Skip to main content
Log in

High negative genetic correlations between growth traits and wood properties suggest incorporating multiple traits selection including economic weights for the future Scots pine breeding programs

  • Original Paper
  • Published:
Annals of Forest Science Aims and scope Submit manuscript

Abstract

Context

The development of multiple trait selection indices for solid (structure) wood production in the Scots pine (Pinus sylvestris L.) breeding program requires genetic variances and covariances estimated among wood quality traits including stiffness.

Aims

Genetic control and relationships among Scots pine growth, fiber, and wood quality traits were assessed by estimating heritability, phenotypic and genetic correlation using a Scots pine full-sib family trial.

Method

Wood quality traits including clearwood and dynamic acoustic stiffness were measured using SilviScan and Hitman in a 40-year-old progeny trial and by sampling increment cores of 778 trees of 120 families. Genetic parameters were estimated using the mixed model by the ASReml software.

Results

Heritability ranged from 0.147 to 0.306 for growth, earlywood, transition wood and latewood proportion traits and from 0.260 to 0.524 for fiber dimension, wood density, MFA and stiffness traits. The highly unfavorable genetic correlation between diameter and whole core density (−0.479) and clearwood stiffness (−0.506) and dynamic acoustic stiffness (−0.382) was observed in this study.

Conclusion

The unfavorable genetic correlations between growth traits and stiffness indicate that multiple traits selection using optimal economic weights and optimal breeding strategies are recommended for the advanced Scots pine breeding program.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Auty D, Achim A (2008) 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 81:475–487. doi:10.1093/forestry/cpn015

    Article  Google Scholar 

  • Baltunis BS, Wu HX, Powell MB (2007) Inheritance of density, microfibril angle, and modulus of elasticity in juvenile wood of Pinus radiata at two locations in Australia. Can J For Res 37:2164–2174

    Google Scholar 

  • Baltunis BS, Gapare WG, Wu HX (2010) Genetic parameters and genotype by environment interaction in radiata pine for growth and wood quality traits in Australia. Silvae Genet 59:113–124

    Google Scholar 

  • Berlin M (2009) Development of economic forest tree breeding objectives. PhD Thesis. Acta Universitatis Agriculturae Sueciae - Agraria, 2009:90. Uppsala Sweden, p 88

  • Brandel G (1990) Volume functions for individual trees. Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula pendula & Betula pubescens). Swedish University of Agricultural Sciences. Department of Forest Yield Research. Report 26: 183 p. ISSN 0348–7636. (In Swedish with English summary)

  • Bucur V (2006) Acoustics of Wood, 2nd edn. SpringerVerlag, Berlin

    Google Scholar 

  • Cave ID (1976) Modelling the structure of the softwood cell wall for computation of mechanical properties. Wood Sci Technol 10:19–28. doi:10.1007/BF00376381

    Article  Google Scholar 

  • Evans R (2006) Wood stiffness by x-ray diffractometry, in “Characterization of the Cellulosic, Cell Wall”. In: Stokke D, Groom LH (eds) Characteristics of the Cellulosic Cell Wall, Southern Research Station, Iowa State University, Colorado, US. Blackwell Publishing, pp 138–146

  • Eriksson G (2008) Pinus sylvestris: Recent Genetic Research. Department of Plant Biology and Forest Genetics, Genetic Center, SLU, Box 7080, SE 750 07 Uppsala, Sweden, pp 111

  • Ericsson T (1997) Enhanced heritabilities and best linear unbiased predictors through appropriate blocking of progeny trials. Can J For Res 27:2097–2101. doi:10.1139/x97-153

    Article  Google Scholar 

  • Ericsson T (1999) Reply—enhanced heritabilities and best linear unbiased predictors through appropriate blocking of progeny trials. Can J For Res 29:1635–1636. doi:10.1139/x99-156

    Article  Google Scholar 

  • Ericsson T, Fries A (2004) Genetic analysis of fiber size in a full-sib Pinus sylvestris L. progeny test. Scand. J. Forest Res 19:7–14. doi:10.1080/02827580310019031

    Google Scholar 

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Longman Group Ltd, Harlow

    Google Scholar 

  • Fries A, Ericsson T (2006) Estimating genetic parameters for wood density of Scots pine (Pinus sylvestris L.). Silvae Genet 55:84–92

    Google Scholar 

  • Fries A, Ericsson T (2009) Genetic parameters for earlywood and latewood densities and development by increasing age in Scots pine. Ann For Sci 66:404. doi:10.1051/forest/2009019

    Article  Google Scholar 

  • Fries A (2012) Genetic parameters, genetic gain and correlated responses in growth, fiber dimensions and wood density in a Scots pine breeding population. Ann For Sci 69:783–794. doi:10.1007/s13595-012-0202-7

    Article  Google Scholar 

  • Gapare WJ, Baltunis BS, Ivković M, Wu HX (2009) Genetic correlations among juvenile wood quality and growth traits and implications for selection strategy in Pinus radiata D. Don Ann For Sci 66:606–611. doi:10.1051/forest/2009044

    Article  Google Scholar 

  • Gapare WJ, Ivković M, Baltunis BS, Matheson CA, Wu HX (2010) Genetic stability of wood density in Pinus radiata D. Don plantation estate across Australia. Tree Genet Genomes 6:113–125

    Google Scholar 

  • Gilmour AR, Gogel BJ, Cullis BR Thomson R (2009) ASReml User Guide release 3.0. VSN-International Ltd. Hemel Hempstead, UK

    Google Scholar 

  • Gräns D, Hannrup B, Isik F, Lundqvist SO, McKeand S (2009) Genetic variation and relationships to growth traits for microfibril angle, wood density and modulus of elasticity in a Picea abies clonal trial in southern Sweden. Scand J Forest Res 24:494–503. doi:10.1080/02827580903280061

    Article  Google Scholar 

  • Gryc V, Vavrčík H, Horn K (2011) Density of juvenile and mature wood of selected coniferous species. J For Sci 57:123–130

    Google Scholar 

  • Haapanen M, Velling P, Annala MJ (1997) Progeny trial estimates of genetic parameters for growth and quality traits in Scots pine. Silva Fenn 31:3–12

    Article  Google Scholar 

  • Hannrup B, Ekberg I (1998) Age–age correlations for tracheid length and wood density in Pinus sylvestris. Can J For Res 28:1373–1379. doi:10.1139/cjfr-28-9-1373

    Article  Google Scholar 

  • Hannrup B, Cahalan C, Chantre G, Grabner M, Karlsson B, Le Bayon I, Jones GL, Muller U, Pereira H, Rodrigues JC, Rosner S, Rozenberg P, Wilhelmsson L, Wimmer R (2004) Genetic parameters of growth and wood quality traits in Picea abies. Scand J For Res 19:14–29. doi:10.1080/02827580310019536

    Article  Google Scholar 

  • Hannrup B, Ekberg I, Persson A (2000) Genetic correlations among wood, growth capacity and stem traits in Pinus sylvestris. Scand J Forest Res 15:161–170. doi:10.1080/028275800750014966

    Article  Google Scholar 

  • Hannrup B, Danell Ö, Ekberg I, Moëll M (2001) Relationships between wood density and tracheid dimensions in Pinus sylvestris L. Wood Fiber Sci 33:173–181

    Google Scholar 

  • Hallingbäck H (2010) Genetic improvement of shape stability in Norway spruce and Scots pine sawn timber. Acta Universitatis Agriculture Sueciae-Agraria 2010:22. Uppsala, Sweden, pp 102

  • Hylen G (1999) Age trends in genetic parameters of wood density in young Norway spruce. Can J For Res 29:135–143. doi:10.1139/cjfr-29-1-135

    Article  Google Scholar 

  • Isik F, Mora CR, Schimleck LR (2011) Genetic variation in Pinus taeda wood properties predicted using non-destructive techniques. Ann For Sci 68:283–293. doi:10.1007/s13595-011-0035-9

    Article  Google Scholar 

  • Ivković M, Wu HX, McRae TA, Powell MB (2006) Developing breeding objectives for radiata pine structural wood production I. Bioeconomic model and economic weights. Can J For Res 36:2920–2931. doi:10.1139/x06-161

    Article  Google Scholar 

  • Kroon J, Andersson B, Mullin TJ (2008) Genetic variation in the diameter-height relationship in Scots pine (Pinus sylvestris). Can J For Res 38:1493–1503. doi:10.1139/X07-233

    Article  CAS  Google Scholar 

  • Kroon J, Ericsson T, Jansson G, Andersson B (2011) Patterns of genetic parameters for height in field genetic tests of Picea abies and Pinus sylvestris in Sweden. Tree Genet Genomes 7:1099–1111. doi:10.1007/s11295-011-0398-y

    Article  Google Scholar 

  • Lachenbruch B, Johnson GR, Downes GM, Evans R (2010) Relationships of density, microfibril angle, and sound velocity with stiffness and strength in mature wood of Douglas-fir. Can J For Res 40:55–64. doi:10.1139/X09-174

    Article  Google Scholar 

  • Lenz P, Coloutier A, MacKay J, Beaulieu J (2010) Genetic control of wood properties in Picea glauca — an analysis of trends with cambial age. Can J For Res 40:703–715. doi:10.1139/X10-014

    Article  Google Scholar 

  • Lenz P, MacKay J, Rainville A, Cloutier A, Beaulieu J (2011) The influence of cambial age on breeding for wood properties in Picea glauca. Tree Genet Genomes 7:641–653. doi:10.1007/s11295-011-0364-8

    Article  Google Scholar 

  • Lenz P, Auty D, Achim A, Beaulieu J, MacKay J (2013) Genetic improvement of white spruce mechanical wood traits – early screening by means of acoustic velocity. Forests 4:575–594. doi:10.3390/f4030575

    Article  Google Scholar 

  • Louzada JLPC, Fonseca FMA (2002) The heritability of wood density components in Pinus pinaster Ait. and the implications for tree breeding. Ann For Sci 59:867–873. doi:10.1051/forest:2002085

    Article  Google Scholar 

  • Park YS, Weng YH, Mansfield SD (2012) Genetic effects on wood quality traits of plantation-grown white spruce (Picea glauca) and their relationships with growth. Tree Genet Genomes 8:303–311. doi:10.1007/s11295-011-0441-z

    Article  Google Scholar 

  • Rosvall O (ed) (2011) Review of the Swedish tree breeding programme. Arbetsrapport, Skogforsk, Uppsala Science Park, Uppsala. pp 114

  • Sokal RR, Rohlf FJ (1995) Biometry: the principles and practice of statistics in biological research, 3rd edn. W.H. Freeman, New York

    Google Scholar 

  • Velling P (1974) Phenotypic and genetic variation in the wood basic density of Scots pine (Pinus sylvestris. L.). Folia Forestalia 188. Finnish Forest Research Institute. Helsinki. (In Finnish with English summary), pp 1–29

  • Vikram V, Cherry ML, Briggs D, Cress DW, Evans R, Howe GT (2011) Stiffness of Douglas-fir lumber: effects of wood properties and genetics. Can J For Res 41:1160–1173. doi:10.1139/x11-039

    Article  Google Scholar 

  • Wu HX, Ivković M, Gapare WJ, Matheson AC, Baltunis BS, Powell MB, McRae TA (2008) Breeding for wood quality and profit in Pinus radiata: a review of genetic parameter estimates and implications for breeding and deployment. N Z J For Sci 38:56–87

    Google Scholar 

  • Wu HX, Sanchez L (2011) Effect of selection method on genetic correlation and gain in a two trait selection scheme. Aust For 74:36–42. doi:10.1080/00049158.2011.10676344

    Article  Google Scholar 

  • York HH, Littlefield EW (1942) The naturalization of Scotch pine, northeastern Oneida County, New York. J For 40:552–559

    Google Scholar 

  • Zhang SY, Jiang ZH (1998) Variability of selected wood characteristics in 40 half-sib families of black spruce (Picea mariana). Wood Sci Technol 32:71–82. doi:10.1007/BF00702561

    Article  CAS  Google Scholar 

  • Zhelev P, Ekberg I, Eriksson G, Norell L (2003) Genotype environment interactions in four full-sib progeny trials of Pinus sylvestris (L.) with varying site indices. For Genet 10:93–102

    Google Scholar 

  • Zobel B, Talbert J (1984) Applied forest tree improvement. John Wiley & Sons, New York, pp 505

Download references

Acknowledgments

We acknowledge the assistance in field sampling by Henrik Hallingbäck, David Hall and Mr Zhiqiang Chen and sample preparation by Valentina Floran and Ann Sehlstedt. SilviScan services were provided by Sven-Olof Lundqvist from Innventia, and Bengt Andersson from Skogforsk provided advices on the project and the access of the experiment.

Funding

The project was funded by grants from Kempestiftelserna and Föreningen Skogsträdsförädling foundation. Institutional support from the Swedish University of Agriculture Sciences and in-kind support from Skogforsk and Innventia are greatly acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Harry X. Wu.

Additional information

Handling Editor: Jean-Michel Leban

Contributions of the co-authors

Zhou Hong's contribution includes field data collection, data analysis and the writing of the manuscript. Anders Fries coordinated the experiment design, data collection and contributed to the writing of the manuscript. Harry X. Wu initiated the project, designed sampling strategy and contributed to the writing of the manuscript. All authors read and approved the final manuscript.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hong, Z., Fries, A. & Wu, H.X. High negative genetic correlations between growth traits and wood properties suggest incorporating multiple traits selection including economic weights for the future Scots pine breeding programs. Annals of Forest Science 71, 463–472 (2014). https://doi.org/10.1007/s13595-014-0359-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13595-014-0359-3

Keywords

Navigation