Wood basic density is one of the most important wood quality properties and one of the simplest to assess but it is too time consuming to be really useful for the screening of populations or for improvement programmes where large numbers of samples need to be assessed. Although the usefulness of near infrared (NIR) spectroscopy to assess wood properties, including wood density, is well established only a few of the published models are suitable for screening. The NIR-based partial least squares regression models obtained in this study can be used for screening the basic density of the Portuguese blackwood [Acacia melanoxylon (R. Br.)] population with standard errors of cross-validation of only 11 kg m−3 and values for the residual prediction deviation well above the 2.5 limit. It was also concluded that at least 45 samples for calibration and a further 16 samples for validation are necessary to obtain acceptable models for screening. Even using a very small number of spectra per disc, accurate estimates of wood basic density were obtained.
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