Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.2134/agronj2018.11.0700 http://hdl.handle.net/11449/201314 |
Resumo: | Seed longevity is characterized as the time for which seed remains viable during storage. Seed longevity can be estimated by a Probit model that determines the period in which 50% of seeds have lost viability (P50). The transformed data are binary and when they are not normally distributed, it is necessary to modify the Probit model or apply other functions to estimate longevity. This work aimed studied the use of the Logit, Cauchy, and Cauchy–Santos– Sartori–Faria (Cauchy-SSF) functions to estimate the longevity of soybean seed [Glycine max (L.) Merr.] and compared Probit longevity models for the ordinary least squares (OLS) adjustment method and the generalized linear model (GLM). Ten seed lots were used to estimate water content, germination, and longevity. The P50 data were transformed via the Probit, Logit, Cauchy, and Cauchy-SSF functions to estimate the coefficients of determination, the Akaike information criterion, deviance, dispersion, and the regression residuals. The effect on the results was observed, depending on the link function. The Cauchy-SSF function as part of the OLS method estimated longevity in eight seed lots within the interval of interest (II), and the Cauchy function as part of the GLM estimated longevity in nine seed lots. The Cauchy, Cauchy-SSF, and Logit models were capable of estimating the longevity of soybean seeds (P50) slightly better than the Probit model. We suggest the Cauchy-SSF function for the OLS method and the Cauchy function for the GLM method to estimate soybean seed longevity when the data are not normally distributed. |
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spelling |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybeanSeed longevity is characterized as the time for which seed remains viable during storage. Seed longevity can be estimated by a Probit model that determines the period in which 50% of seeds have lost viability (P50). The transformed data are binary and when they are not normally distributed, it is necessary to modify the Probit model or apply other functions to estimate longevity. This work aimed studied the use of the Logit, Cauchy, and Cauchy–Santos– Sartori–Faria (Cauchy-SSF) functions to estimate the longevity of soybean seed [Glycine max (L.) Merr.] and compared Probit longevity models for the ordinary least squares (OLS) adjustment method and the generalized linear model (GLM). Ten seed lots were used to estimate water content, germination, and longevity. The P50 data were transformed via the Probit, Logit, Cauchy, and Cauchy-SSF functions to estimate the coefficients of determination, the Akaike information criterion, deviance, dispersion, and the regression residuals. The effect on the results was observed, depending on the link function. The Cauchy-SSF function as part of the OLS method estimated longevity in eight seed lots within the interval of interest (II), and the Cauchy function as part of the GLM estimated longevity in nine seed lots. The Cauchy, Cauchy-SSF, and Logit models were capable of estimating the longevity of soybean seeds (P50) slightly better than the Probit model. We suggest the Cauchy-SSF function for the OLS method and the Cauchy function for the GLM method to estimate soybean seed longevity when the data are not normally distributed.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)São Paulo State Univ. (UNESP) Dep. of Plant Production and Breeding College of Agricultural SciencesFederal Inst. GoianoSão Paulo State Univ. (UNESP) Dep. of Plant Production and Breeding College of Agricultural SciencesCNPq: 305524/2015-1Universidade Estadual Paulista (Unesp)Federal Inst. GoianoDos Santos, Amanda Rithieli Pereira [UNESP]de Faria, Rute QuelviaAmorim, Deoclecio Jardim [UNESP]Giandoni, Valéria Cristina Retameiro [UNESP]da Silva, Edvaldo Aparecido Amaral [UNESP]Sartori, Maria Márcia Pereira [UNESP]2020-12-12T02:29:29Z2020-12-12T02:29:29Z2019-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article2929-2939http://dx.doi.org/10.2134/agronj2018.11.0700Agronomy Journal, v. 111, n. 6, p. 2929-2939, 2019.1435-06450002-1962http://hdl.handle.net/11449/20131410.2134/agronj2018.11.07002-s2.0-85074784717Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAgronomy Journalinfo:eu-repo/semantics/openAccess2021-10-22T17:02:21Zoai:repositorio.unesp.br:11449/201314Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:10:19.309789Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
title |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
spellingShingle |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean Dos Santos, Amanda Rithieli Pereira [UNESP] |
title_short |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
title_full |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
title_fullStr |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
title_full_unstemmed |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
title_sort |
Cauchy, cauchy–santos–sartori–faria, logit, and probit functions for estimating seed longevity in soybean |
author |
Dos Santos, Amanda Rithieli Pereira [UNESP] |
author_facet |
Dos Santos, Amanda Rithieli Pereira [UNESP] de Faria, Rute Quelvia Amorim, Deoclecio Jardim [UNESP] Giandoni, Valéria Cristina Retameiro [UNESP] da Silva, Edvaldo Aparecido Amaral [UNESP] Sartori, Maria Márcia Pereira [UNESP] |
author_role |
author |
author2 |
de Faria, Rute Quelvia Amorim, Deoclecio Jardim [UNESP] Giandoni, Valéria Cristina Retameiro [UNESP] da Silva, Edvaldo Aparecido Amaral [UNESP] Sartori, Maria Márcia Pereira [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Federal Inst. Goiano |
dc.contributor.author.fl_str_mv |
Dos Santos, Amanda Rithieli Pereira [UNESP] de Faria, Rute Quelvia Amorim, Deoclecio Jardim [UNESP] Giandoni, Valéria Cristina Retameiro [UNESP] da Silva, Edvaldo Aparecido Amaral [UNESP] Sartori, Maria Márcia Pereira [UNESP] |
description |
Seed longevity is characterized as the time for which seed remains viable during storage. Seed longevity can be estimated by a Probit model that determines the period in which 50% of seeds have lost viability (P50). The transformed data are binary and when they are not normally distributed, it is necessary to modify the Probit model or apply other functions to estimate longevity. This work aimed studied the use of the Logit, Cauchy, and Cauchy–Santos– Sartori–Faria (Cauchy-SSF) functions to estimate the longevity of soybean seed [Glycine max (L.) Merr.] and compared Probit longevity models for the ordinary least squares (OLS) adjustment method and the generalized linear model (GLM). Ten seed lots were used to estimate water content, germination, and longevity. The P50 data were transformed via the Probit, Logit, Cauchy, and Cauchy-SSF functions to estimate the coefficients of determination, the Akaike information criterion, deviance, dispersion, and the regression residuals. The effect on the results was observed, depending on the link function. The Cauchy-SSF function as part of the OLS method estimated longevity in eight seed lots within the interval of interest (II), and the Cauchy function as part of the GLM estimated longevity in nine seed lots. The Cauchy, Cauchy-SSF, and Logit models were capable of estimating the longevity of soybean seeds (P50) slightly better than the Probit model. We suggest the Cauchy-SSF function for the OLS method and the Cauchy function for the GLM method to estimate soybean seed longevity when the data are not normally distributed. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-01 2020-12-12T02:29:29Z 2020-12-12T02:29:29Z |
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/10.2134/agronj2018.11.0700 Agronomy Journal, v. 111, n. 6, p. 2929-2939, 2019. 1435-0645 0002-1962 http://hdl.handle.net/11449/201314 10.2134/agronj2018.11.0700 2-s2.0-85074784717 |
url |
http://dx.doi.org/10.2134/agronj2018.11.0700 http://hdl.handle.net/11449/201314 |
identifier_str_mv |
Agronomy Journal, v. 111, n. 6, p. 2929-2939, 2019. 1435-0645 0002-1962 10.2134/agronj2018.11.0700 2-s2.0-85074784717 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Agronomy Journal |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
2929-2939 |
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 |
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1808128613444222976 |