Multivariate calibration for quantitative analysis of eucalypt kraft pulp by NIR spectrometry

Near infrared spectrometry and multivariate data analysis were applied to predict the chemical composition and physico-chemical characteristics of eucalypt unbleached kraft pulps obtained at different laboratory pulping conditions. Viscosity, degree of polymerization (DP), kappa, brightness and contents of glucan, xylan, uronic acids, and lignin were the modeled variables using diffuse reflectance near infrared spectra obtained on pulp handsheets and the partial least squares (PLS) method. Models with two to four PLS components and good predictive ability were established after first derivative spectra pre-processing and application of cross-validation methodology. The predictive models can reduce the time consuming traditional analyses in the pulping industry laboratories, and also lead to a better process monitoring for suitable applications.