ABSTRACT. The goal of this research was to develop nondestructive evaluation (NDE) he strong demand for wood together with timber harvest restrictions and escalating raw material costs have accentuated the need for efficient T utilization of wood resources. In the case of lumber, efficiency dictates that it be accurately sorted into grades, each having an acceptable range of quality for the intended uses.Current methods for grading structural lumber include visual stress rating (VSR), machine stress rating (MSR), and machine evaluating lumber (MEL). Both visual and mechanical lumber grading methods inherently have some limitations. The VSR categorizes lumber strength by surface characteristics alone, resulting in relatively wide variabilities of mechanical properties within grades. The MSR and MEL use nondestructively measured properties of modulus of elasticity (MOE) and density, respectively, to predict lumber strength, followed by a visual check for certain defects in the lumber. Linear correlations between MOE or density and lumber strength typically range from 0.6 to 0.8. Since predictions of lumber strength are not 100% accurate, visual grading rules and machine grading thresholds are conservatively set to minimize the probability of assigning a piece of lumber a grade that is too high.Research is needed to develop innovative stress rating technology for more accurate grading of lumber, leading to better utilization of timber resources. Another incentive for developing new lumber grading technology is the cost of present grading machines, which is prohibitive for many of

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