Near-infrared spectroscopy can characterize wood surfaces fast and without significant surface preparation. It is based on molecular overtone and combination vibrations which are typically very broad, leading to complex spectra. Multivariate calibration techniques are often employed to extract the desired chemical information. This study focused on the potential of near-infrared spectroscopy combined with partial least squares for identifying and sorting wood with respect to species and physical properties and on the effects of wood preparation and weathering on the precision of analysis. It was shown that a range of moisture content values and artificial weathering periods could be well predicted indepenedently of wood species analyzed. Species within the spruce-pine-fir species group could be predicted reasonably well when tested under similar conditions. When different moisture contents and weathering exposure periods were introduced, species prediction was still possible, but, with decreased prediciton ability.