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Wood basic density is indicative of several other properties and is considered a key feature for many industrial applications. Near infrared spectroscopy (NIRS) is a fast, efficient technique that is capable of estimating that property. However, it should be improved in order to complement the often time-consuming and costly conventional method. Research on wood technological properties using near infrared spectroscopy has shown promising results. Thus the aim of this study is to evaluate the efficiency of near infrared spectroscopy for estimating wood basic density in Eucalyptus urophylla and Eucalyptus grandis. The coefficients of determination of the predictive models for cross validation ranged between 0.74 and 0.86 and the ratio performance deviation (RPD) ranged between 1.9 and 2.7. Application of spectral filter, detection and removal of outlier samples, and selection of variables (wavelength) improved the adjustment of calibrations, thereby reducing the standard error of calibration (SEC) and cross validation (SECV) as well as increasing the coefficient of determination (R²) and the RPD. The technique of near infrared spectroscopy can therefore be used for predicting wood basic density in Eucalyptus urophylla and Eucalyptus grandis.