Please use this identifier to cite or link to this item:
https://repositorio.inpa.gov.br/handle/1/15384
Title: | Yield modeling in sawing logs of Manilkara spp. (Sapotaceae) in sawmill in the state of Roraima, Brazil |
Other Titles: | Modelagem do rendimento no desdobro de toras de Manilkara spp. (Sapotaceae) em serraria do estado de Roraima, Brasil |
Authors: | Danielli, Filipe Eduardo Gimenez, Bruno Oliva Oliveira, Criscian Kellen Amaro de Santos, Joaquim dos Higuchi, Niro |
Keywords: | Lumber Saw Mills Wood Products Coefficient Of Determination Diameter Class Homogeneous Distribution Roraima , Brazil Sawnwoods Standard Errors Statistical Differences Yield Modeling Sawing Byproducts Logs Saw Mills |
Issue Date: | 2016 |
metadata.dc.publisher.journal: | Scientia Forestalis/Forest Sciences |
metadata.dc.relation.ispartof: | Volume 44, Número 111, Pags. 641-651 |
Abstract: | The aim of this study was to estimate the yield of sawing Manilkara spp. logs, to quantify the wood by products generated, to evaluate differences in the yield between the diameter classes and to adjust models to estimate the yield in lumber and to estimate the volume of the hollow part of the logs. Seventy-one logs were sampled and grouped into diameter classes. Log volumes were determined by the Smalian method and the volume of lumber was calculated to determine the yield. Twelve models were tested to estimate the sawn lumber and twelve models to estimate the volume of the hollow logs. The choice of the best models was made based on the highest adjusted coefficient of determination (Rajust2), lowest standard error of estimate (Syx%) and homogeneous distribution of the residues. The average yield was 30.1% and showed no statistical differences in yield between the diameter classes and between hollow logs and non-hollow logs. Class 5 (70<79,9 cm) was the one that presented the best yield. To estimate the yield, the best equation was the number seven. To estimate the volume of the hollow part of the logs, the best equations were number two, three and ten. |
metadata.dc.identifier.doi: | 10.18671/scifor.v44n111.10 |
Appears in Collections: | Artigos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
artigo-inpa.pdf | 1,24 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License