Table of Contents
Forests, Volume 9, Issue 12 (December 2018)
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Cover Story (view full-size image) The provision of enhanced operational intelligence arising from in-forest forecasts of end-product [...] Read more. The provision of enhanced operational intelligence arising from in-forest forecasts of end-product potential through non-destructive acoustic-based methods may yield increased efficiencies within the upper portion of the forest products supply chain. Accordingly, this study developed a suite of acoustic-based models for predicting commercially-relevant fiber attributes that largely govern the end-product potential of jack pine logs: dynamic modulus of elasticity, wood density, microfibril angle, tracheid wall thickness, fiber coarseness, and specific surface area. Resultantly, enabling enhanced segregation decision-making and solidifying the empirical foundation of the acoustic-based inferential framework proposed for boreal conifers. The photo exemplifies in-forest acoustic sampling of jack pine logs deploying a resonance-based tool within the Canadian boreal forest. View Paper here.