Modelling the influence of radiata pine log variables on structural lumber production

Authors

  • Elvis Gavilán
  • Rosa M. Alzamora
  • Luis A. Apiolaza
  • Katia Sáez
  • Juan Pedro Elissetche
  • Antonio Pinto

DOI:

https://doi.org/10.4067/s0718-221x2023000100402

Keywords:

Acoustic technology, log variables, Pinus radiata, regression models, structural lumber

Abstract

We run logit models to explain the variability of Pinus radiata structural lumber in 71 second and third unpruned logs. The response variable was the proportion of lumber with a static modulus of elasticity greater or equal than 8 GPa, pMSG8+, and the explanatory variables were log volume, branch index, largest branch, log internode index, wood basic density, and acoustic velocity. The average pMSG8+ volume was 44,30 % and 36,18 % in the second and third log respectively. Ten models were selected based on meeting statistical assumptions, their goodness of fit, and the statistical significance of their parameters. The best models (R2 - adj. > 0,75) included acoustic velocity (AV) as explanatory variable, which explained 56,25 % of the variability of pMSG8+. Models without AV presented goodness of fit ranging from 0,60 to 0,75 (R2 - adj.), and variables with the highest weight to explain the variability of pMSG8+ were volume, followed by wood basic density, branch index, and largest branch. It is possible to model pMSG8+ from log variables even when acoustic velocity is not available; however, this requires wood basic density models calibrated for the Pinus radiata growing zone.

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References

Alzamora, R.M.; Apiolaza, L.A.; Evison, D.C. 2013. Using a production approach to estimate economic weights for structural attributes of Pinus radiata wood. Scand J For Res 28(3): 282-290. https://doi.org/10.1080/02827581.2012.734328

Apiolaza, L.A. 2009. Very early selection for wood quality: screening for early winners. Ann For Sci 66(6): 1-10. https://www.doi.org/10.1051/forest/2009047

Arriaga, F.; Monton J.; Segues, E.; Íñiguez-Gonzalez, G. 2013. Determination of the mechanical properties of P. radiata timber by means of longitudinal and transverse vibration methods. Holzforschung 68(3): 299-305 https://doi.org/10.1515/hf-2013-0087

Beall, F.C. 2001. Wood Products: Nondestructive Evaluation. Encyclopedia of Materials: Science and Technology (Second Edition). Elsevier, Oxford, pp 9702-9707. https://doi.org/10.1016/B0-08-043152-6/01761-7

Beauregard, R.L.; Gazo, R.; Ball, R.D. 2002. Grade recovery, value, and return-to-log for the production of NZ visual grades (cutting and framing) and Australian machine stress grades. Wood Fiber Sci 34(3): 485-505. https://wfs.swst.org/index.php/wfs/article/viewFile/1586/1586

Bruce, D. 1982. Butt Log Volume Estimators. For Sci 28(3): 489-503. https://doi.org/10.1093/forestscience/28.3.489

Caliro-Saw. 2014. Simulador de aserrío Caliro-Saw, Software desarrollado por Allware y la Universidad Austral de Chile. Chile. (In Spanish). http://tienda.caliro.cl/index.php?route=information/information&information_id=5

Chauhan, S.S.; Walker J.C.F. 2006. Variations in acoustic velocity and density with age, and their interrelationships in radiata pine. For Ecol Manag 229(1-3): 388-394. https://doi.org/10.1016/j.foreco.2006.04.019

Dickson, R.L.; Raymond C.A.; Joe, W.; Wilkinson C.A. 2003. Segregation of Eucalyptus dunnii logs using acoustics. For Ecol Manag 179(1-3): 243-251. https://doi.org/10.1016/S0378-1127(02)00519-4 Fernández, M. P.; Basauri, J.; Madariaga, C.; Menéndez-Miguélez, M.; Olea, R.; Zubizarreta-Gerendiain,

A. 2017. Effects of thinning and pruning on stem and crown characteristics of radiata pine (Pinus radiata D. Don). iForest 10(2): 383-390. https://doi.org/10.3832/ifor2037-009

Gapare, W.J.; Ivković, M.; Baltunis B.S.; Matheson C.A., Wu H.X. 2010. Genetic stability of wood Density and diameter in Pinus radiata D. Don plantation estate across Australia. Tree Genet Genomes 6(1): 113-125. https://doi.org/10.1007/s11295-009-0233-x

García-Iruela, A.; García Fernández, F.; García Esteban, L.; de Palacios, P.; Simón, C.; Arriaga, F. 2016. Comparison of modelling using regression techniques and an artificial neural network for obtaining the static modulus of elasticity of Pinus radiata D. Don. timber by ultrasound. Compos B

Eng 96: 112-118. https://doi.org/10.1016/j.compositesb.2016.04.036

Gelman, A.; Hill, J. 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press. New York. United States.

http://www.stat.columbia.edu/~gelman/arm/

Grace, J.C.; Carson, M.J. 1993. Prediction of internode length in Pinus radiata stands. N Z J For Sci 23(1): 10-26. http://www.scionresearch.com/__data/assets/pdf_file/0019/17731/NZJFS2311993GRACE10_26.pdf

Grant, D.J.; Anton A.; Lind P. 1984. Bending strength, stiffness, and stress-grade of structural Pinus radiata: effect of knots and timber density. N Z J For Sci 14(3): 331-348. https://www.scionresearch.com/__data/assets/pdf_file/0006/30894/NZJFS1431984GRANT331_348.pdf

Gujarati D.N.; Porter D.C. 2010. Econometría. Mc. Graw Hill. México D. F. México (In Spanish). https://www.marcialpons.es/libros/econometria/9786071502940/

Ivković, M.; Gapare W.J.; Abarquez A.; Ilic J.; Powell M.B.; Wu H.X. 2009. Prediction of wood stiffness, strength, and shrinkage in juvenile wood of radiata pine. Wood Sci Technol 43(3): 237-257. https://doi.org/10.1007/s00226-008-0232-3

Ivković, M.; Wu, H.X.; McRae T.A.; Powell M.B. 2006. Developing breeding objectives for P. radiata structural wood production. I. Bioeconomic model and economic weights. Can J For Res 36(11): 2920-2931. https://doi.org/10.1139/x06-161

Jones, T.G.; Emms, G.W. 2010. Influence of acoustic velocity, density, and knots on the stiffness grade outturn of radiata pine logs. Wood Fiber Sci 42(1): 1-9. https://wfs.swst.org/index.php/wfs/article/view/736

Kimberley, M.O.; Cown, D.J.; McKinley, R.B.; Moore J.R.; Dowling L.J. 2015. Modelling variation in wood density within and among trees in stands of New Zealand-grown P. radiata. N Z For Sci 45(22): 1-13. https://doi.org/10.1186/s40490-015-0053-8

Lasserre, J.P.; Mason, E.G.; Watt, M.S. 2005. Effects of genotype and spacing on Pinus radiata (D. Don) corewood stiffness in an 11 year-old experiments. For Ecol Manag 205(1-3): 375-383. https://doi.org/10.1016/j.foreco.2004.10.037

Legg, M.; Bradley, S. 2016. Measurement of stiffness of standing trees and felled logs using acoustics: A review. J Acoust Soc Am 139(2): 588-604. https://doi.org/10.1121/1.4940210

Matheson, A.C.; Dickson L.R.; Spencer, D.J: Joe, B.; Ilic, J. 2002. Acoustic segregation of Pinus radiata logs according to stiffness. Ann For Sci 59(5-6): 471-477. https://doi.org/10.1051/forest:2002031

Moore, J.R.; Cown, D.J. 2017. Corewood (Juvenile Wood) and Its Impact on Wood Utilization. Curr For Rep 3: 107-118. https://doi.org/10.1007/s40725-017-0055-2

R Core Team 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Ross, R.J. 2015. Nondestructive Evaluation of Wood. Department of Agriculture, Forest Service, Forest Products Laboratory. General Technical Report FPL-GTR-238. Madison, WI. United States https://www.fs.usda.gov/treesearch/pubs/48688

Schmoldt, D.L.; Occeña, L.G.; Abbott, L.A.; Gupta, N.K. 1993. Nondestructive evaluation of hardwood logs: CT scanning, machine vision and data utilization. Nondestr Test Eval 15: 279-309. https://doi.org/10.1080/10589759908952876

Soto, L.; Valenzuela, L.; Lasserre, J.P. 2012. Efecto de la densidad de plantación inicial en el módulo de elasticidad dinámico de árboles en pie y trozas de una plantación de pino radiata de 28 años, en la zona de arenales, Chile. Maderas-Cienc Tecnol 14(2): 209-224. https://www.doi.org/10.4067/S0718-221X2012000200008

Tsehaye, A.; Buchanan A.H.; Walker, J.C.F. 2000. Selecting trees for structural timber. Holz Roh Werkst 58(3): 162-167. https://doi.org/10.1007/s001070050407

Tsuchikawa, S. 2007. A review of recent near infrared research for wood and paper. Appl Spectros Rev 42(1): 43-71. https://doi.org/10.1080/05704920601036707 UNE 1995. UNE-EN 519: Madera estructural. Clasificación. Requisitos para la madera clasificada mecánicamente y para las máquinas de clasificación. AENOR. España.

Waghorn, M.J.; Watt M.S.; Mason, E.G. 2007. Influence of tree morphology, genetics, and initial stand density on outerwood modulus of elasticity of 17-year-old Pinus radiata. For Ecol Manag 244(1-3): 86-92. https://doi.org/10.1016/j.foreco.2007.03.057

Schimleck, L; Dahlen, J.; Apiolaza, L.A.; Downes, G.; Emms, G.; Evans, R.; Moore, J.; Pâques, L.; Van den Bulcke, J.; Wang, X. 2019. Non-Destructive Evaluation Techniques and What They Tell Us About Wood Property Variation. Forests 10(9): 1-50. https://doi.org/10.3390/f10090728

Xu, P., Walker, J.C.F. 2004. Stiffness gradients in radiata pine trees. Wood Sci Technol 38(1):1-9. https://doi.org/10.1007/s00226-003-0188-2

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Published

2022-09-28

How to Cite

Gavilán, E. ., Alzamora, R. M. ., Apiolaza, L. A. ., Sáez, K. ., Elissetche, J. P. ., & Pinto, A. . (2022). Modelling the influence of radiata pine log variables on structural lumber production. Maderas. Ciencia Y Tecnología, 25, 1–10. https://doi.org/10.4067/s0718-221x2023000100402

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