Acoustic-Based Non-Destructive Estimation of Wood Quality Attributes within Standing Red Pine Trees

Abstract

Abstract:The relationship between acoustic velocity (v d ) and the dynamic modulus of elasticity (m e ), wood density (w d ), microfibril angle, tracheid wall thickness (w t ,), radial and tangential diameters, fibre coarseness (c o ) and specific surface area (s a ), within standing red pine (Pinus resinosa Ait.) trees, was investigated. The data acquisition phase involved 3 basic steps: (1) random selection of 54 sample trees from 2 intensively-managed 80-year-old plantations in central Canada; (2) attainment of cardinal-based v d measurements transecting the breast-height position on each sample tree; and (3) felling, sectioning and obtaining cross-sectional samples from the first 5.3 m sawlog from which Silviscan-based area-weighted mean attribute estimates were determined. The data analysis phase consisted of applying graphical and correlation analyses to specify regression models for each of the 8 attribute-acoustic velocity relationships. Results indicated that viable relationships were obtained for m e , w d , w t , c o and s a based on a set of statistical measures: goodness-of-fit (42%, 14%, 45%, 27% and 43% of the variability explained, respectively), lack-of-fit (unbiasedness) and predictive precision (±12%, ±8%, ±7%, ±8% and ±6% error tolerance intervals, respectively). Non-destructive approaches for estimating the prerequisite w d value when deploying the analytical framework were also empirically evaluated. Collectively, the proposed approach and associated results provide the foundation for the development of a comprehensive and precise end-product segregation strategy for use in red pine management.

Acoustic-Based Prediction of End-Product-Based Fibre Determinates within Standing Jack Pine Trees

“…Previous research on standing red pine (Pinus resinosa Ait.) trees, which has utilized this modelling approach has revealed a satisfactory level of performance in terms of statistical significance, explanatory power, unbiasedness, and predictive ability [14]. Experimental results from other forest regions have also been supportive of this modelling approach.…”

“…Given that wood density is also among the principal attributes influencing end-product potential, its relationship with acoustic velocity has also been included within these frameworks (w d ∝ v 2 d ). Actual empirical results arising from an evaluation of these secondary relationships for 54 standing red pine trees, revealed statistically viable relationships for five of the eight attributes examined (m e , w d , w t , c o , and s a , [14]).…”

“…and other species [14,[26][27][28][29][30][31][32], among attribute correlative relationships, have been used to formulate a more encompassing acoustic-based inferential framework. Specifically, deploying the bivariate relationships between m e and microfibril angle (MFA denoted m a in this study, • ), tracheid wall thickness (w t , µm), radial and tangential tracheid diameters (d r (µm) and d t (µm), respectively), fibre coarseness (c o , µg/m) and specific surface area (s a , m 2 /kg), yielded the following suite of empirical-based secondary relationships applicable to standing softwood trees (sensu [14]): (1) m a ∝ 1/m e ⇒m a ∝ w d v 2 . Given that wood density is also among the principal attributes influencing end-product potential, its relationship with acoustic velocity has also been included within these frameworks (w d ∝ v 2 d ).…”

“…Furthermore, the potential deployment of this acoustic-based inferential framework is dependent on the provision of a wood density estimate. Promising results were attained previously for red pine trees where it was shown that wood density estimates could be derived either directly from acoustic velocity measurements or indirectly through the relationship between wood density and amplitude measures derived from resistance profiles generated from the Resistograph micro-drill tool (IML, Inc., Moultonborough, NH, USA) [14,33]. However, the utility of these approaches for other boreal conifers is largely unknown.…”

Nondestructive Characterization of Dry Heat-Treated Fir (Abies Alba Mill.) Timber in View of Possible Structural Use

“…The important role of material changes during heat treatment mostly concerns the initial structure and density inhomogeneity, which is almost always present in real size solid wood. In the case of the use of such heat-treated solid wood for structural purposes, it is necessary to ensure reliable quality control based on non-invasive techniques [17], widely present in the management of wood quality in the whole forest-wood chain [18,19]. Therefore, the main goal of the study was to use non-destructive mechanical and physical testing methods to investigate possible internal structural changes of fir (Abies alba Mill.)…”