Jump to ContentJump to Main Navigation
Show Summary Details
More options …
Wood Research and Technology

Holzforschung

Cellulose – Hemicelluloses – Lignin – Wood Extractives

Editor-in-Chief: Salmén, Lennart

Editorial Board: Daniel, Geoffrey / Militz, Holger / Rosenau, Thomas / Sixta, Herbert / Vuorinen, Tapani / Argyropoulos, Dimitris S. / Balakshin, Yu / Barnett, J. R. / Burgert, Ingo / Rio, Jose C. / Evans, Robert / Evtuguin, Dmitry V. / Frazier, Charles E. / Fukushima, Kazuhiko / Gindl-Altmutter, Wolfgang / Glasser, W. G. / Holmbom, Bjarne / Isogai, Akira / Kadla, John F. / Koch, Gerald / Lachenal, Dominique / Laine, Christiane / Mansfield, Shawn D. / Morrell, J.J. / Niemz, Peter / Potthast, Antje / Ragauskas, Arthur J. / Ralph, John / Rice, Robert W. / Salin, Jarl-Gunnar / Schmitt, Uwe / Schultz, Tor P. / Sipilä, Jussi / Takano, Toshiyuki / Tamminen, Tarja / Theliander, Hans / Welling, Johannes / Willför, Stefan / Yoshihara, Hiroshi


IMPACT FACTOR 2017: 2.079

CiteScore 2017: 1.94

SCImago Journal Rank (SJR) 2017: 0.709
Source Normalized Impact per Paper (SNIP) 2017: 0.979

Online
ISSN
1437-434X
See all formats and pricing
More options …
Volume 64, Issue 4

Issues

Predicting the longitudinal modulus of elasticity of Sitka spruce from cellulose orientation and abundance

J. Paul McLean / Robert Evans / John R. Moore
Published Online: 2010-05-04 | DOI: https://doi.org/10.1515/hf.2010.084

Abstract

Sitka spruce (Picea sitchensis) is the most widely planted commercial tree species in the United Kingdom and Ireland. Because of the increasing use of this species for construction, the ability to predict wood stiffness is becoming more important. In this paper, a number of models are developed using data on cellulose abundance and orientation obtained from the SilviScan-3 system to predict the longitudinal modulus of elasticity (MOE) of small defect-free specimens. Longitudinal MOE was obtained from both bending tests and a sonic resonance technique. Overall, stronger relationships were found between the various measures of cellulose abundance and orientation and the dynamic MOE obtained from the sonic resonance measurements, rather than with the static MOE obtained from bending tests. There was only a moderate relationship between wood bulk density and dynamic MOE (R2=0.423), but this relationship was improved when density was divided by microfibril angle (R2=0.760). The best model for predicting both static and dynamic MOE involved the product of bulk density and the coefficient of variation in the azimuthal intensity profile (R2=0.725 and 0.862, respectively). The model parameters obtained for Sitka spruce differed from those obtained in earlier studies on Pinus radiata and Eucalyptus delegatensis, indicating that the model might require recalibration before it can be applied to different species.

Keywords: microfibril angle (MFA); SilviScan; Sitka spruce; wood stiffness; X-ray diffraction

About the article

Corresponding author. Present address: Equipe Mecanique de l'arbre et du bois, Laboratoire de Mécanique et Génie Civil, Université Montpellier II, Campus St Priest, 34090 Montpellier, France Phone: +33-4-6714-9344 Fax: +33-4-6714-4792


Received: 2009-09-30

Accepted: 2010-01-29

Published Online: 2010-05-04

Published Online: 2010-05-04

Published in Print: 2010-06-01


Citation Information: Holzforschung, Volume 64, Issue 4, Pages 495–500, ISSN (Online) 1437-434X, ISSN (Print) 0018-3830, DOI: https://doi.org/10.1515/hf.2010.084.

Export Citation

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Sven-Olof Lundqvist, Stefan Seifert, Thomas Grahn, Lars Olsson, Maria Rosario García-Gil, Bo Karlsson, and Thomas Seifert
European Journal of Forest Research, 2018
[2]
David Auty, John Moore, Alexis Achim, Andrew Lyon, Shaun Mochan, and Barry Gardiner
Forestry: An International Journal of Forest Research, 2018, Volume 91, Number 3, Page 307
[3]
Jun Tanabe, Futoshi Ishiguri, Akira Tamura, Jyunichi Ohshima, Kazuya Iizuka, and Shinso Yokota
Scandinavian Journal of Forest Research, 2017, Volume 32, Number 1, Page 39
[4]
David Auty, Barry A. Gardiner, Alexis Achim, John R. Moore, and Andrew D. Cameron
Annals of Forest Science, 2013, Volume 70, Number 2, Page 209
[5]
John R Moore, Dave J Cown, and Russell B McKinley
New Zealand Journal of Forestry Science, 2014, Volume 44, Number 1
[6]
Yoshio Kijidani, Yoshitomo Kawasaki, Daisuke Matsuda, Fumiaki Nakazono, Masato Hayakawa, Hisashi Mutaguchi, and Hiroki Sakagami
Journal of Wood Science, 2014, Volume 60, Number 6, Page 381
[8]
John R. Moore, Andrew J. Lyon, and Stefan Lehneke
Annals of Forest Science, 2012, Volume 69, Number 3, Page 353
[9]
Yoshio Kijidani, Yoshimitsu Fujii, Keita Kimura, Yoshitake Fujisawa, Yuichiro Hiraoka, and Ryushi Kitahara
Journal of Wood Science, 2012, Volume 58, Number 3, Page 195
[10]
Tuomas Hänninen, Pekka Tukiainen, Kirsi Svedström, Ritva Serimaa, Pekka Saranpää, Eero Kontturi, Mark Hughes, and Tapani Vuorinen
Holzforschung, 2012, Volume 66, Number 3
[11]
Wayne Hall, Andrew Seagar, and Stuart Palmer
Holzforschung, 2012, Volume 66, Number 2

Comments (0)

Please log in or register to comment.
Log in