Modeling knot geometry from branch angles in Douglas-fir (Pseudotsuga menziesii)

Abstract

Lumber and veneer recovery from Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) trees depend on the size and distribution of knots. Two approaches have been used to simulate the effect of knots on recovery of these products: (i) prediction of recovery based on mill studies and (ii) simulated milling of virtual trees. A benefit of the latter approach is that different milling configurations may be tested. Knots in virtual logs are usually based on data from X-ray scanning. A novel approach was used in this study to model knot geometry by inferring the development of a branch knot over time from a chronosequence of branch angle and diameter measurements. Branch angle was modeled from a database of 17 953 branch measurements on 412 trees sampled in 16 Douglas-fir plantations. Branch angles from tree tip to crown base were assumed to represent a chronosequence describing the change in branch angle. Knot pith curvature was then derived from this chronosequence of branch angles and modeled as a first-degree inverse polynomial, conditioned on tree size and position within the tree bole. Knot pith curvature was predicted to follow a linear path near the tree tip and became more curved with increasing age and depth into the crown.

Validation of a CT knot detection algorithm on fresh Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) logs

“…According to Todoroki (2003), an increase in value may vary between 13% using imprecise data, and up to 26% when applying precise knowledge of the internal knot structure. The use of such information to optimize log grading, as well as the final product value, has been discussed by Berglund et al (2013), Fredriksson (2014), and Oja et al (2010). In addition, knot geometry data can also be employed to build knot models, which aid in stand management decision making, thus enabling the implementation of wood quality-oriented strategies earlier in the wood supply chain.…”

Un método de muestreo para predecir la edad de ramas de primer orden

“…De acuerdo con Rautiainen y Stenberg (2005) [ 33 ] bastante razonable, al menos en ramas juveniles. Para ramas adultas es probable que el ángulo de inserción aumente como lo señalan Colin y Houllier (1992), Lemieux, Samson y Usenius (1997), Vestøl y Høibø (2001), Trincado y Burkhart (2008) y Osborne y Maguire (2015). El tamaño y peso de las ramas modifica el ángulo de inserción como se deduce de los estudios de Shigo (1986) y Lemieux et al (1997).…”

“…La evaluación de prescripciones silvícolas para especies de alto valor comercial destinadas a uso estructural requiere conocer atributos de ramas como su posición, tamaño, longevidad, mantención y persistencia a lo largo del fuste. Las ramas incluidas en el fuste se convierten en nudos que desde una perspectiva de calidad de madera se consideran como defectos internos (Trincado y Burkhart, 2008;Osborne y Maguire, 2015). Decisiones silvícolas tales como: densidad inicial de plantación y espaciamiento (Amateis, Radtke y Hansen, 2004), raleo (Baldwin et al, 2000), poda (Clark, Saucier, Baldwin y Bower, 1994) y fertilización (Yu, Chambers, Tang y Barnett, 2003) tienen un efecto en el tamaño de las ramas y consecuentemente en la dimensión de los nudos.…”

Assessing wood properties in standing timber with laser scanning

“…The tight interdependencies between primary and secondary growth are due to the wood formation responding to intrinsic (increasing size) and extrinsic (climate and competition) factors as described in the Introduction. With detailed inputs from TLS point clouds accompanied by wood property references, any of the above-mentioned models could be utilized in translating allometric growth responses into vertical and radial gradients of wood properties such as knottiness, wood density, or fiber properties (Duchateau et al 2013;Eberhardt et al 2019;Ikonen et al 2003;Mäkelä et al 2010;Mäkinen et al 2020;Moberg 2006;Osborne and Maguire 2016) (Figures 1 and 4).…”

“…Establishing databases that combine detailed morphological tree traits from standing timber, bucking data from harvesters, and wood quality data from sawmills would enable reconstructions of virtual sawlogs that are used to optimize the secondary log breakdown, or sawing. Using stem taper, branching, and knot shape models, comprehensive reconstructions of interior knot structures were previously demonstrated (Duchateau et al 2013;Osborne and Maguire 2016). TLS provides an excellent instrument for obtaining the calibration data from standing timber (Figure 4).…”