo ajustou-se adequadamente aos nove conjuntos de dados de percentual de germinação e o cálculo do viés de Box e das curvaturas permitiu a escolha do lote três como o de melhor qualidade. Utilizando-se de dados de percentuais germinativos de sementes de milho híbrido OC 705 e CD 5501, em função dos dias de amostragens, em duas épocas de semeadura, ajustou-se o modelo y(t)=A-B.exp(-Ct). Os testes de comparação de modelos indicaram que a época de semeadura de (28/10/96) pode ter o percentual de germinação dos dois híbridos descritos por uma única equação. Verificou-se, ainda, que a época de (28/10/96) foi a melhor para a semeadura dos dois híbridos, devendo a colheita ser realizada 57 dias após o florescimento feminino, para obter o percentual máximo de 96,1% de germinação. A metodologia Bayesiana possibilitou o estudo das curvas de germinação e permitiu recomendar, para os dois híbridos, a primeira época de semeadura, 28/10/96, como a mais viável. Os resultados indicaram o tempo ideal de colheita, 57 dias após o florescimento feminino, para obter o percentual máximo de 96,1% de germinação. Ainda por meios de intervalos de credibilidade foi possível a comparação das equações ajustadas para a combinação de híbridos e/ou épocas de semeadura.x, 116 fUniversidade Estadual de MaringáBrasilPrograma de Pós-Graduação em AgronomiaUEMMaringá, PRDepartamento de AgronomiaCarlos Alberto ScapimBruno Grimaldo Martinho Churata - UFPRDécio Sperandio - UEMAntonio Carlos Andrade Gonçalves - UEMTerezinha Aparecida Guedes - UEMGazola, Sebastião2018-04-04T17:23:42Z2018-04-04T17:23:42Z2009info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesishttp://repositorio.uem.br:8080/jspui/handle/1/1155porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM)instname:Universidade Estadual de Maringá (UEM)instacron:UEM2018-04-20T17:26:57Zoai:localhost:1/1155Repositório InstitucionalPUBhttp://repositorio.uem.br:8080/oai/requestopendoar:2024-04-23T14:54:03.569557Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
title |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
spellingShingle |
Modelagem de percentuais de germinação de sementes de milho em função do tempo Gazola, Sebastião Milho Germinação de sementes Modelagem Regressão não linear Regressão probito Inferência bayesiana. Nonlinear regression Seed germination Probit analyses Bayesian inference. Ciências Agrárias Agronomia |
title_short |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
title_full |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
title_fullStr |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
title_full_unstemmed |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
title_sort |
Modelagem de percentuais de germinação de sementes de milho em função do tempo |
author |
Gazola, Sebastião |
author_facet |
Gazola, Sebastião |
author_role |
author |
dc.contributor.none.fl_str_mv |
Carlos Alberto Scapim Bruno Grimaldo Martinho Churata - UFPR Décio Sperandio - UEM Antonio Carlos Andrade Gonçalves - UEM Terezinha Aparecida Guedes - UEM |
dc.contributor.author.fl_str_mv |
Gazola, Sebastião |
dc.subject.por.fl_str_mv |
Milho Germinação de sementes Modelagem Regressão não linear Regressão probito Inferência bayesiana. Nonlinear regression Seed germination Probit analyses Bayesian inference. Ciências Agrárias Agronomia |
topic |
Milho Germinação de sementes Modelagem Regressão não linear Regressão probito Inferência bayesiana. Nonlinear regression Seed germination Probit analyses Bayesian inference. Ciências Agrárias Agronomia |
description |
In 2008, the national production of grains was about 58.7 million of tonnes for which the seed quality had the most effective contribution. However, the seed quality is reduced during warehouse storage and the prediction of seed lot performance under such conditions has been a challenge for seed technologist. Therefore, research programs must always investigate the seed lots performance in which the percentage of germination during the storage could properly be described by regression models. In this context, the germination performance of aged seeds of maize was estimated by the probit P(Y=y)=C+ (1-C).F(β0+β1.log(x)) as an alternative to the simplified equation in which Vp=Vі‾p.tg(β). Seeds from three seed lots of the hybrid maize OC 705 were aged at 43 °C for 24, 48, 72, 96, 120, 144, 168 and 192 h. The seeds were stored under warehouse conditions and the experiment was replicated three times. Coefficients of determination at most of 0.92 had no goodness of fit to describe the data by the simplified equation. On the other hand, the x² of the Pearson and log-likelihood tests indicated significant goodness of fit for the same data described by the probit model. Next, another analysis was carried out to fit the logistic model y(t)=C/(1+exp(B(t-M))) to the same data. The goodness of fit was evaluated by the parameter and intrinsic curvatures and bias of Box which were important in identifying the seed lot with the best fit. Finally, data from another experiment was analyzed to describe the germination performance of hybrid seeds of maize °C 705 and CD 5501 along sampling days and during two planting times by using the nonlinear model y(t)=A-B.exp(-Ct). First, the identity of the models indicated that in the seeding time 28 Oct. 1996 the performance from both hybrid seeds were described by the same equation. The date 28 Oct. 1996 was the best planting time and 57 d after anthesis was the best harvesting time when the percentage of seed germination was 96.1%. The methodology Bayesiana made possible the study of the germination curves and it allowed to recommend, for the two hybrid, the first harvesting time, as the viable for the sown. Still, for means of credibility intervals, it was possible the comparison of the adjusted equations for the combination of hybrid and harvesting times. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009 2018-04-04T17:23:42Z 2018-04-04T17:23:42Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.uem.br:8080/jspui/handle/1/1155 |
url |
http://repositorio.uem.br:8080/jspui/handle/1/1155 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil Programa de Pós-Graduação em Agronomia UEM Maringá, PR Departamento de Agronomia |
publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil Programa de Pós-Graduação em Agronomia UEM Maringá, PR Departamento de Agronomia |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
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Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
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Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
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Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM) |
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