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

Abstract

Background: Near infrared (NIR) spectroscopy has been successfully applied to estimate the chemical, physical and mechanical properties of various biological materials, including wood. This study aimed to evaluate basic density calibrations based on NIR spectra collected from three wood faces and subject to different mathematical treatments. Methods: Diffuse reflectance NIR spectra were recorded using an integrating sphere on the transverse, radial and tangential surfaces of 278 wood specimens of Eucalyptus urophylla x Eucalyptus grandis. Basic density of the wood specimens was determined in the laboratory by the immersion method and correlated with NIR spectra by Partial Least Squares regression. Different statistical treatments were then applied to the data, including Standard Normal Variate, Multiplicative Scatter Correction, First and Second Derivatives, Normalization, Autoscale and MeanCenter transformations. Results: The predictive model based on NIR spectra measured on the transverse surface performed the best (R²cv = 0.85 and RMSE = 25.5 kg/m³) while the model developed from the NIR spectra measured on the tangential surface had the poorest performance (R²cv = 0.53 and RMSE = 46.8 kg/m³). The difference in performance between models based on original (untreated) and mathematically-treated spectra was minimal. Conclusions: Multivariate models fitted to NIR spectra were found to be efficient for predicting the basic density of Eucalyptus wood, especially when based on spectra measured on the transversal surface. For this data set, models based on the original spectra and mathematically treated spectra had similar performance. The reported findings show that mathematical transformations are not always able to extract more information from the spectra in the NIR.

Prediction of the Carbon Content of Six Tree Species from Visible-Near-Infrared Spectroscopy

“…According to the research of Jiang Z. H. et al [51] and Evelize A. [29], the information contained in the near-infrared spectra of the three sections of wood samples can be used to characterize wood samples, and the information content is rich. According to the characteristics of the experimental materials, the cross-section of the wood sample was selected to collect the near-infrared spectrum (Figure 1a).…”

“…Coupled with suitable chemometric methods, NIR has been successfully applied in many fields such as the petrochemical [18,19], agricultural [20][21][22], food [17,23,24], pharmaceutical [25], and traditional Chinese medicine industries [26]. In recent years, Vis-NIR has also shown great potential in forestry applications [27][28][29][30]. Wood spectroscopy relies on the fact that the fraction of reflected light received by the instrument at any given wavelength (typically between 350 and 2500 nm in the visible and near-infrared parts of the spectrum) relates to the vibrational and rotational states of molecules containing oxygen, hydrogen, carbon, or nitrogen atoms.…”

Estimation of the basic density of Eucalyptus grandis wood chips at different moisture levels using benchtop and handheld NIR instruments

“…The information obtained from NIR spectroscopy is associated with the values of the properties determined in the laboratory. From this, statistical models can be developed to predict such properties; partial least squares regression (PLS-R) is the most commonly used model for analysis (Sandak et al, 2016;Amaral et al, 2021).…”

“…Among the wood properties, the density variation has a strong correlation with the spectral signature in the NIR (Hein et al, 2009). In the studies by Rosso et al (2013), Costa et al (2018), Arriel et al (2019), and Amaral et al (2021), models for estimating the basic density of Eucalyptus wood by NIR spectroscopy with a benchtop instrument showed adequate results for the selection of the genetic material in forestry companies.…”

Identification of Eight Pterocarpus Species and Two Dalbergia Species Using Visible/Near-Infrared (Vis/NIR) Hyperspectral Imaging (HSI)

“…Coupled with suitable modeling methods, Vis/NIR has been successfully applied in many fields, such as the petrochemical [17,18], agricultural [19,20], food [21,22], and pharmaceutical [23] industries. In recent years, Vis/NIR has also shown great potential in forestry applications [24][25][26]. Compared with Vis/NIR, Vis/NIR-HSI provides simultaneous determination of the physical and chemical properties of the sample as well as their spatial distribution, which overcomes some limitations of Vis/NIR spectroscopy.…”