Critical points in logistic growth curves and treatment comparisons
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/S0103-90162012000500004 http://hdl.handle.net/11449/226996 |
Resumo: | Several biological phenomena have a behavior over time mathematically characterized by a strong increasing function in the early stages of development, then by a less pronounced growth, sometimes showing stability. The separation between these phases is very important to the researcher, since the maintenance of a less productive phase results in uneconomical activity. In this report we present methods of determining critical points in logistic functions that separate the early stages of growth from the asymptotic phase, with the aim of establishing a stopping critical point in the growth and on this basis determine differences in treatments. The logistic growth model is fitted to experimental data of imbibition of araribá seeds (Centrolobium tomentosum). To determine stopping critical points the following methods were used: i) accelerating growth function, ii) tangent at the inflection point, iii) segmented regression; iv) modified segmented regression; v) non-significant difference; and vi) non-significant difference by simulation. The analysis of variance of the abscissas and ordinates of the breakpoints was performed with the objective of comparing treatments and methods used to determine the critical points. The methods of segmented regression and of the tangent at the inflection point lead to early stopping points, in comparison with other methods, with proportions ordinate/asymptote lower than 0.90. The non-significant difference method by simulation had higher values of abscissas for stopping point, with an average proportion ordinate/asymptote equal to 0.986. An intermediate proportion of 0.908 was observed for the acceleration function method. |
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Critical points in logistic growth curves and treatment comparisonsAsymptotic regressionNonlinear regressionSeeds imbibitionStopping critical levelSeveral biological phenomena have a behavior over time mathematically characterized by a strong increasing function in the early stages of development, then by a less pronounced growth, sometimes showing stability. The separation between these phases is very important to the researcher, since the maintenance of a less productive phase results in uneconomical activity. In this report we present methods of determining critical points in logistic functions that separate the early stages of growth from the asymptotic phase, with the aim of establishing a stopping critical point in the growth and on this basis determine differences in treatments. The logistic growth model is fitted to experimental data of imbibition of araribá seeds (Centrolobium tomentosum). To determine stopping critical points the following methods were used: i) accelerating growth function, ii) tangent at the inflection point, iii) segmented regression; iv) modified segmented regression; v) non-significant difference; and vi) non-significant difference by simulation. The analysis of variance of the abscissas and ordinates of the breakpoints was performed with the objective of comparing treatments and methods used to determine the critical points. The methods of segmented regression and of the tangent at the inflection point lead to early stopping points, in comparison with other methods, with proportions ordinate/asymptote lower than 0.90. The non-significant difference method by simulation had higher values of abscissas for stopping point, with an average proportion ordinate/asymptote equal to 0.986. An intermediate proportion of 0.908 was observed for the acceleration function method.UNESP/IBB Depto. de Bioestatística, C.P. 510, 18618-970 - Botucatu, SPUNESP/IBB Depto. de Bioestatística, C.P. 510, 18618-970 - Botucatu, SPUniversidade Estadual Paulista (UNESP)Passos, José Raimundo de Souza [UNESP]de Pinho, Sheila Zambello [UNESP]de Carvalho, Lídia Raquel [UNESP]Mischan, Martha Maria [UNESP]2022-04-29T05:24:26Z2022-04-29T05:24:26Z2012-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article308-312http://dx.doi.org/10.1590/S0103-90162012000500004Scientia Agricola, v. 69, n. 5, p. 308-312, 2012.0103-90161678-992Xhttp://hdl.handle.net/11449/22699610.1590/S0103-901620120005000042-s2.0-84867439606Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengScientia Agricolainfo:eu-repo/semantics/openAccess2022-04-29T05:24:26Zoai:repositorio.unesp.br:11449/226996Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:11:46.797768Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Critical points in logistic growth curves and treatment comparisons |
title |
Critical points in logistic growth curves and treatment comparisons |
spellingShingle |
Critical points in logistic growth curves and treatment comparisons Passos, José Raimundo de Souza [UNESP] Asymptotic regression Nonlinear regression Seeds imbibition Stopping critical level |
title_short |
Critical points in logistic growth curves and treatment comparisons |
title_full |
Critical points in logistic growth curves and treatment comparisons |
title_fullStr |
Critical points in logistic growth curves and treatment comparisons |
title_full_unstemmed |
Critical points in logistic growth curves and treatment comparisons |
title_sort |
Critical points in logistic growth curves and treatment comparisons |
author |
Passos, José Raimundo de Souza [UNESP] |
author_facet |
Passos, José Raimundo de Souza [UNESP] de Pinho, Sheila Zambello [UNESP] de Carvalho, Lídia Raquel [UNESP] Mischan, Martha Maria [UNESP] |
author_role |
author |
author2 |
de Pinho, Sheila Zambello [UNESP] de Carvalho, Lídia Raquel [UNESP] Mischan, Martha Maria [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Passos, José Raimundo de Souza [UNESP] de Pinho, Sheila Zambello [UNESP] de Carvalho, Lídia Raquel [UNESP] Mischan, Martha Maria [UNESP] |
dc.subject.por.fl_str_mv |
Asymptotic regression Nonlinear regression Seeds imbibition Stopping critical level |
topic |
Asymptotic regression Nonlinear regression Seeds imbibition Stopping critical level |
description |
Several biological phenomena have a behavior over time mathematically characterized by a strong increasing function in the early stages of development, then by a less pronounced growth, sometimes showing stability. The separation between these phases is very important to the researcher, since the maintenance of a less productive phase results in uneconomical activity. In this report we present methods of determining critical points in logistic functions that separate the early stages of growth from the asymptotic phase, with the aim of establishing a stopping critical point in the growth and on this basis determine differences in treatments. The logistic growth model is fitted to experimental data of imbibition of araribá seeds (Centrolobium tomentosum). To determine stopping critical points the following methods were used: i) accelerating growth function, ii) tangent at the inflection point, iii) segmented regression; iv) modified segmented regression; v) non-significant difference; and vi) non-significant difference by simulation. The analysis of variance of the abscissas and ordinates of the breakpoints was performed with the objective of comparing treatments and methods used to determine the critical points. The methods of segmented regression and of the tangent at the inflection point lead to early stopping points, in comparison with other methods, with proportions ordinate/asymptote lower than 0.90. The non-significant difference method by simulation had higher values of abscissas for stopping point, with an average proportion ordinate/asymptote equal to 0.986. An intermediate proportion of 0.908 was observed for the acceleration function method. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-09-01 2022-04-29T05:24:26Z 2022-04-29T05:24:26Z |
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 |
http://dx.doi.org/10.1590/S0103-90162012000500004 Scientia Agricola, v. 69, n. 5, p. 308-312, 2012. 0103-9016 1678-992X http://hdl.handle.net/11449/226996 10.1590/S0103-90162012000500004 2-s2.0-84867439606 |
url |
http://dx.doi.org/10.1590/S0103-90162012000500004 http://hdl.handle.net/11449/226996 |
identifier_str_mv |
Scientia Agricola, v. 69, n. 5, p. 308-312, 2012. 0103-9016 1678-992X 10.1590/S0103-90162012000500004 2-s2.0-84867439606 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Scientia Agricola |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
308-312 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129170446745600 |