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Indirect Prediction of Breeding Values for Fusiform Rust Resistance of Slash Pine Parents Using Greenhouse Tests

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Abstract:

Six-week-old greenhouse-grown seedlings of 100 open-pollinated slash pine families were artificially inoculated with fusiform rust fungus at the USDA Forest Service Resistance Screening Center (RSC). All families had been tested for rust resistance in four or more field tests. Selection indices were developed to use symptoms of rust infection observed in the greenhouse to predict parental breeding values for field resistance to fusiform rust. Of the 100 families, 75 represented an unimproved population, while 25 represented a population improved for rust resistance. A large number (56,688) of indirect selection indices were considered in an attempt to identify efficient indices which use a small number of traits. Indices were developed using three different sets of variance and covariance estimates: (1) from the unimproved population, (2) from the improved population, and (3) from the combined population. Separate indices were necessary for the two distinct populations. The new indices were more correlated with field resistance and result in more efficient indirect selection for field resistance than the equation currently in use by the RSC. However, the greenhouse test to indirectly assess field rust resistance (using the new indices) is somewhat less efficient than a single field progeny test on average. For. Sci. 38(1):45-60.

Keywords: Cronartium quercuum f. sp. fusiforme; Pinus elliottii var. elliottii; breeding value; indirect selection; selection index

Document Type: Journal Article

Affiliations: School of Forest Resource and Conservation, University of Florida, Gainesville, FL 32611

Publication date: February 1, 1992

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

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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