Wood Science and Technology

, Volume 30, Issue 1, pp 63–75

Genetic variation and inheritance of wood density in black spruce (Picea mariana) and its relationship with growth: implications for tree breeding

  • S. Y. Zhang
  • E. K. Morgenstern
Originals

DOI: 10.1007/BF00195269

Cite this article as:
Zhang, S.Y. & Morgenstern, E.K. Wood Sci.Technol. (1995) 30: 63. doi:10.1007/BF00195269

Summary

Based on 15-year-old spruce (Picea mariana) trees of 40 open-pollinated families grown in New Brunswick, this study examined the genetic variation and inheritance of wood density, and its relationship with growth trait (tree diameter, tree height and bole volume). Implications of these genetic parameters for wood quality improvement were discussed. Although wood density, earlywood density and latewood density show smaller phenotypic variation than growth traits, a larger part of the variation in these traits is due to families. These traits are under strong genetic control (hi2ranges from 0.60 to 0.86, and hf2ranges from 0.56 to 0.68). Wood density has a strong genetic correlation with earlywood density and latewood density (+0.72 and -0.73, respectively), but earlywood density and latewood density are strongly related to each other. As a result, wood density components have little value in improving the efficiency of selection for overall wood density. Overall wood density shows negative genetic correlations with growth traits (ranging from -0.34 to -0.41). To achieve optimal genetic gains, therefore, index selection for multiple traits is essential. This study reveals that selection for dry mass weight would result in remarkably higher genetic gain in gross fibre yield than selection for bole volume alone (+14.15% and +9.28%, respectively). Furthermore, selection for dry mass weight would result in less reduction in wood density, and while holding wood density at zero change, it is still possible to obtain huge genetic gain in gross fibre yield.

Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • S. Y. Zhang
    • 1
  • E. K. Morgenstern
    • 2
  1. 1.Resource Assessment and Utilization, Forintek Canada Corp.Sainte-FoyCanada
  2. 2.Faculty of Forestry and Environmental ManagementUniversity of New BrunswickFrederictonCanada

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