Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira

The objetive of this study is to cluster selected trees of Eucalyptus grandis Hill ex-Maiden as a function of phenotypic, dendrometric and wood technology characteristics. In a 27 years old commercial stand, located in the northern coast of Rio Grande do Sul, 63 selected trees were cut down and clas...

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Main Authors: Merielen Lopes de Carvalho, Clovis Roberto Haselein, Elio José Santini, Solon Jonas Longhi, Silviana Rosso, Denis L. G. Fernandes, Leonel Menezes Freitas de
Format: Article
Language:Portuguese
Published: Universidade Federal de Santa Maria 2004-01-01
Series:Ciência Florestal
Online Access:http://www.redalyc.org/articulo.oa?id=53414213
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spelling doaj-5c51dd16506940d6ac4b837fc9a9385e2020-11-25T02:03:48ZporUniversidade Federal de Santa MariaCiência Florestal0103-99541980-50982004-01-01142133144Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeiraMerielen Lopes de CarvalhoClovis Roberto HaseleinElio José SantiniSolon Jonas LonghiSilviana RossoDenis L. G. FernandesLeonel Menezes Freitas deThe objetive of this study is to cluster selected trees of Eucalyptus grandis Hill ex-Maiden as a function of phenotypic, dendrometric and wood technology characteristics. In a 27 years old commercial stand, located in the northern coast of Rio Grande do Sul, 63 selected trees were cut down and classified to the phenotypic and dendrometric characteristics. Then, disks were taken at the base, 25, 50, 75 and 100% of the commercial height, and at the DBH, for basic density determination. From the two first logs above the DBH boards parallel to the pith were taken, with 25mm of thickness, for sawn wood qualitative evaluation. The selected trees were grouped into four distinct groups following cluster analysis. In Group I were classified the trees with a lower tendency of presenting boards with end splits while in Groups II and III were classified the trees with a lower tendency of presenting logs with end splits and, in Group IV were classified the trees with a higher tendency of presenting end splits of the boards and the logs. For these groups, by discriminant analysis, there were identified five variables with real power of discrimination (DBH, estimated log split perimeter, ratio height/diameter (rh/d), type of bark and sapwood volumetric percentage) and three discriminant functions. The technique of the multivariate analyze was an efficient method of grouping the selected trees of Eucalyptus grandis. The discriminant analysis enabled the selection of variables with real power of sorting the trees and determinating the discriminant functions that allow the allocation of future trees in the cluster.http://www.redalyc.org/articulo.oa?id=53414213
collection DOAJ
language Portuguese
format Article
sources DOAJ
author Merielen Lopes de Carvalho
Clovis Roberto Haselein
Elio José Santini
Solon Jonas Longhi
Silviana Rosso
Denis L. G. Fernandes
Leonel Menezes Freitas de
spellingShingle Merielen Lopes de Carvalho
Clovis Roberto Haselein
Elio José Santini
Solon Jonas Longhi
Silviana Rosso
Denis L. G. Fernandes
Leonel Menezes Freitas de
Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
Ciência Florestal
author_facet Merielen Lopes de Carvalho
Clovis Roberto Haselein
Elio José Santini
Solon Jonas Longhi
Silviana Rosso
Denis L. G. Fernandes
Leonel Menezes Freitas de
author_sort Merielen Lopes de Carvalho
title Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
title_short Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
title_full Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
title_fullStr Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
title_full_unstemmed Agrupamento de árvores matrizes de Eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
title_sort agrupamento de árvores matrizes de eucalyptus grandis em função das variáveis dendrométricas e das caracteristicas tecnológicas da madeira
publisher Universidade Federal de Santa Maria
series Ciência Florestal
issn 0103-9954
1980-5098
publishDate 2004-01-01
description The objetive of this study is to cluster selected trees of Eucalyptus grandis Hill ex-Maiden as a function of phenotypic, dendrometric and wood technology characteristics. In a 27 years old commercial stand, located in the northern coast of Rio Grande do Sul, 63 selected trees were cut down and classified to the phenotypic and dendrometric characteristics. Then, disks were taken at the base, 25, 50, 75 and 100% of the commercial height, and at the DBH, for basic density determination. From the two first logs above the DBH boards parallel to the pith were taken, with 25mm of thickness, for sawn wood qualitative evaluation. The selected trees were grouped into four distinct groups following cluster analysis. In Group I were classified the trees with a lower tendency of presenting boards with end splits while in Groups II and III were classified the trees with a lower tendency of presenting logs with end splits and, in Group IV were classified the trees with a higher tendency of presenting end splits of the boards and the logs. For these groups, by discriminant analysis, there were identified five variables with real power of discrimination (DBH, estimated log split perimeter, ratio height/diameter (rh/d), type of bark and sapwood volumetric percentage) and three discriminant functions. The technique of the multivariate analyze was an efficient method of grouping the selected trees of Eucalyptus grandis. The discriminant analysis enabled the selection of variables with real power of sorting the trees and determinating the discriminant functions that allow the allocation of future trees in the cluster.
url http://www.redalyc.org/articulo.oa?id=53414213
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