Crescimento de linho oleaginoso descrito por modelos de regressão não lineares
Main Author: | |
---|---|
Publication Date: | 2022 |
Format: | Doctoral thesis |
Language: | por |
Source: | Biblioteca Digital de Teses e Dissertações do UFSM |
Download full: | http://repositorio.ufsm.br/handle/1/27871 |
Summary: | The cultivation of linseed is an activity with high potential because it is a rustic plant, with low production costs and high demand in the domestic and foreign markets due to its nutritional and economic importance. However, it is little cultivated nationally due to the lack of studies on the cultivars and varieties used and the plant-atmosphere interactions. Thus, the objective of this study was to model the growth of linseed, using two varieties and two cultivars, cultivated in different agricultural years and sowing times, and adjusting nonlinear logistic and von Bertalanffy regression models, in order to indicate them as Statistical analysis tool to describe linseed growth. The data came from experiments carried out between 2014 and 2020, in the city of Curitibanos, Santa Catarina. The design was randomized blocks, with the treatments being the Dourada and Marrom varieties and the Aguará and Caburé cultivars, with four replications. Weekly evaluations were made of the number of leaves, plant height and number of secondary stems and, every two weeks, of total dry mass. The data were then organized into four collection methods: longitudinal, mean, random and cross-sectional, and subsequently tested in non-linear logistic and von Bertalanffy models. The best model was selected based on the value of the adjusted coefficient of determination, adjusted standard error, residual standard deviation, Akaike information criterion, Bayesian criterion and intrinsic and parametric non-linearity. In addition, the critical points of the model were obtained, namely the points of: maximum acceleration, inflection, maximum deceleration and asymptotic deceleration. The studied variables present a sigmoidal behavior, which allowed the adjustment of non-linear models, and among them, the logistic one was the most indicated, since it represents in a real way the estimates of the parameters and the critical points of the model, being an important way to evaluate growth variables of linseed. Among the data collection methods, there were better adjustments for the longitudinal, average and cross-sectional methods, the latter being considered an applicable alternative for the researcher in cases of need to reduce time, manpower or resources to conduct the experiment. From the logistic model, it was possible to infer about the growth of varieties and cultivars, in different years and sowing times, since the linseed cycle is directly related to the conditions of temperature, precipitation and sowing time. Thus, plant-atmosphere interactions are essential to understand the growth of agricultural crops, helping to choose management practices and ensuring high production rates. Although this work focuses on the linseed crop, the models are an analysis alternative for any agricultural crop. |
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2023-02-23T14:29:58Z2023-02-23T14:29:58Z2022-11-25http://repositorio.ufsm.br/handle/1/27871The cultivation of linseed is an activity with high potential because it is a rustic plant, with low production costs and high demand in the domestic and foreign markets due to its nutritional and economic importance. However, it is little cultivated nationally due to the lack of studies on the cultivars and varieties used and the plant-atmosphere interactions. Thus, the objective of this study was to model the growth of linseed, using two varieties and two cultivars, cultivated in different agricultural years and sowing times, and adjusting nonlinear logistic and von Bertalanffy regression models, in order to indicate them as Statistical analysis tool to describe linseed growth. The data came from experiments carried out between 2014 and 2020, in the city of Curitibanos, Santa Catarina. The design was randomized blocks, with the treatments being the Dourada and Marrom varieties and the Aguará and Caburé cultivars, with four replications. Weekly evaluations were made of the number of leaves, plant height and number of secondary stems and, every two weeks, of total dry mass. The data were then organized into four collection methods: longitudinal, mean, random and cross-sectional, and subsequently tested in non-linear logistic and von Bertalanffy models. The best model was selected based on the value of the adjusted coefficient of determination, adjusted standard error, residual standard deviation, Akaike information criterion, Bayesian criterion and intrinsic and parametric non-linearity. In addition, the critical points of the model were obtained, namely the points of: maximum acceleration, inflection, maximum deceleration and asymptotic deceleration. The studied variables present a sigmoidal behavior, which allowed the adjustment of non-linear models, and among them, the logistic one was the most indicated, since it represents in a real way the estimates of the parameters and the critical points of the model, being an important way to evaluate growth variables of linseed. Among the data collection methods, there were better adjustments for the longitudinal, average and cross-sectional methods, the latter being considered an applicable alternative for the researcher in cases of need to reduce time, manpower or resources to conduct the experiment. From the logistic model, it was possible to infer about the growth of varieties and cultivars, in different years and sowing times, since the linseed cycle is directly related to the conditions of temperature, precipitation and sowing time. Thus, plant-atmosphere interactions are essential to understand the growth of agricultural crops, helping to choose management practices and ensuring high production rates. Although this work focuses on the linseed crop, the models are an analysis alternative for any agricultural crop.O cultivo de linho oleaginoso é uma atividade de alto potencial por ser uma planta rústica, com baixo custo de produção e possuir elevada demanda de mercado interno e externo devido sua importância nutricional e econômica. Entretanto, é pouco cultivada nacionalmente pela falta de estudos sobre as cultivares e variedades utilizadas e as interações planta-atmosfera. Assim, o objetivo deste estudo foi modelar o crescimento de linho oleaginoso, utilizando duas variedades e duas cultivares, cultivadas em diferentes anos agrícolas e épocas de semeadura e ajustando aos modelos de regressão não lineares logístico e von Bertalanffy, a fim de indicálos como ferramenta de análise estatística para descrever o crescimento do linho oleaginoso. Os dados foram provenientes de experimentos realizados entre 2014 e 2020, no município de Curitibanos, Santa Catarina. O delineamento foi de blocos casualizados, sendo os tratamentos as variedades Dourada e Marrom e as cultivares Aguará e Caburé, com quatro repetições. Realizou-se avaliações semanalmente do número de folhas, altura de planta e número de hastes secundárias e, quinzenalmente de massa seca total. Os dados então foram organizados em quatro métodos de coleta: longitudinal, média, aleatório e transversal, e posteriormente testados nos modelos não linear logístico e von Bertalanffy. O melhor modelo foi selecionado com base no valor do coeficiente de determinação ajustado, erro padrão ajustado, desvio padrão residual, critério de informação de Akaike, critério Bayesiano e na não linearidade intrínseca e paramétrica. Além disso, foram obtidos os pontos críticos do modelo, sendo eles os pontos de: aceleração máxima, inflexão, desaceleração máxima e desaceleração assintótica. As variáveis estudadas apresentam comportamento sigmoidal, o que possibilitou o ajuste de modelos não lineares, sendo que dentre eles, o logístico foi o mais indicado, pois representa de maneira real as estimativas dos parâmetros e dos pontos críticos do modelo, sendo uma importante forma para avaliar as variáveis de crescimento do linho oleaginoso. Entre os métodos de coleta dos dados, houve melhores ajustes para os métodos longitudinal, média e transversal, sendo este último, considerado uma alternativa aplicável para o pesquisador em casos de necessidade de redução de tempo, mão de obra ou recursos para condução do experimento. A partir do modelo logístico foi possível inferir sobre o crescimento das variedades e cultivares, nos diferentes anos e épocas de semeadura, pois o ciclo do linho oleaginoso está diretamente relacionado as condições de temperatura, precipitação e época de semeadura. Assim, as interações planta-atmosfera são essenciais para entender o crescimento das culturas agrícolas, auxiliando na escolha dos manejos e garantindo altos índices produtivos. Apesar desse trabalho se concentrar na cultura do linho oleaginoso, os modelos são uma alternativa de análise para qualquer cultura agrícola.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em AgronomiaUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessLinum usitatissimum L.Modelo logísticoModelo von BertalanffyVon Bertalanffy modelLogistic modelCNPQ::CIENCIAS AGRARIAS::AGRONOMIACrescimento de linho oleaginoso descrito por modelos de regressão não linearesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisLúcio, Alessandro Dal'Colhttp://lattes.cnpq.br/0972869223145503Dornelles, Sylvio Henrique BidelFolmamm, Diego NicolauBosco, Leosane CristinaCarvalho, Ivan Ricardohttp://lattes.cnpq.br/5635108296356247Peripolli, Mariane500100000009600600600600600600600d51ee404-e7f0-41c1-bf30-c5fa02c4e509c8613dbd-281f-4cd5-8e68-5ff3152690c9d5f46eb0-6e88-4a8c-acd5-90c72fa0010deaa348a4-6a83-4c96-9005-1de8d9ce13015530eca8-6349-4b57-9ebe-a9721edde5d41e193e3b-295d-4f3c-9ef8-361672fef592reponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/27871/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52ORIGINALTES_PPGAGRONOMIA_2022_PERIPOLLI_MARIANE.pdfTES_PPGAGRONOMIA_2022_PERIPOLLI_MARIANE.pdfTese de doutoradoapplication/pdf1325680http://repositorio.ufsm.br/bitstream/1/27871/1/TES_PPGAGRONOMIA_2022_PERIPOLLI_MARIANE.pdfebee82ab19a5e958e91cfa8c00bfecb5MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/27871/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD531/278712023-02-23 11:29:59.003oai:repositorio.ufsm.br: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 Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2023-02-23T14:29:59Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
title |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
spellingShingle |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares Peripolli, Mariane Linum usitatissimum L. Modelo logístico Modelo von Bertalanffy Von Bertalanffy model Logistic model CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
title_full |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
title_fullStr |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
title_full_unstemmed |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
title_sort |
Crescimento de linho oleaginoso descrito por modelos de regressão não lineares |
author |
Peripolli, Mariane |
author_facet |
Peripolli, Mariane |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Lúcio, Alessandro Dal'Col |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/0972869223145503 |
dc.contributor.referee1.fl_str_mv |
Dornelles, Sylvio Henrique Bidel |
dc.contributor.referee2.fl_str_mv |
Folmamm, Diego Nicolau |
dc.contributor.referee3.fl_str_mv |
Bosco, Leosane Cristina |
dc.contributor.referee4.fl_str_mv |
Carvalho, Ivan Ricardo |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/5635108296356247 |
dc.contributor.author.fl_str_mv |
Peripolli, Mariane |
contributor_str_mv |
Lúcio, Alessandro Dal'Col Dornelles, Sylvio Henrique Bidel Folmamm, Diego Nicolau Bosco, Leosane Cristina Carvalho, Ivan Ricardo |
dc.subject.por.fl_str_mv |
Linum usitatissimum L. Modelo logístico Modelo von Bertalanffy Von Bertalanffy model |
topic |
Linum usitatissimum L. Modelo logístico Modelo von Bertalanffy Von Bertalanffy model Logistic model CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Logistic model |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
The cultivation of linseed is an activity with high potential because it is a rustic plant, with low production costs and high demand in the domestic and foreign markets due to its nutritional and economic importance. However, it is little cultivated nationally due to the lack of studies on the cultivars and varieties used and the plant-atmosphere interactions. Thus, the objective of this study was to model the growth of linseed, using two varieties and two cultivars, cultivated in different agricultural years and sowing times, and adjusting nonlinear logistic and von Bertalanffy regression models, in order to indicate them as Statistical analysis tool to describe linseed growth. The data came from experiments carried out between 2014 and 2020, in the city of Curitibanos, Santa Catarina. The design was randomized blocks, with the treatments being the Dourada and Marrom varieties and the Aguará and Caburé cultivars, with four replications. Weekly evaluations were made of the number of leaves, plant height and number of secondary stems and, every two weeks, of total dry mass. The data were then organized into four collection methods: longitudinal, mean, random and cross-sectional, and subsequently tested in non-linear logistic and von Bertalanffy models. The best model was selected based on the value of the adjusted coefficient of determination, adjusted standard error, residual standard deviation, Akaike information criterion, Bayesian criterion and intrinsic and parametric non-linearity. In addition, the critical points of the model were obtained, namely the points of: maximum acceleration, inflection, maximum deceleration and asymptotic deceleration. The studied variables present a sigmoidal behavior, which allowed the adjustment of non-linear models, and among them, the logistic one was the most indicated, since it represents in a real way the estimates of the parameters and the critical points of the model, being an important way to evaluate growth variables of linseed. Among the data collection methods, there were better adjustments for the longitudinal, average and cross-sectional methods, the latter being considered an applicable alternative for the researcher in cases of need to reduce time, manpower or resources to conduct the experiment. From the logistic model, it was possible to infer about the growth of varieties and cultivars, in different years and sowing times, since the linseed cycle is directly related to the conditions of temperature, precipitation and sowing time. Thus, plant-atmosphere interactions are essential to understand the growth of agricultural crops, helping to choose management practices and ensuring high production rates. Although this work focuses on the linseed crop, the models are an analysis alternative for any agricultural crop. |
publishDate |
2022 |
dc.date.issued.fl_str_mv |
2022-11-25 |
dc.date.accessioned.fl_str_mv |
2023-02-23T14:29:58Z |
dc.date.available.fl_str_mv |
2023-02-23T14:29:58Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
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publishedVersion |
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http://repositorio.ufsm.br/handle/1/27871 |
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http://repositorio.ufsm.br/handle/1/27871 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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500100000009 |
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600 600 600 600 600 600 600 |
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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.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Agronomia |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
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