The Predictive Accuracy of Modulus of Elasticity (MOE) in the Wood of Standing Trees and Logs

The characterization of poplar wood assumes a strategic position to increase the competitiveness entire forest supply chain. From this aspect, identification quality represents primary objective for researchers and private landowners. can be defined via traditional visual methods based on experience technicians or using tools, such as incremental drills sound hammers. properties these traits, only characteristics, outline classification macroscopic with aim defining volume recoverable wood. However, approach does not provide good indicator physical mechanical Mechanical tests require felling trees correlated preparation specimens. A different solution determine is application non-destructive technology (NDT). In context, present study was predictive accuracy analysis MOEd in standing logs 22-year-old clone examine relationship MOEs sawn This also studied at three stem heights. We non-destructively measured green TreeSonic Resonance Log Grader compared results those obtained destructive method universal testing machine. showed that I-214 trees, dynamic elastic moduli were validly static modulus. These suggest it possible evaluate directly from techniques (NDT) tool easily used presort material forest.