Canadian Forest Service Publications
Acoustic-based prediction of end-product-based fibre determinates within standing jack pine trees: empirical relationships, conceptual inferences and potential utility in value-based forest management. 2019. Newton, P. Forests 10: Art. 605.
Issued by: Great Lakes Forestry Centre
Catalog ID: 39982
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Plain Language Summary
The quality and associated economic value of manufactured wood-based end-products, such as dimensional lumber, engineered wood composites and utility poles, are largely dependent on the characteristics of the internal fibre attributes within merchantable portion the harvested tree stem. The degree of bending stiffness as quantified by the static modulus of elasticity is one of the more important attributes associated with solid wood products as reflected by its use in machine grading systems for classifying dimensional lumber products. This metric has traditionally been determined through destructive sampling procedures and consequently end-product quality of standing trees remains largely unknown until processed. However, as demonstrated in this study for jack pine trees, tree stiffness can be estimated via non-destructive means through its relationship with acoustic velocity and wood density and hence provides an alternative in-forest methodology for evaluating wood quality. The expansion of this primary relationship to include secondary relationships enabled the prediction of a broader suite of commercially-relevant fibre attributes. These attributes are explicitly associated with the quantity and (or) quality of a wide range of end-products and as a consequence, enhances the ability to classify standing trees into a more encompassing set of end-product categories and grade classes. Although this advancement could result in gains in segregation and merchandising efficiency within the upstream portion of the forest products supply chain, the precision requirements and overall segregation objectives of the end-user will be among the principal determinants underlying the operational deployment of the acoustic approach. Directing further research efforts towards increasing predictive precision through the identification and controlling of extraneous sources of variation, generalizing attribute point-estimates into a small number of grade classes, and determining product-based design specifications for each predictable attribute, would be useful. Additionally, the assessment of micro-drill resistance amplitude measures for use in providing the prerequisite wood density estimate used in the developed suite of acoustic - attribute prediction equations for jack pine, revealed that this approach would be more logistically challenging and yield only a slight improvement in predictive precision. Overall, the results of this study not only provided a suite of prediction models that could be of utility in forecasting end-product potential during pre-harvest inventories or informing post-harvest segregation and allocation decision-making for jack pine, but also contributed to solidifying the empirical foundation of the expanded acoustic-based inferential framework for boreal conifers, and assessing an alternative in-forest wood density determination method for potential deployment in acoustic-based sampling. Collectively, these results should be utility in advancing the acoustic approach in value-based forest management decision-making.