NIR PLSR model selection for Kappa number prediction of maritime pine Kraft pulps

Abstract

A total of 910 maritime pine (Pinus pinaster Aiton) wood discs, belonging to a genetic trial of 80 families with 11–12 trees per family, were used in this study. A near infrared (NIR) partial least squares regression (PLSR) model for the prediction of Kappa number of Pinus pinaster Aiton pulps obtained from samples pulped under identical conditions was calculated. Very good correlations between NIR spectra of maritime pine pulps and Kappa numbers in the range from 58 to 100 were obtained. Besides the raw spectra, spectra pre-processed with ten methods were used for PLS analysis (cross validation with 57 samples), showing that even after test set validation (with 34 samples) no model decision could be made due to almost identical statistics. The final evaluation that proved the predictive power of the models by predicting pulps with unknown Kappa numbers allowed choosing a model according to a minimal number of outliers found during this process. The minimum–maximum normalized spectra in the wave number range from 6,110 to 5,440 cm−1 used for the calculation gave the best model with a root mean square error of prediction of 2.3 units of Kappa number, a coefficient of determination of 95.9%, and one PLS component. The percentage of outliers during evaluation was 0.9%.