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Variability studies for needle and wood traits of different half sib progenies of Pinus roxburghii Sargent

Abstract

Genetic variability studies for needle and wood traits were carried out for the different half sib progenies of Chir pine, raised in 1985 at the main campus of University. There existed a significant variation for these traits among the different half sib progenies, viz., needle length (18.1–24.6 cm), needle thickness (0.53–0.71 mm), number of stomata per mm of a row (7.3–12.0), specific gravity of wood (0.36–0.46), tracheid length (1.51–1.85) and moisture content of wood (47.76–58.81). This variability was found under genetic control, as all these progenies are growing under same environment, and are of same age. Traits having high heritability and genetic gain like, needle thickness, wood specific gravity, tracheid length and others, indicate high genetic control. This variability can be exploited in tree improvement programs through selection and breeding approaches for development of advanced generations. Correlation studies for different traits at genotypic and phenotypic levels provided the basic knowledge of association to chalk out efficient breeding strategy for higher productivity through indirect selection.

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Acknowledgments

Part of the project was carried out under Network Project on Harvesting, Processing and Value Addition of Natural Resins and Gums, Ranchi, for which the first author is highly thankful to the former Director Dr. R. Ramani and Project Coordinator, Dr. N. Prasad. The first author also acknowledges the Department of Science and Technology, Govt. of India, for providing the fellowship under INSPIRE Fellowship program.

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Correspondence to Sheeraz Saleem Bhat.

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Bhat, S.S., Singh, N.B., Sankhyan, H.P. et al. Variability studies for needle and wood traits of different half sib progenies of Pinus roxburghii Sargent. Physiol Mol Biol Plants 22, 231–239 (2016). https://doi.org/10.1007/s12298-016-0358-y

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Keywords

  • Pinus roxburghii
  • Heritability
  • Tracheid length
  • Needle
  • Principal component analysis