The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar

Detalhes bibliográficos
Autor(a) principal: Ribeiro,Thais Destefani
Data de Publicação: 2018
Outros Autores: Savian,Taciana Villela, Fernandes,Tales Jesus, Muniz,Joel Augusto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100202
Resumo: ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.
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spelling The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivarBiometric measurementsAsian pearmodel Gompertzlogistic modelABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.Universidade Federal de Santa Maria2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100202Ciência Rural v.48 n.1 2018reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20161097info:eu-repo/semantics/openAccessRibeiro,Thais DestefaniSavian,Taciana VillelaFernandes,Tales JesusMuniz,Joel Augustoeng2018-01-19T00:00:00ZRevista
dc.title.none.fl_str_mv The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
title The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
spellingShingle The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
Ribeiro,Thais Destefani
Biometric measurements
Asian pear
model Gompertz
logistic model
title_short The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
title_full The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
title_fullStr The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
title_full_unstemmed The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
title_sort The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar
author Ribeiro,Thais Destefani
author_facet Ribeiro,Thais Destefani
Savian,Taciana Villela
Fernandes,Tales Jesus
Muniz,Joel Augusto
author_role author
author2 Savian,Taciana Villela
Fernandes,Tales Jesus
Muniz,Joel Augusto
author2_role author
author
author
dc.contributor.author.fl_str_mv Ribeiro,Thais Destefani
Savian,Taciana Villela
Fernandes,Tales Jesus
Muniz,Joel Augusto
dc.subject.por.fl_str_mv Biometric measurements
Asian pear
model Gompertz
logistic model
topic Biometric measurements
Asian pear
model Gompertz
logistic model
description ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
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=S0103-84782018000100202
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100202
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20161097
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 Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.48 n.1 2018
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1749140552116338688

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