Investigating the Potential of Strength Grading Green Eucalyptus grandis Lumber using Multi-Sensor Technology

Michela Nocetti, Marco Pröller, Michele Brunetti, George Patrick Dowse, Conraad Brand Wessels


The exploitation of Eucalyptus grandis lumber as structural material may take advantage of the finger-jointing and edge-gluing of the boards while they are still wet, so as to reduce the natural susceptibility of the species to warp and split during drying. But the strength grading needed for structural uses, usually performed on dried lumber, should be done before any gluing process, then already in wet condition. Thus, detection and assessment of selected properties of the wet lumber were evaluated. Eucalyptus grandis boards were measured by a multi-sensor machine soon after sawing, then dried and measured again. Destructive bending tests were then performed to determine the mechanical properties of the lumber and several predictive models were compared. The determination of non-destructive parameters by the machine was as effective on fresh as on dry lumber. The dynamic modulus of elasticity was the best single predictor of mechanical properties. In contrast, the knot parameter did not show a correlation between strength and stiffness robust enough to justify the efforts to measure it. Wet grading proved to be as effective as dry grading. Therefore, the study suggests that measuring only dynamic modulus of elasticity on fresh lumber is the best approach for the mechanical grading of Eucalyptus grandis.


Non-destructive measurement; Machine grading; Hardwood; Wet processing

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Welcome to BioResources! This online, peer-reviewed journal is devoted to the science and engineering of biomaterials and chemicals from lignocellulosic sources for new end uses and new capabilities. The editors of BioResources would be very happy to assist you during the process of submitting or reviewing articles. Please note that logging in is required in order to submit or review articles. Martin A. Hubbe, (919) 513-3022,; Lucian A. Lucia, (919) 515-7707, URLs:; ISSN: 1930-2126