Modelos NIRS para as características químicas da madeira de Eucalyptus benthamii Maiden & Cambage

Abstract

Near Infrared Spectroscopy (NIRS) is a non-destructible, fast, and reliable technique that can be applied in many different samples. NIR has been shown to be an efficient tool in determining the chemical, anatomical, physical, and mechanical properties of wood. The aimed of this study was to development calibration models for the wood of Eu-calyptus benthamii as to its chemical constitution. For the development of the calibration models 87 trees were used (75 of E. benthamii, 4 of E. dunnii, 4 of E. grandis, and 4 of E. saligna). A portion of the sample was used for analysis of ash, extractives, lignin and holocellulose content. Another portion was milled and used to acquire the spectra, which were later correlated to laboratory values. Calibration of the model was determined by partial least squares regression analysis (PLS). Selection of the best models was based on the following statistical criteria: coefficient of determination (R²), mean cross-validation error (RMSECV), residual forecast deviation (RPD), and number of latent variables (VLs). The chemical composition of E. benthamii wood agrees with the results evidenced in the literature for Eucalyptus. NIRS calibration models presented satisfactory adjustments for holocellulose content (R2 = 0.82), total lignin content (R2 = 0.74) and Klason lignin content (R2 = 0.82). The NIRS models developed in this study present a viable commercial tool for characterization of samples of Eucalyptus benthamii wood for the cellulose industry.