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Prediction Equations for Centers of Gravity and Moments of Inertia of Loblolly Pine Stems

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Adequate design of tree harvesting equipment requires reliable estimates of centers of gravity and moments of inertia for full trees and tree-length stems. Several prediction models were developed for both centers of gravity and moments of inertia based on the theory of geometric solids. These models were fitted to center of gravity and moment of inertia estimates that were derived from stem dimension and weight measurements on loblolly pine (Pinus taeda L.) trees. The models were compared, and the best prediction equations for center of gravity and moment of inertia of tree-length stems were identified. Application of standard multiple regression methods resulted in a moment of inertia prediction model with a slope parameter estimate that had a sign opposite to that indicated by a theoretical model. Ridge regression and nonlinear regression were used to fit moment of inertia prediction models having coefficient signs consistent with those predicted by the theoretical model. The parameter estimates obtained by nonlinear regression were selected since they conformed more closely to properties of the theoretical moment of inertia model. FOR. SCI 39(2):260-274.

Keywords: Harvesting; Pinus taeda L; nonlinear regression; ridge regression

Document Type: Journal Article

Affiliations: Graduate Research Assistant, School of Forestry and Wildlife Resources, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0324

Publication date: May 1, 1993

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.
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