Paradis, Normand and Auty, David and Carter, Peter and Achim, Alexis (2013) Using a standing-tree acoustic tool to identify forest stands for the production of mechanically-graded lumber. Sensors (Basel, Switzerland), 13 (3). pp. 3394-408. ISSN 1424-8220
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Paradis_N_Auty_D_et_al_2013_Using_Standing_Tree_Acoustic_Tool.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
This study investigates how the use of a Hitman ST300 acoustic sensor can help identify the best forest stands to be used as supply sources for the production of Machine Stress-Rated (MSR) lumber. Using two piezoelectric sensors, the ST300 measures the velocity of a mechanical wave induced in a standing tree. Measurements were made on 333 black spruce (Picea mariana (Mill.) BSP) trees from the North Shore region, Quebec (Canada) selected across a range of locations and along a chronosequence of elapsed time since the last fire (TSF). Logs were cut from a subsample of 39 trees, and sawn into 77 pieces of 38 mm × 89 mm cross-section before undergoing mechanical testing according to ASTM standard D-4761. A linear regression model was developed to predict the static modulus of elasticity of lumber using tree acoustic velocity and stem diameter at 1.3 m above ground level (R2 = 0.41). Results suggest that, at a regional level, 92% of the black spruce trees meet the requirements of MSR grade 1650Fb-1.5E, whilst 64% and 34% meet the 2100Fb-1.8E and 2400Fb-2.0E, respectively. Mature stands with a TSF < 150 years had 11 and 18% more boards in the latter two categories, respectively, and therefore represented the best supply source for MSR lumber.
Item Type: | Article |
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ID number or DOI: | 10.3390/s130303394 |
Keywords: | acoustic sensors; forestry wood chain; wood stiffness; machine stress-rated lumber |
Subjects: | S Agriculture > SD Forestry |
NAU Depositing Author Academic Status: | Faculty/Staff |
Department/Unit: | College of Engineering, Forestry, and Natural Science > School of Forestry |
Date Deposited: | 02 Oct 2015 17:37 |
URI: | http://openknowledge.nau.edu/id/eprint/1089 |
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