Estimation of total extractive content of wood from planted and native forests by near infrared spectroscopy

Abstract

The aim of this study was to evaluate the performance of multivariate models using Near infrared (NIR) spectra for predicting total extractives content of solid and powdered wood of planted and native species from tropical savanna. NIR spectra were recorded on the milled wood and radial surface of solid wood specimens of Cedrela sp., Jacaranda sp., Apuleia sp., Aspidosperma sp. and clones of Eucalyptus hybrids via an integrating sphere and fiber optics probe. NIR spectral signatures were evaluated by Principal Component Analysis (PCA) and then associated to the total extractive content quantified by extraction in toluene/ethanol (2:1) solutions, pure ethanol and hot water by Partial Least Squares (PLS) regressions. PCA revealed that NIR spectra measured in solid wood by integrating sphere gave a better discrimination of wood species. A global PLS model was developed based on NIR obtained by integrating sphere with satisfactory estimations both for solid wood (R²cv= 0.87, RMSECV= 1.08%) and wood powder (R²cv= 0.85, RMSECV= 1.19%). An independent test-set validation was performed with 25% of the samples and yielded R²p= 0.93 and RMSEP= 0.95% (for solid wood) and R²p= 0.87 and RMSEP= 1.40% (for wood powder). Both models can be applied for rapid screenings, though models developed from NIR spectra by integrating sphere on solid wood are considered more suitable for rapid predictions of extractive content in unknown wood specimens.

Keywords

• Lumber
• Multivariate Analysis
• Non-destructive Testing
• Test Set Validation
• Wood Chemistry