This paper deals with the characterization of the properties of wood fibres leather shavings composite board by using the near infrared spectroscopy (NIRS) and multivariate data analysis. In this study fibreboards were manufactured with different leather amounts by using spruce fibres, as well as vegetable and mineral tanned leather shavings (wet white and wet blue). The NIR spectroscopy was used to analyse the raw materials as well as the wood leather fibreboards. Moreover, the physical and mechanical features of the wood leather composite fibreboards were determined to characterize their properties for the further data analysis. The NIR spectra were analysed by univariate and multivariate methods using the Principal Component Analysis (PCA) and the Partial Least Squares Regression (PLSR) method. These results demonstrate the potential of FT-NIR spectroscopy to estimate the physical and mechanical properties (e.g., bending strength). This phenomenon provides a possibility for quality assurance systems by using the NIRS.
The scarcity of resources can be a motor or motivation for innovation. The application of unused biogenic resources is one way where innovation can happen. With these new raw materials the product characteristics can change; thus material analysis and material test are necessary to determine the composite properties. Also guidelines for quality assurance of the new materials can aid in the transfer from laboratory to industrial conditions for consumer applications.
There is a lot of innovation regarding the use of by-product from biogenic resources in the forest product field [
Besides the biobased materials also the fossil-based materials, such as plastic waste [
To produce a wood based panel out of a mixture of wood fibres and leather particles is a quite new idea, which was patented by Lackinger [
Therefore, based on their mechanical and technical properties the wood leather fibre composites are one of the most interesting wood engineered materials of the last years. These composite materials are highly sustainable because they can be produced by coupling wood fibres with industrial waste of tannery plants. The analysis of the wood leather fibreboard with the near infrared spectroscopy (NIRS) can provide a basis for further efforts in the upscaling from the laboratory to industrial conditions for consumer application concerning this tool for the development of quality assurance control system.
When leather gets produced, hides have to run through different production steps. After the withdrawal of the skin a preservation process has to be done to protect the freshly peeled skins against the influence of microorganisms. The next step, the tanning process, is used to protect the skin against enzymatic degradation and increase their resilience. Only after this production step the skins are called leather. For this investigation the leather types, wet blue and wet white, were used (Figure
Raw materials to produce the composite materials: (a) wood fibres, (b) leather shavings wet blue, and (c) leather shavings wet white.
The leather particles accrue during the shaving process of hides preparation, where they got sliced to a specific thickness. These particles were dried to moisture content (m.c.) of
Norway spruce wood fibres (
The spruce fibres and wet white leather particles were glued based on the oven-dry density with 10% urea formaldehyde (UF) resin with 1% ammonium sulphate solution in a lab ENT WBH 75 ploughshare blender type with a Schlick two-substance nozzle upright section. For the process a nozzle with a whole diameter of 2.3 mm and a pneumatic pressure of 2 bar was used. Further the glued fibres were distributed manually in a frame and were pressed to a final thickness of 8 to 20 mm in a Hoefer HLPO 280 automated hot lab press at 80°C with a pressing factor of 1 min/mm. Fibreboards with dimensions of 450 × 450 mm2 with different thicknesses were produced under laboratory conditions. The ratio of different leathers to the wood fibres and the various thickness of fibreboard samples were selected from the results of various previous mechanical studies by Solt et al. [
For FT-NIR measurements each raw material (e.g., leather particles and wood fibres) was milled with a cutting mill (Retsch) using solid CO2 to pass a mesh of 500
The FT-NIR spectra were obtained on the surface of wood leather fibreboards and on the milled fibres of each sample by an MPA spectrometer (Buker) equipped with a fibre probe (4 mm measurement diameter) at a resolution of 8 cm−1 (32 scans). For every wood leather fibreboard and milled fibres five single spectra of the surface per sample were taken to minimize the influence of different concentrations of wood and leather shavings on various wood leather panels.
The sample preparation and the mechanical testing procedure for the modulus of rupture (MOR) and elasticity (MOE) were done according to the OENORM EN 326-1 [
The Unscrambler 10.3 software (CAMO, Norway) was used for the data analysis. The FT-NIR spectra were managed without data treatment and also were pretreated by using the second derivative (15 smoothing points). Principal Component Analysis (PCA) is a linear projection method to reduce the multidimensional data (e.g., NIR spectra) to only few orthogonal features (principal components (PCs)). The Partial Least Squares Regression (PLSR) method was applied to find the latent variables in
The chemical information relating to the two different milled leather powders and the milled wood powder was obtained by using the FT-NIR spectroscopy. Figure
FT-NIR spectra of various raw materials in the wave number range of 9000–4000 cm−1.
These results show that the NIR spectroscopy is suitable for characterizing different materials of wood and leather, which was also depicted by the FT-IR and Raman Spectroscopy [
Also, the NIR spectra of the various wood leather panels show differences in IR bands (Figure
FT-NIR spectra of wood leather fibreboards with various concentrations of wood and wet white (ww) leather particles in the wave number range between 9000 and 4000 cm−1.
For this reason, the data of the NIRS were used for the classification via principal components analysis (PCA). Figure
Principal component (PC) analysis score plot of near infrared spectra of various wood fibre leather panels.
It can be observed that the two principal components allow the classification of the amount of leather shavings in the panels.
Even though the PC 1 explained 85% of the variance, whereas the PC 2 explains only 13% of the variance, the combination of the two components describes the two most important parameters: wood fibre and leather content. The loadings of the PCs provide information between each of wave numbers and the corresponding score plot of the principle components (Figure
Loadings of the first two principal components (PCs) of near infrared spectra of various wood fibre leather panels.
The loadings of the PC 1 show high positive values for the wave numbers around 5110 and 4562 cm−1, which represent protein vibrations. In the loadings for PC 2, contributions of the wood fibres (e.g., cellulose) derived bands can be observed at band around the wave number 4747 cm−1, which has the highest positive values of the loadings.
The results of the physical and mechanical properties of various wood leather fibreboards are shown in Table
Estimated mean and standard deviation (SD) of the physical and mechanical properties of the wood leather fibreboards with different leather types (ww and wb) and various ratios of wood fibre and leather.
Composition1 of the panel | Thickness (mm) | Density (kg/m3) | MOE |
MOR# (N/mm2) | ||
---|---|---|---|---|---|---|
Wood (%) | ww leather (%) | wb leather (%) | ||||
66.6 | 33.3 | — | 8 | 807 (49.9) | 1997.53 (148.30) | 23.32 (1.66) |
66.6 | 33.3 | — | 12 | 854 (31.4) | 1779.72 (120.77) | 17.11 (1.79) |
66.6 | 33.3 | — | 16 | 767 (39.1) | 1721.00 (156.89) | 17.14 (2.03) |
66.6 | 33.3 | — | 20 | 764 (50.5) | 1627.89 (195.98) | 15.47 (2.35) |
33.3 | 66.6 | — | 8 | 829 (27.7) | 1178.70 (95.74) | 13.00 (1.10) |
33.3 | 66.6 | — | 12 | 890 (29.3) | 1151.01 (83.25) | 13.33 (0.89) |
33.3 | 66.6 | — | 16 | 835 (34.0) | 1278.56 (127.11) | 13.80 (1.35) |
— | 100 | — | 8 | 722 (24.3) | 539.00 (88.67) | 6.35 (0.94) |
— | 100 | — | 12 | 935 (59.1) | 1099.31 (237.85) | 9.35 (1.76) |
— | 100 | — | 16 | 956 (63.7) | 908.67 (160.08) | 10.67 (1.93) |
— | 100 | — | 20 | 951 (59.0) | 816.53 (156.04) | 10.30 (1.98) |
66.6 | — | 33.3 | 12 | 772 (90.0) | 1513.00 (349.01) | 14.57 (3.42) |
66.6 | — | 33.3 | 16 | 703 (60.5) | 1577.00 (98.86) | 11.80 (0.87) |
66.6 | — | 33.3 | 20 | 694 (77.7) | 1488.00 (189.81) | 15.15 (1.82) |
33.3 | — | 66.6 | 12 | 828 (30.4) | 1142.00 (277.49) | 12.59 (2.86) |
33.3 | — | 66.6 | 16 | 777 (79.6) | 1122.00 (251.38) | 11.80 (0.87) |
33.3 | — | 66.6 | 20 | 725 (34.5) | 938.00 (208.01) | 9.72 (2.01) |
#Modulus of rupture/bending strength (standard deviation).
For the PLSR models the NIR data were pretreated by using the second derivative (15 smoothing points). A full cross-validation was performed for every sample. For wood leather fibreboard samples (
Predicted versus measured values of the PLSR model to estimate the bending strength with the FT-NIR data.
The relationship between the mechanical properties and the FT-NIR spectra demands further consideration. The physical and mechanical features of the wood fibre leather composite samples depend on the leather content of the fibreboards. The geometric form of leather particles is not to be compared with wood fibres. Therefore, the distribution of the leather particles is not homogeneous [
Based on these results of this study, NIR spectroscopy can be used to distinguish wood fibres from different types of leather shavings (wet white and wet blue). These differences can be also observed of the wood leather fibreboard samples. The score plot from the PCA depicts a possible classification into various amounts of leather contents of the fibreboards. Moreover, the PLSR models for the prediction of the physical and mechanical properties were successfully developed. These results demonstrate that a classification of fibreboard composite and the estimation of density as well as bending strength features are possible with fast, nondestructive measurement methods. The methods may serve a basis to establish guidelines for quality assurance control systems of this new engineered wood leather composite fibreboard. These findings provide a basis for further efforts in the upscale from laboratory to industrial conditions for consumer applications.
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors gratefully acknowledge the support of the Austrian Research Promotion Agency (FFG) in Vienna under Grant no. 836988.