Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/53318 |
Resumo: | Brazil stands out worldwide for planting homogeneous forests, mainly pine and eucalyptus. Forestry production is of great importance for the country’s economy, being also a reference in sustainability, competitiveness and innovation. Of the 10 million hectares of planted trees, 76.3% is composed of the genus Eucalyptus, which makes Brazil one of the largest producers of this genus in the world. The analysis of the growth trajectory of trees of this genus can be a great ally in improving the management plans currently used. In this sense, the aim of this study was to compare the performance of the nonlinear models Gompertz, von Bertalanffy, Brody, Chapman-Richards and Schöngart, which were fit using the R software considering the first order autoregressive error structure (AR1), applied to data of average height, in meters, in relation to time, in months, totaling 15 observations obtained during six and a half years. Nonlinearity measures were used to check the adequacy of the linear approximations of models and as criteria for model selection the R2, AICC and DPR, with the Schöngart (AR1) model being the one that best fit the data. |
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Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear modelsGrowth curveAutoregressive errorsRegressionBrazil stands out worldwide for planting homogeneous forests, mainly pine and eucalyptus. Forestry production is of great importance for the country’s economy, being also a reference in sustainability, competitiveness and innovation. Of the 10 million hectares of planted trees, 76.3% is composed of the genus Eucalyptus, which makes Brazil one of the largest producers of this genus in the world. The analysis of the growth trajectory of trees of this genus can be a great ally in improving the management plans currently used. In this sense, the aim of this study was to compare the performance of the nonlinear models Gompertz, von Bertalanffy, Brody, Chapman-Richards and Schöngart, which were fit using the R software considering the first order autoregressive error structure (AR1), applied to data of average height, in meters, in relation to time, in months, totaling 15 observations obtained during six and a half years. Nonlinearity measures were used to check the adequacy of the linear approximations of models and as criteria for model selection the R2, AICC and DPR, with the Schöngart (AR1) model being the one that best fit the data.Universidade Federal de Lavras2022-08-18T20:48:36Z2022-08-18T20:48:36Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFRUHAUF, A. C. et al. Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models. Brazilian Journal of Biometrics, Lavras, v.40, n.2, p.138-151, 2022.http://repositorio.ufla.br/jspui/handle/1/53318Brazilian Journal of Biometricsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFrühauf, Ariana CamposSilva, Édipo Menezes daGranato-Souza, DanielaSilva, Edilson MarcelinoMuniz, Joel AugustoFernandes, Tales Jesuseng2022-08-18T20:48:36Zoai:localhost:1/53318Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2022-08-18T20:48:36Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
title |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
spellingShingle |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models Frühauf, Ariana Campos Growth curve Autoregressive errors Regression |
title_short |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
title_full |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
title_fullStr |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
title_full_unstemmed |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
title_sort |
Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models |
author |
Frühauf, Ariana Campos |
author_facet |
Frühauf, Ariana Campos Silva, Édipo Menezes da Granato-Souza, Daniela Silva, Edilson Marcelino Muniz, Joel Augusto Fernandes, Tales Jesus |
author_role |
author |
author2 |
Silva, Édipo Menezes da Granato-Souza, Daniela Silva, Edilson Marcelino Muniz, Joel Augusto Fernandes, Tales Jesus |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Frühauf, Ariana Campos Silva, Édipo Menezes da Granato-Souza, Daniela Silva, Edilson Marcelino Muniz, Joel Augusto Fernandes, Tales Jesus |
dc.subject.por.fl_str_mv |
Growth curve Autoregressive errors Regression |
topic |
Growth curve Autoregressive errors Regression |
description |
Brazil stands out worldwide for planting homogeneous forests, mainly pine and eucalyptus. Forestry production is of great importance for the country’s economy, being also a reference in sustainability, competitiveness and innovation. Of the 10 million hectares of planted trees, 76.3% is composed of the genus Eucalyptus, which makes Brazil one of the largest producers of this genus in the world. The analysis of the growth trajectory of trees of this genus can be a great ally in improving the management plans currently used. In this sense, the aim of this study was to compare the performance of the nonlinear models Gompertz, von Bertalanffy, Brody, Chapman-Richards and Schöngart, which were fit using the R software considering the first order autoregressive error structure (AR1), applied to data of average height, in meters, in relation to time, in months, totaling 15 observations obtained during six and a half years. Nonlinearity measures were used to check the adequacy of the linear approximations of models and as criteria for model selection the R2, AICC and DPR, with the Schöngart (AR1) model being the one that best fit the data. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-18T20:48:36Z 2022-08-18T20:48:36Z 2022 |
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 |
FRUHAUF, A. C. et al. Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models. Brazilian Journal of Biometrics, Lavras, v.40, n.2, p.138-151, 2022. http://repositorio.ufla.br/jspui/handle/1/53318 |
identifier_str_mv |
FRUHAUF, A. C. et al. Description of height growth of hybrid eucalyptus clones in semi-arid region using non-linear models. Brazilian Journal of Biometrics, Lavras, v.40, n.2, p.138-151, 2022. |
url |
http://repositorio.ufla.br/jspui/handle/1/53318 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International 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 |
Universidade Federal de Lavras |
publisher.none.fl_str_mv |
Universidade Federal de Lavras |
dc.source.none.fl_str_mv |
Brazilian Journal of Biometrics 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 |
_version_ |
1815438983841185792 |