Mixed visual and machine grading to select eucalyptus grandis poles into high-strength classes

Before round timber can be profitably used in construction, it needs structural characterization. The visual grading of Eucalyptus grandis poles was integrated with additional parameters developed by multivariate regression analysis. Acoustic velocity and dynamic modulus of elasticity were combined with density and pole diameter in the estimation of bending strength and stiffness. The best models achieved were used to group the visually graded material into qualitative structural classes. Overall, dynamic modulus of elasticity was the best single predictor; and adding density and diameter to the model improved the estimation of strength but not of stiffness. The developed parameters separated the material into two classes with very distinct mechanical properties. The models including velocity as a parameter did not perform as well. The strength grading of Eucalyptus grandis poles can be effectively improved by combining visual parameters and nondestructive measurements. The determination of the dynamic modulus of elasticity as a grading parameter should be preferred over that of acoustic velocity.