Description of blackberry fruit growth by nonlinear regression models
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/42732 |
Resumo: | Blackberry is a small fruit with several properties beneficial to human health and its cultivation is an alternative for small producers due to its fast and high financial return. Studying the growth of fruits over time is extremely important to understand their development, helping in the most appropriate crop management, avoiding post-harvest losses, which is one of the aggravating factors of blackberry cultivation, being a short shelf life fruit. Thus, growth curves are highlighted in this type of study and modeling through statistical models helps understanding how such growth occurs. Data from this study were obtained from an experiment conducted at the Federal University of Lavras in 2015. The aim of this study was to adjust nonlinear, double Logistic and double Gompertz models to describe the diameter growth of four blackberry cultivars (‘Brazos’, ‘Choctaw’, ‘Guarani’ and ‘Tupy’). Estimations of parameters were obtained using the least squares method and the Gauss-Newton algorithm, with the “nls” and “glns” functions of the R statistical software. The comparison of adjustments was made by the Akaike information criterion (AICc), residual standard deviation (RSD) and adjusted determination coefficient (R2 aj). The models satisfactorily described data, choosing the Logistic double model for ‘Brazos’ and ‘Guarani’ cultivars and the double Gompertz model for ‘Tupy’ and ‘Choctaw’ cultivars. |
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Description of blackberry fruit growth by nonlinear regression modelsDescrição do crescimento de frutos de amora-preta por modelos de regressão não linearRegression analysisModel SelectionFit qualitySigmoidSmall fruitsFruit developmentAnálise de regressãoSeleção de modelosQualidade de ajustePequenas frutasComportamento sigmoideDesenvolvimento de frutosBlackberry is a small fruit with several properties beneficial to human health and its cultivation is an alternative for small producers due to its fast and high financial return. Studying the growth of fruits over time is extremely important to understand their development, helping in the most appropriate crop management, avoiding post-harvest losses, which is one of the aggravating factors of blackberry cultivation, being a short shelf life fruit. Thus, growth curves are highlighted in this type of study and modeling through statistical models helps understanding how such growth occurs. Data from this study were obtained from an experiment conducted at the Federal University of Lavras in 2015. The aim of this study was to adjust nonlinear, double Logistic and double Gompertz models to describe the diameter growth of four blackberry cultivars (‘Brazos’, ‘Choctaw’, ‘Guarani’ and ‘Tupy’). Estimations of parameters were obtained using the least squares method and the Gauss-Newton algorithm, with the “nls” and “glns” functions of the R statistical software. The comparison of adjustments was made by the Akaike information criterion (AICc), residual standard deviation (RSD) and adjusted determination coefficient (R2 aj). The models satisfactorily described data, choosing the Logistic double model for ‘Brazos’ and ‘Guarani’ cultivars and the double Gompertz model for ‘Tupy’ and ‘Choctaw’ cultivars.A amora-preta é um pequeno fruto com várias propriedades benéficas à saúde humana, e seu cultivo é uma alternativa para os pequenos produtores. Estudar o crescimento de frutos, ao longo do tempo, é extremamente importante para entender seu desenvolvimento, auxiliando no manejo mais adequado da cultura, evitando, por exemplo, perda após a colheita, que é um dos fatores agravantes da amora-preta, por ser um fruto de curto período de prateleira. Sendo assim, as curvas de crescimento ganham destaque, nesse tipo de estudo, e a modelagem, por meio de modelos estatísticos, ajuda a entender como tal crescimento acontece. Conduziu-se este trabalho com o objetivo de ajustar modelos não lineares, duplo Logístico e duplo Gompertz, para descrever o crescimento do diâmetro de quatro cultivares da amora-preta (Brazos, Choctaw, Guarani e Tupy). As estimativas dos parâmetros foram obtidas por meio do método de mínimos quadrados, utilizando o algoritmo de Gauss-Newton, por meio do software R. A comparação dos ajustes foi feitas pelo critério de informação Akaike (AICc), desvio padrão residual (DPR) e coeficiente de determinação ajustado (R2 aj). Os modelos descreveram de forma satisfatória os dados, sendo escolhido o modelo duplo Logístico para as cultivares Brazos e Guarani, e o duplo Gompertz para as cultivares Tupy e Choctaw.Sociedade Brasileira de Fruticultura2020-08-31T17:43:50Z2020-08-31T17:43:50Z2020-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSILVA, E. M. da et al. Description of blackberry fruit growth by nonlinear regression models. Revista Brasileira de Fruticultura, Jaboticabal, v. 42, n. 2, 2020. DOI: https://doi.org/10.1590/0100-29452020177.http://repositorio.ufla.br/jspui/handle/1/42732Revista Brasileira de Fruticulturareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessSilva, Édipo Menezes daTadeu, Maraísa HellenSilva, Victor Ferreira daPio, RafaelFernandes, Tales JesusMuniz, Joel Augustoeng2020-08-31T17:44:09Zoai:localhost:1/42732Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-08-31T17:44:09Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Description of blackberry fruit growth by nonlinear regression models Descrição do crescimento de frutos de amora-preta por modelos de regressão não linear |
title |
Description of blackberry fruit growth by nonlinear regression models |
spellingShingle |
Description of blackberry fruit growth by nonlinear regression models Silva, Édipo Menezes da Regression analysis Model Selection Fit quality Sigmoid Small fruits Fruit development Análise de regressão Seleção de modelos Qualidade de ajuste Pequenas frutas Comportamento sigmoide Desenvolvimento de frutos |
title_short |
Description of blackberry fruit growth by nonlinear regression models |
title_full |
Description of blackberry fruit growth by nonlinear regression models |
title_fullStr |
Description of blackberry fruit growth by nonlinear regression models |
title_full_unstemmed |
Description of blackberry fruit growth by nonlinear regression models |
title_sort |
Description of blackberry fruit growth by nonlinear regression models |
author |
Silva, Édipo Menezes da |
author_facet |
Silva, Édipo Menezes da Tadeu, Maraísa Hellen Silva, Victor Ferreira da Pio, Rafael Fernandes, Tales Jesus Muniz, Joel Augusto |
author_role |
author |
author2 |
Tadeu, Maraísa Hellen Silva, Victor Ferreira da Pio, Rafael Fernandes, Tales Jesus Muniz, Joel Augusto |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Silva, Édipo Menezes da Tadeu, Maraísa Hellen Silva, Victor Ferreira da Pio, Rafael Fernandes, Tales Jesus Muniz, Joel Augusto |
dc.subject.por.fl_str_mv |
Regression analysis Model Selection Fit quality Sigmoid Small fruits Fruit development Análise de regressão Seleção de modelos Qualidade de ajuste Pequenas frutas Comportamento sigmoide Desenvolvimento de frutos |
topic |
Regression analysis Model Selection Fit quality Sigmoid Small fruits Fruit development Análise de regressão Seleção de modelos Qualidade de ajuste Pequenas frutas Comportamento sigmoide Desenvolvimento de frutos |
description |
Blackberry is a small fruit with several properties beneficial to human health and its cultivation is an alternative for small producers due to its fast and high financial return. Studying the growth of fruits over time is extremely important to understand their development, helping in the most appropriate crop management, avoiding post-harvest losses, which is one of the aggravating factors of blackberry cultivation, being a short shelf life fruit. Thus, growth curves are highlighted in this type of study and modeling through statistical models helps understanding how such growth occurs. Data from this study were obtained from an experiment conducted at the Federal University of Lavras in 2015. The aim of this study was to adjust nonlinear, double Logistic and double Gompertz models to describe the diameter growth of four blackberry cultivars (‘Brazos’, ‘Choctaw’, ‘Guarani’ and ‘Tupy’). Estimations of parameters were obtained using the least squares method and the Gauss-Newton algorithm, with the “nls” and “glns” functions of the R statistical software. The comparison of adjustments was made by the Akaike information criterion (AICc), residual standard deviation (RSD) and adjusted determination coefficient (R2 aj). The models satisfactorily described data, choosing the Logistic double model for ‘Brazos’ and ‘Guarani’ cultivars and the double Gompertz model for ‘Tupy’ and ‘Choctaw’ cultivars. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-31T17:43:50Z 2020-08-31T17:43:50Z 2020-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
SILVA, E. M. da et al. Description of blackberry fruit growth by nonlinear regression models. Revista Brasileira de Fruticultura, Jaboticabal, v. 42, n. 2, 2020. DOI: https://doi.org/10.1590/0100-29452020177. http://repositorio.ufla.br/jspui/handle/1/42732 |
identifier_str_mv |
SILVA, E. M. da et al. Description of blackberry fruit growth by nonlinear regression models. Revista Brasileira de Fruticultura, Jaboticabal, v. 42, n. 2, 2020. DOI: https://doi.org/10.1590/0100-29452020177. |
url |
http://repositorio.ufla.br/jspui/handle/1/42732 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Fruticultura |
publisher.none.fl_str_mv |
Sociedade Brasileira de Fruticultura |
dc.source.none.fl_str_mv |
Revista Brasileira de Fruticultura reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1815438976116326400 |