Influence of spectral acquisition technique and wood anisotropy on the statistics of predictive near infrared–based models for wood density

Abstract

Wood density is an important criterion for material classification, as it is directly related to quality of wood for structural use. Several studies have shown promising results for the estimation of wood density by near infrared spectroscopy. However, the optimal conditions for spectral acquisition need to be investigated in order to develop predictive models and to understand how anisotropy and surface roughness affect the statistics of predictive partial least square regression models. The aim of this study was to evaluate how the spectral acquisition technique, wood surface, and the surface quality influence the ability of partial least square-based models to estimate wood density. Near infrared spectra were recorded using an integrating sphere and fiber-optic probe on the tangential, radial, and transverse surfaces machined by circular and band saws in 278 wood specimens of six-yearold Eucalyptus hybrids. The basic density values determined by the conventional method were then correlated with near infrared spectra acquired using an integrating sphere and fiber-optic probe on the wood surfaces by means of partial least square regressions. The most promising models for predicting wood density were generated from near infrared spectra obtained from the transverse surface machined by the bandsaw, via an integrating sphere (r 2 p ¼ 0:87, RMSEP ¼ 23 kg m À3 and RPD ¼ 3.0) as well as for the optic fiber (r 2 p ¼ 0:78, RMSEP ¼ 35 kg m À3 and RPD ¼ 2.1). Surface quality affected the spectral information and robustness of predictive models with a rougher surface, caused by band sawing, showing better results.

DEVELOPING NEAR INFRARED SPECTROSCOPIC MODELS FOR PREDICTING DENSITY OF Eucalyptus WOOD BASED ON INDIRECT MEASUREMENT

“…means of the fiber were also the ones that have worse association. The integration sphere was able to collect more useful information, during the acquisition of wood spectra, for predicting the basic density than fiber optics, a fact also reported by Costa et al (2018). Thus, it can be inferred that it is more efficient and its preference for use must be taken into account.…”

Evaluating basic density calibrations based on NIR spectra recorded on the three wood faces and subject to different mathematical treatments

“…Partial Least Squares (PLS-R) regressions were developed to describe the relationship between basic density of wood and NIR spectra for each specimen surface using the Unscrambler software (Camo AS, Norway, v.9.7). For calibration and validations, only the spectral range from 9,000 cm -1 to 4,000 cm -1 was considered as indicated by Costa et al (2018). The number of latent variables used in these regressions was automatically suggested by FIGURE 1: Transverse, radial and tangential surface the wood the software.…”

“…The average value is subtracted from the absorbance for every data point and the result is divided by the standard deviation (Reis et al 2013). The first derivative is widely used in original spectra obtained from wood and consists of better defining overlapping peaks in the same region and making the baseline correction in wood spectra as a result of the particle morphology (Costa et al 2018).…”

“…They found that differences between the two sets of calibrations were small, indicating that either face could be used for NIR analysis. These differences in performance of models developed using spectra obtained from transverse, radial or tangential surfaces can be explained by the variation in the wood anatomical structure in the different planes (Costa et al 2018). Variation in the exposition of the anatomical features in the different planes affects the absorbance and reflectance of NIR radiation.…”

“…For example, Hein et al (2010) demonstrated that the chemical properties of Eucalyptus urophylla wood are better estimated from the spectra measured in milled wood than in whole (unprocessed) wood. Costa et al (2018) investigated parameter settings of the NIR spectrometer and which wood surface is most suitable for measuring spectra and generating models to estimate wood density in Eucalyptus. According to Sandak et al (2016), there is still a need to better understand the fundamental issues and the impact that the most commonly utilised methods for pre-processing spectral data have on predictive models for wood properties (and those of other ligno-cellulosic materials).…”