Using a standing-tree acoustic tool to identify forest stands for the production of mechanically-graded lumber

Normand Paradis, David Auty, Peter Carter, Alexis Achim

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)3394-3408
Number of pages15
JournalSensors
Volume13
Issue number3
DOIs
StatePublished - Mar 2013
Externally publishedYes

Keywords

  • Acoustic sensors
  • Forestry wood chain
  • Machine stress-rated lumber
  • Wood stiffness

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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