Identification of wood species by acoustic-resonance spectrometry using multivariate subpopulation analysis

The identification of wood species remains an issue in restoration involving rare, old, or disguised wood parts. Precise restoration is required in reconditioning the works of designers such as Frank Lloyd Wright, and a quick, reliable, and nondestructive method of identification facilitates this restoration. Acoustic-resonance spectrometry (ARS) is an analytical method using interferences in resonance signals across a range of frequencies. Combined with multivariate analysis techniques, ARS is a solution to the problem of identifying wood species. Subpopulation detection analysis of samples of 26 different wood species achieved complete differentiation among species (p = 0.01). The number of bootstrap replications of the spectral data has a significant effect on differentiation among the woods, as does the type of spectral filtering prior to subpopulation analysis. Acoustic-resonance spectrometry outperforms near-IR spectrometry by a wide margin in identification of the same wood species.