An efficient method to reduce grain angle influence on NIR spectra for predicting extractives content from heartwood stem cores of Toona. sinensis

Abstract

Background A fast and reliable non-destructive method for qualifying the content of extracts content (EC) in heartwood of T. sinensis cores is needed in the breeding program for studying the genetically infect on EC. However, the affecting of grain angle on near infrared (NIR) spectra prediction model for EC is unclear. In this study, NIR spectra were collected both from cross section and radial section of wood core samples in order to predict the EC in heartwood. Results The effect of grain angle on calibration EC model was studied. Several different spectra pre-processing methods were tested for calibration. It was found that standard normal variation (SNV) followed by 1 st derivative yield the best calibration for EC. Grain angle has a significant influence on the predict model for EC when use the whole NIR spectra. However, after using the significant multivariate correlation (sMC) selection of the prior of wavenumbers for EC, the influence of grain angle have been significantly reduced. Conclusions It was suggested that NIR spectroscopy could be a promising methods to predict EC in solid wood without the infection of grain angle.