There is a growing interest to use acoustic sensors for selection in tree breeding to ensure high wood quality of future plantations. In this study, we assessed acoustic velocity as a selection trait for the improvement of mechanical wood properties in two 15- and 32-year-old white spruce ( Picea glauca [Moench.] Voss) genetic tests. Individual heritability of acoustic velocity was moderate and of the same magnitude as heritability of wood density. Considerable genetic gain could be expected for acoustic velocity and a measure combining velocity and wood density. The relationship between acoustic velocity and cellulose microfibril angle (MFA) was strong on the genetic level and selection based on velocity could effectively improve MFA, which is one of the most important determinants of wood mechanical properties. Although low, the positive relationship between acoustic velocity and tree height presents an interesting opportunity for the improvement of both tree growth and wood quality. On the phenotypic level, MFA was more strongly correlated to acoustic velocity in mature trees than in young trees. The addition of easily obtainable traits such as diameter at breast height (DBH), height-to-diameter ratio as well as wood density to velocity determinations could improve models of MFA at the young and the mature age. We conclude that juvenile acoustic velocity is an appropriate trait to select for wood quality in a tree breeding context.
References
[1]
Zhang, S.Y.; Koubaa, A. Softwoods of Eastern Canada: Their Silvics, Characteristics, Manufacturing and End-Uses; FPInnovations–Forintek Division: Québec, Canada, 2008.
[2]
Corriveau, A.; Beaulieu, J.; Daoust, G. Heritability and genetic correlations of wood characters of Upper Ottawa Valley white spruce populations grown in Quebec. For. Chron. 1991, 67, 698–705.
[3]
Ivkovich, M.; Namkoong, G.; Koshy, M. Genetic variation in wood properties of interior spruce. II. Tracheid characteristics. Can. J. For. Res. 2002, 32, 2128–2139, doi:10.1139/x02-139.
[4]
Yanchuk, A.D.; Kiss, G.K. Genetic variation in growth and wood specific gravity and its utility in the improvement of interior spruce in British Columbia. Silvae Genet. 1993, 42, 141–148.
[5]
Yu, Q.; Yang, D.Q.; Zhang, S.Y.; Beaulieu, J.; Duchesne, I. Genetic variation in decay resistance and its correlation to wood density and growth in white spruce. Can. J. For. Res. 2003, 33, 2177–2183, doi:10.1139/x03-150.
[6]
Beaulieu, J. Genetic variation in tracheid length and relationships with growth and wood traits in eastern white spruce (Picea glauca). Wood Fib. Sci. 2003, 35, 609–616.
[7]
Zhang, S.Y.; Yu, Q.; Beaulieu, J. Genetic variation in veneer quality and its correlation to growth in white spruce. Can. J. For. Res. 2004, 34, 1311–1318, doi:10.1139/x04-015.
[8]
Ivkovich, M.; Namkoong, G.; Koshy, M. Genetic variation in wood properties of interior spruce. I. Growth, latewood percentage, and wood density. Can. J. For. Res. 2002, 32, 2116–2127, doi:10.1139/x02-138.
[9]
Lenz, P.; Cloutier, A.; MacKay, J.; Beaulieu, J. Genetic control of wood properties in Picea glauca—An analysis of trends with cambial age. Can. J. For. Res. 2010, 40, 703–715, doi:10.1139/X10-014.
[10]
Wessels, C.B.; Malan, F.S.; Rypstra, T. A review of measurement methods used on standing trees for the prediction of some mechanical properties of timber. Eur. J. For. Res. 2011, 130, 881–893, doi:10.1007/s10342-011-0484-6.
[11]
Jones, P.D.; Schimleck, L.R.; Peter, G.F.; Daniels, R.F.; Clark, A. Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy. Wood Sci. Technol. 2006, 40, 709–720.
[12]
Schimleck, L.R.; Mora, C.; Daniels, R.F. Estimation of the physical wood properties of green Pinus taeda radial samples by near infrared spectroscopy. Can. J. For. Res. 2003, 33, 2297–2305, doi:10.1139/x03-173.
[13]
Poke, F.S.; Potts, B.M.; Vaillancourt, R.E.; Raymond, C.A. Genetic parameters for lignin, extractives and decay in Eucalyptus globulus. Ann. For. Sci. 2006, 63, 813–821, doi:10.1051/forest:2006080.
[14]
Costa E Silva, J.; Borralho, N.M.G.; Wellendorf, H. Genetic parameter estimates for diameter growth, pilodyn penetration and spiral grain in Picea abies (L.) Karst. Silvae Genet. 2000, 49, 29–36.
[15]
Isik, F.; Li, B. Rapid assessment of wood density of live trees using the Resistograph for selection in tree improvement programs. Can. J. For. Res. 2003, 33, 2426–2435, doi:10.1139/x03-176.
[16]
Bucur, V. Acoustics of Wood; Springer-Verlag: Berlin, Germany, 2006.
[17]
Panshin, A.J.; Zeeuw, C. Textbook of Wood Technology; McGraw-Hill Book Co.: New York, NY, USA, 1980; p. 722.
[18]
Bowyer, J.L.; Shmulsky, R.; Haygreen, J.G. Forest Products and Wood Science: An Introduction; Blackwell Publishing: Ames, IO, USA, 2007.
[19]
Alteyrac, J.; Cloutier, A.; Ung, C.H.; Zhang, S.Y. Mechanical properties in relation to selected wood characteristics of black spruce. Wood Fib. Sci. 2006, 38, 229–237.
[20]
Chauhan, S.S.; Walker, J.C.F. Variations in acoustic velocity and density with age, and their interrelationships in radiata pine. For. Ecol. Manag. 2006, 229, 388–394, doi:10.1016/j.foreco.2006.04.019.
[21]
Grabianowski, M.; Manley, B.; Walker, J.C.F. Acoustic measurements on standing trees, logs and green lumber. Wood Sci. Technol. 2006, 40, 205–216, doi:10.1007/s00226-005-0038-5.
[22]
Achim, A.; Paradis, N.; Carter, P.; Hernández, R.E. Using acoustic sensors to improve the efficiency of the forest value chain in Canada: A case study with laminated veneer lumber. Sensors 2011, 11, 5716–5728, doi:10.3390/s110605716.
[23]
Auty, D.; Achim, A. The relationship between standing tree acoustic assessment and timber quality in Scots pine and the practical implications for assessing timber quality from naturally regenerated stands. Forestry 2008, 81, 475–487, doi:10.1093/forestry/cpn015.
[24]
Kumar, S. Genetic parameter estimates for wood stiffness, strength, internal checking, and resin bleeding for radiata pine. Can. J. For. Res. 2004, 34, 2601–2610, doi:10.1139/x04-128.
[25]
Eckard, J.T.; Isik, F.; Bullock, B.; Li, B.; Gumpertz, M. Selection efficiency for solid wood traits in Pinus taeda using time-of-flight acoustic and micro-drill resistance methods. For. Sci. 2010, 56, 233–241.
[26]
Ivkovic, M.; Gapare, W.J.; Abarquez, A.; Ilic, J.; Powell, M.B.; Wu, H.X. Prediction of wood stiffness, strength, and shrinkage in juvenile wood of radiata pine. Wood Sci. Technol. 2009, 43, 237–257, doi:10.1007/s00226-008-0232-3.
[27]
Apiolaza, L.A. Very early selection for solid wood quality: Screening for early winners. Ann. For. Sci. 2009, 66, 601–611, doi:10.1051/forest/2009047.
[28]
El-Kassaby, Y.A.; Mansfield, S.; Isik, F.; Stoehr, M. In situ wood quality assessment in Douglas-fir. Tree Genet. Genome. 2011, 7, 553–561, doi:10.1007/s11295-010-0355-1.
[29]
Wielinga, B.; Raymond, C.A.; James, R.; Matheson, A.C. Effect of green density values on Pinus radiata stiffness estimation using a stress-wave technique. NZ J. For. Sci. 2009, 39, 71–79.
[30]
Kennedy, R.W. Coniferous wood quality in the future: Concerns and strategies. Wood Sci. Technol. 1995, 29, 321–338, doi:10.1007/BF00202581.
[31]
Gardiner, B.; Leban, J.M.; Auty, D.; Simpson, H. Models for predicting wood density of British-grown Sitka spruce. Forestry 2011, 84, 119–132, doi:10.1093/forestry/cpq050.
[32]
Auty, D.; Gardiner, B.A.; Achim, A.; Moore, J.R.; Cameron, A.D. Models for predicting microfibril angle variation in Scots pine. Ann. For. Sci. 2013, 70, 209–218, doi:10.1007/s13595-012-0248-6.
[33]
Lenz, P.; MacKay, J.; Rainville, A.; Cloutier, A.; Beaulieu, J. The influence of cambial age on breeding for wood properties in Picea glauca. Tree Genet. Genome. 2011, 7, 641–653, doi:10.1007/s11295-011-0364-8.
[34]
Li, X.; Huber, D.A.; Powell, G.L.; White, T.L.; Peter, G.F. Breeding for improved growth and juvenile corewood stiffness in slash pine. Can. J. For. Res. 2007, 37, 1886–1893, doi:10.1139/X07-043.
[35]
Gao, S.; Wang, X.; Wang, L.; Allison, R.B. Effect of temperature on acoustic evaluation of standing trees and logs: Part 2: Field investigation. Wood Fib. Sci. 2013, 45, 15–25.
[36]
Evans, R. Rapid measurement of the transverse dimensions of tracheids in radial wood sections from Pinus radiata. Holzforschung 1994, 48, 168–172, doi:10.1515/hfsg.1994.48.2.168.
[37]
Evans, R. A variance approach to the X-ray diffractometric estimation of microfibril angle in wood. Appita J. 1999, 52, 283–289.
[38]
Megraw, R.; Leaf, G.; Bremer, D. Longitudinal shrinkage and microfibril angle in loblolly pine. In Proceedings of IAWA/IUFRO International Workshop on Microfibril Angle in Wood, Westport, New Zealand, 11–13 November 1997; Butterfield, B, Ed.; University of Canterbury: Christchurch, New Zealand, 1998; pp. 27–61.
[39]
Littell, R.C.; Milliken, G.A.; Stroup, W.W.; Wolfinger, R.D.; Schabenberger, O. SAS for Mixed Models, 2nd ed. ed.; SAS Publishing: Cary, NC, USA, 2006.
[40]
Holland, J.B. Estimating genotypic correlations and their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop Sci. 2006, 46, 642–654, doi:10.2135/cropsci2005.0191.
[41]
Lynch, M.; Walsh, B. Genetics and Analysis of Quantitative Characters; Sinauer: Sunderland, MA, USA, 1998.
Akaike, H. A new look at the statistical model identification. IEEE Trans. Automat. Control 1974, 19, 716–723, doi:10.1109/TAC.1974.1100705.
[44]
Parresol, B.R. Assessing tree and stand biomass: A review with examples and critical comparisons. For. Sci. 1999, 45, 573–593.
[45]
Kumar, S.; Jayawickrama, K.J.S.; Lee, J.; Lausberg, M. Direct and indirect measures of stiffness and strength show high heritability in a wind-pollinated radiata pine progeny test in New Zealand. Silvae Genet. 2002, 51, 256–261.
[46]
Timell, T. Compression Wood in Gymnosperms; Springer Verlag: Berlin, Germany, 1986.
[47]
Zobel, B.J.; Van Buijtenen, J.P. Wood Variation: Its Causes and Control; Springer-Verlag: Heidelberg, NY, USA, 1989.
[48]
Park, Y.S.; Weng, Y.; Mansfield, S.D. Genetic effects on wood quality traits of plantation-grown white spruce (Picea glauca) and their relationships with growth. Tree Genet. Genome 2012, 8, 303–311, doi:10.1007/s11295-011-0441-z.
[49]
Liu, C.; Zhang, S.Y.; Cloutier, A.; Rycabel, T. Modeling lumber bending stiffness and strength in natural black spruce stands using stand and tree characteristics. For. Ecol. Manag. 2007, 242, 648–655, doi:10.1016/j.foreco.2007.01.077.
[50]
Paradis, N.; Auty, D.; Carter, P.; Achim, A. Using a standing-tree acoustic tool to identify forest stands for the production of mechanically-graded lumber. Sensors 2013, 13, 3394–3408, doi:10.3390/s130303394.
[51]
Lindstr？m, H.; Harris, P.; Sorensson, C.T.; Evans, R. Stiffness and wood variation of 3-year old Pinus radiata clones. Wood Sci. Technol. 2004, 38, 579–597, doi:10.1007/s00226-004-0249-1.
[52]
Zhang, H.; Wang, X.; Su, J. Experimental investigation of stress wave propagation in standing trees. Holzforschung 2011, 65, 743–748.
[53]
Apiolaza, L.A.; Chauhan, S.S.; Walker, J.C.F. Genetic control of very early compression and opposite wood in Pinus radiata and its implications for selection. Tree Genet. Genome 2011, 7, 563–571, doi:10.1007/s11295-010-0356-0.
[54]
Perron, M.; DeBlois, J.; Desponts, M. Use of resampling to assess optimal subgroup composition for estimating genetic parameters from progeny trials. Tree Genet. Genome 2012, 9, 129–143, doi:10.1007/s11295-012-0540-5.
