Abstract

Fourier transform near infrared (FT-NIR) associated with multivariate analysis was used to estimate glucan, xylan, 4-O-Methyl-a-D- glucuronic acid (MeGlcA) content, and pulp yield in kraft pulps of Eucalyptus globulus Labill. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of principal components regression (PCR) or partial least square (PLS) algorithms. Calibration models were built and validated by using all the spectral data and cross-validation methodology. The r c 2 values for the best calibration models for quantification of glucan, xylan, MeGlcA contents and pulp yield were between 0.71-0.92. The model was validated using a set of external samples. The amount of glucan (64-77%), xylan (12-18%), and MeGlcA (204-363 mmol kg pulp -1) in pulps were predicted with a root mean square error of prediction (RMSEP) of 0.91%, 0.46%, and 15.21% for glucan, xylan, and MeGlcA, respectively. Pulp yield (in the range of 46-70%) was also predicted with good accuracy with a RMSEP of 1.63%. These results suggest that glucan, xylan, MeGlcA composition, and pulp yield in kraft pulps of E. globulus can be adequately estimated by NIR spectroscopy for laboratory or industrial applications. NIR predictions can also provide useful and cost-effective tools for the rapid screening of large numbers of samples.