The use of near-infrared scanning for the prediction of pulp yield and chemical properties of Pinus patula in the Mpumalanga escarpment area of South Africa

Abstract

Near-infrared (NIR) scanning technology is regarded as a potential tool for rapid determination of wood properties, which can substitute time-consuming and costly traditional methods. Pinus patula is the most important softwood species in South Africa, and this study is aimed at developing NIR calibration models for quick prediction of its pulp yield and chemical composition. A total of 85 trees from 17 plots, covering the range of site conditions in the Mpumalanga escarpment area, were sampled. Two samples were taken from each tree: a 1 m billet above breast height and a 20 mm disc at breast height. The billet was pulped using the kraft pulping process to determine pulp yield. The disc was ground into sawdust and the chemical composition was determined using conventional wet chemistry. Sawdust was scanned on a NIR spectrophotometer to produce NIR spectra. Calibration models to predict pulp yield, cellulose and lignin content were developed by applying chemometrics and partial least squares regression. Validation and determination of prediction accuracy of the models were performed using independent data. The prediction of cellulose and lignin were acceptable with correlations of determinations (r ²) of 0.71 and 0.70 respectively. Standard errors of prediction were generally low (less that 0.86) for all the models. The prediction r ² for both total and screened pulp yield were only 0.62. Although the cellulose and lignin models can be used with confidence, the expansion of the sample size for follow-up research must be considered in order to increase the variability of tested wood properties and improve the prediction strength of the models. The NIR calibration provided in this study can contribute to the efficient examination of forest site-to-wood quality relationships that would enhance precision forest management and wood processing efficiency.

Keywords:

• cellulose
• lignin
• near infra-red calibration models
• Pinus patula
• pulp yield