Abstract

Near infrared diffuse reflectance was used for the determination of specific gravity in green Pinus taeda L. wood samples representing simulated increment cores obtained at breast height and merchantable green logs. The effects of using three pre-processing methods (second derivative, multiplicative scatter correction, and orthogonal signal correction) to reduce the scatter observed in the original spectra were evaluated. The effectiveness of each method was assessed in terms of the average predictive ability of the models and in terms of multivariate figures of merit derived from net analyte signal theory. Specific gravity was successfully modeled using green wood samples. No differences in predictive ability among models were found, although more parsimonious regressions were obtained using transformed spectra. The incorporation of figures of merit for the characterization of calibration models proved to be a valuable tool for understanding the effects of the pre-processing alternatives on the final results.

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