Property Modeling of Changbai Larch ( Larix Olgensis Henry) Veneers in Relation to Stand and Tree Variables

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

You are here

Property Modeling of Changbai Larch ( Larix Olgensis Henry) Veneers in Relation to Stand and Tree Variables

TitleProperty Modeling of Changbai Larch ( Larix Olgensis Henry) Veneers in Relation to Stand and Tree Variables
Publication TypeJournal Article
Year of Publication2013
AuthorsWANG, BRADJIANHE, ZHANG, HONGBIN, WU, LANG, HUANG, SUYONG, LU, JIANXIONG, Zidek, J
JournalWood and Fiber Science
Volume45
Pagination314–329
Date Publishedjul
ISSN0735-6161
KeywordsChangbai larch, DBH, density, MOE, stand, statistical model, tree, veneer
AbstractThe key objective of this work was to investigate properties of Changbai larch (Larix olgensis Henry) veneers in relation to stand and tree variables using both linear regression (LR) and linear mixed effects (LME) models. A veneer data set was formed with 36 sample trees from four stands in China. Each tree was cross-cut into six segments along the vertical stem. The results showed that tree diameter at breast height (DBH), tree height, and branch height exhibited certain degrees of association with either veneer modulus of elasticity (MOE) or ultrasonic propagation time (UPT) but not with veneer density. Both veneer MOE and UPT exhibited a polynomial pattern along the tree stem. Stem position was found to be the only significant variable affecting veneer density. The highest veneer MOE appeared to be situated between the second and third stems from the butt. LME and LR models were clearly similar with regard to parameter estimates. However, the overall standard error and p value from the LME model were smaller than those from the LR model, indicating that the LME model was more effective for stem-specific analysis. After adjusting confounders including the stem position, tree height exhibited no association with veneer MOE. This result did not occur with standard LR analysis.
URLhttp://wfs.swst.org/index.php/wfs/article/view/2023