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Selection Efficiency for Solid Wood Traits in Pinus taeda using Time-of-Flight Acoustic and Micro-Drill Resistance Methods

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Conventional sampling and laboratory analysis of solid wood properties to facilitate clonal screening in tree improvement programs are prohibitively time-consuming and expensive. Alternative methods—time-of-flight acoustics and micro-drilling resistance—were assessed for efficiency in screening clones for wood stiffness (modulus of elasticity [MOE]), strength (modulus of rupture [MOR]), and density. Ninety clones, consisting of 30 from each of 3 full-sib families, were screened in an 8-year-old loblolly pine (Pinus taeda L.) field test using a TreeSonic time-of-flight tool and Resistograph drill resistance tool. The same clones were sampled for wood specimens for laboratory tests of MOE, MOR, and density. TreeSonic stress wave speed measurements produced highly repeatable clonal phenotypes that facilitated efficient selection for MOE and to a lesser extent for MOR. Resistograph amplitude measurements had a strong genetic correlation with wood density and facilitated highly efficient selection for density, with correlated responses for MOR and MOE. Combining the indirect traits into a selection index improved gain for mechanical wood traits. Both tools provided high measurement rates that resulted in cost efficiencies. Indirect measurements of solid wood properties should be attractive for clonal selection programs that must screen thousands of clones under a finite budget.

Keywords: clonal forestry; modulus of elasticity; modulus of rupture; nondestructive testing; wood density

Document Type: Research Article

Publication date: 2010-06-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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