Rapid spectroscopic separation of three Canadian softwoods

Near Infrared (NIR) and Fluorescence (FS) spectroscopy were investigated for their ability to rapidly separate three Canadian softwoods: balsam fir, western hemlock, and white spruce. NIR and FS spectral data were used to develop classification models using soft independent modeling of class analogies (SIMCA) method. For each wood species, spectra of 90 wood specimens were collected over a wavelength window of 800–2,500?nm for NIR spectral data and a wavelength range of 380–540 and 380–705?nm for FS spectral data. Raw spectra and first-derivative-transformed spectra were used to develop NIR calibration models to separate the three wood species using the wavelength ranges, 800–2,500, 1,100–2,200, and 1,300–2,000?nm, by the SIMCA method. Similarly, FS raw spectral data were also used to develop FS calibrations using wavelength ranges of 380–540 and 380–705?nm. Principal component analysis models were made for each class from the calibration set consisting of 65 specimens of each of the three wood species. Specimens not present in the calibration set (27 specimens of each wood species) were tested for classification according to the SIMCA method at a 5 and 25% significance level. Type I error associated with the models developed with NIR spectral data ranged from 0 to 19 and 0 to 52% for the 5 and 25% significance levels, respectively, while type II error ranged from 2 to 50 and 0 to 19%, respectively. When tested at a 5% significance level, there was no significant improvement in NIR models developed with first-derivative-transformed spectra over models developed with raw spectra. Type I error associated with the models developed with Fluorescence spectral data ranged from 0 to 4 and 7 to 30% for the 5 and 25% significance levels, respectively, while type II error ranged from 1 to 9 and 0 to 1%, respectively. There were no significant differences in performance of FS models developed with spectra using wavelength ranges of 380–540 and 380–705?nm.     

近红外光谱技术及其在木材科学中的应用

近红外光谱技术是一项新的木材无损评价方法,能够迅速、准确地对生长锥、固体木材或木粉等试样的性质进行全面无损评价,目前已广泛应用于木材性质预测、木材加工利用等方面的研究中,并为林木的定向培育、木材的遗传改良和高效利用提供技术支持。本文介绍了近红外光谱技术的基本原理及其主要应用,重点介绍了木材的近红外光谱技术及其在木材化学组成、物理力学性质、木材加工利用和木质复合材料等方面的研究成果及应用。     

近红外光谱技术在木材性质预测中的应用研究进展

林木定向培育和木材资源的优化利用, 都需要对大量木材样本的性质进行快速测试.然而, 传统的测试方法成本高、效率低, 不能满足生产和科研的需要.近红外光谱技术是一种新的无损评价方法, 能够迅速、准确地对木材试样的性质进行预测.文中主要介绍了近红外分析技术的基本原理、特点以及在预测木材化学组成、物理力学性质、解剖性质等方面的研究进展.     

Detection of the effective refractive index of thermally modified Scots pine by immersion liquid method

The purpose of this study was to determine the effective refractive index of thermally modified Scots pine (Pinus sylvestris L.) wood specimens as a quantitative measure regarding the change of wood density which is due to the thermal modification. The refractive index of thermally modified Scots pine wood was obtained by introducing pine wood powder into an immersion liquid and measuring light backscattering with a homebuilt multifunction spectrophotometer. The present method provides useful information that in principle can be applied, for example, in the optimization of the thermal modification process and inspection of the quality of thermally modified wood.     

Evaluation of thermally modified beech and spruce wood and their properties by FT-NIR spectroscopy

Quality assessment of thermally modified spruce (Picea abies (L.) Karst) and beech (Fagus sylvatica L.) wood and of the corresponding reference samples was carried out by means of non-destructive FT-NIR spectroscopic measurements and PLS regression. Oven-dry and basic density as well as MOE and MOR determined by 3-point bending tests were evaluated. The focus was put on specimens produced from material that had been thermally modified in an industrial scale kiln. Modelling results range from poor to very good. The results of the spectra taken from the spruce samples resulted in better prediction results than the spectra of the beech samples. This could be due to different proveniences or variation in the industrial modification process. The results indicate that FT-NIR surface measurements of sound thermally modified wood samples could be applied to evaluate several characteristics before and after the modification process. The method could be used for screening during pre-sorting of thermally modified wood.     

Shear strength of furfurylated,N-methylol melamine and thermally modified wood bonded with three conventional adhesives

The shear strength of furfurylated, N-methylol melamine (NMM) and thermally modified wood bonded with emulsion polymer isocyanate, polyvinyl acetate (PVAc), and polyurethane (PU) adhesives was examined. Furfurylation and NMM modification of Scots pine had a significant negative effect on the bonding strength with all adhesives irrespective of the treatment intensity. The obtained low-shear strength values were related to the brittle nature of the wood after modifications rather to the failure of the bondline. PVAc showed a better bonding performance with both furfurylated and NMM modified wood while the combination of furfurylated wood and PU gave the highest reduction in bonding strength (47–51%). Shear strength also decreased significantly after thermal modification in both Scots pine (36–56%) and beech (34–48%) with all adhesives. With the exception of thermally modified beech samples bonded with PU, bondline was found to be the weakest link in thermally modified wood as it was revealed by the wood failure surfaces. Bondline thickness and effective penetration of adhesives did not relate to the shear strength of all modified wood materials. The lower shear strength of modified wood could be attributed to other factors, such as the reduced chemical bonding or mechanical interlocking of adhesives, and the reduced strength of brittle modified wood substrate.     

Discriminant analysis of wood-based materials using near-infrared spectroscopy

 This study deals with the suitable discriminant techniques of wood-based materials by means of near-infrared spectroscopy (NIRS) and several chemometric analyses. The concept of Mahalanobis' generalized distance, K nearest neighbors (KNN), and soft independent modeling of class analogy (SIMCA) were evaluated to determine the best analytical procedure. The difference in the accuracy of classification with the spectrophotometer, the wavelength range as the explanatory variables, and the light-exposure condition of the sample were examined in detail. It was difficult to apply Mahalanobis' generalized distances to the classification of wood-based materials where NIR spectra varied widely within the sample category. The performance of KNN in the NIR region (800–2500 nm), for which the device used in the laboratory was employed, exhibited a high rate of correct answers of validation (>98%) independent of the light-exposure conditions of the sample. When employing the device used in the field, both KNN and SIMCA revealed correct answers of validation (>88%) at wavelengths of 550–1010 nm. These results suggest the applicability of NIRS to a reasonable classification of used wood at the factory and at job sites. Received: March 13, 2002 / Accepted: July 19, 2002 Acknowledgments The authors thank Gifu Prefectural Human Life Technology Research Institute and Kubota Co. for their support. We also thank Professor Dr. Shiro Kimura and Dr. Hideyuki Yokochi for their constructive discussions about the research.     

Research Advance of Near-infrared Spectroscopy in Wood Anatomical Characteristics Estimation

As a newly current advanced analysis technology,the near-infrared(NIR)spectroscopy possesses advantages of easy operation,fast and accurate detection,low cost and non-destructive test, has been widely used in the fields including pulp manufacturing and paper-making,wood properties estimation,wood progressing,wood composites producing and wood protection.In present work, based on introduction of the basic principles of NIR and its main characteristics,an overview was conducted focusing on the research status of wood anatomical characteristics(including cellulose crystallinity,microfibril angle and fiber morphology) estimation by using NIR spectroscopy.Moreover, the application trends were prospected.     

Determination of physical and chemical properties and degradation of archeological Japanese cypress wood from the Tohyamago area using near-infrared spectroscopy

Here, we evaluated the application of near-infrared (NIR) spectroscopy for estimating the degradation level of archeological wood samples from the Tohyamago area, the dendrochronological ages of which were also determined. The wood samples were radially cut from three logs obtained from the Tohyamago area. NIR reflectance spectra were measured from the tangential faces of air- and oven-dried wood samples using a Fourier transform NIR spectrophotometer. The second derivative spectra within the wavenumber range of 6400–5200 cm^?1, in which the effect of moisture content in wood is suspected to be insignificant, showed a characteristic behavior with age. By comparing the second derivative spectral change in our wood samples with that in wood degraded by aging, thermal treatment, fungal attack, and lightning reported in the literature, we found that the second derivative spectra of wood samples from one log was similar to those of wood degraded by hygro-thermal treatment, whereas those of wood samples from another log was similar to those of wood degraded by brown-rot fungi. The physical and chemical properties of archeological wood were well predicted using a combination of partial least square regression analysis and NIR spectroscopy.     

Prediction of dry veneer stiffness using near infrared spectra from transverse section of green log

This study examined the feasibility of near infrared spectroscopy as a novel technique for log assessment on the basis of wood property. Near infrared (NIR) spectra were obtained from the transverse section of green log and multivariate regression analysis was carried out to predict the stiffness of veneer processed from the log. The stiffness of the veneer was dynamic modulus of elasticity measured using ultrasonic method. The calibrations of veneer stiffness had moderate relationships between measured and NIR-predicted values, with regression coefficients ranging from 0.84 to 0.88. The calibration equations were applied to the test set and it was found that predictions were also well fitted, with regression coefficients ranging from 0.67 to 0.89. The results indicate that the variation of wood stiffness within the logs could be assessed using the NIR spectra from the cross-section of logs. The spectra were obtained from green condition of the log and the stiffness of veneer was measured after kiln drying. Thus, the results imply that the wood stiffness in dry condition could be predicted using the spectra collected from green logs. If the models obtained in this study put into the imaging system, the two-dimensional map of the stiffness would be visualized on the cross-section of logs. The NIR spectroscopy coupled with imaging system could compensate the weak point of the traditional methods for log assessment.     

近红外光谱结合支持向量机快速识别树种

利用阿达玛变换近红外光谱结合支持向量机,对制浆造纸常用木材树种的快速识别进行研究。将各树种近红外光谱先进行多点平滑和标准正态变换预处理以消除噪音干扰和光散射导致的测量偏差,然后基于不同建模策略建立一对多和一对一两种支持向量机模型,考察这两种模型对多树种属间分类和种间分类的预测能力,并与传统的偏最小二乘判别分析分类法进行对比。结果表明,支持向量机预测模型对桉木、相思木、杨木、水杉等树种的属间分类正确率达到98%以上,种间分类正确率均达到95%以上,在处理复杂分类问题时模型稳健性明显优于传统分类方法,从方法上证明了近红外技术工业化应用的可能性,为进一步建立近红外在线检测木片材性分析系统奠定了基础。     

Application of near-infrared spectroscopy for moisture-based sorting of green hem-fir timber

A rapid, non-destructive, in-line method suitable for sorting green hem-fir timbers (115-mm square) based on moisture content was established by near-infrared (NIR) spectroscopy. The accuracy of NIR sorting was compared with a commercial capacitance-type moisture meter. Mixedspecies samples consisting of three moisture classes were assessed in this study. The NIR-based prediction model showed positive correlation with the actual calculated values as determined by oven-drying, regardless of knots, surface roughness, and the mix of two wood species. NIR proved to be capable of detecting the moisture content between all pairs of the three moisture groups, whereas the capacitance-type moisture meter failed to establish a significant difference between middle- and high-moisture groups. These findings clearly demonstrate that NIR spectroscopy has a potential to estimate average moisture of green timber indirectly, although it inherently gives only surface moisture content values, as it is limited by scan depth.     

Wood defects during industrial-scale production of thermally modified Norway spruce and Scots pine

This research investigates wood defects, particularly the formation of surface cracks, during the production of thermally modified wood and its exposure to cyclic moisture changes. Boards of Norway spruce and Scots pine originating from different steps within the production of ThermoWood® were collected and wood defects were investigated at macroscopic and microscopic scale. Subsequently, the wood was exposed to capillary wetting cycles to record its sensitivity towards cracking. After the modification process, typical anatomical defects of conventional kiln-drying became more frequent and severe, with the magnitude being to some extent depending on the presence of defects in the raw material. At microscopic scale, damages to ray parenchyma and epithelial cells as well as longitudinal cracks within the cell walls of earlywood tracheids were evident in thermally modified wood. Despite a lower water uptake and higher dimensional stability, thermally modified wood was more sensitive to surface cracking during wetting cycles than unmodified wood, i.e. at the outside face of outer boards (near bark). For limiting surface cracking of thermally modified wood during service life, the use of high-quality raw material, the exposure of the inside face of the boards (near pith) and the application of a surface coating are considered beneficial.     

Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy

The use of calibrated near infrared (NIR) spectroscopy for predicting the chemical composition of Pinus taeda L. (loblolly pine) wood samples is investigated. Seventeen P. taeda radial strips, representing seven different sites were selected and NIR spectra were obtained from the radial longitudinal face of each strip. The spectra were obtained in 12.5 mm sections from pre-determined positions that represented juvenile wood (close to pith), transition wood (zone between juvenile and mature wood), and mature wood (close to bark). For these sections, cellulose, hemicellulose, lignin (acid soluble and insoluble), arabinan, galactan, glucan, mannan, and xylan contents were determined by standard analytical chemistry methods. Calibrations were developed for each chemical constituent using the NIR spectra, wood chemistry data and partial least squares (PLS) regression. Relationships were variable with the best results being obtained for cellulose, glucan, xylan, mannan, and lignin. Prediction errors were high and may be a consequence of the diverse origins of the samples in the test set. Further research with a larger number of samples is required to determine if prediction errors can be reduced.     

Development of chemometric models based on near infrared spectroscopy and thermogravimetric analysis for predicting the treatment level of furfurylated Scots pine

The use of furfuryl alcohol (FA) as a wood modification agent has been known for decades. An independent and reliable analytical method to determine the level of furfurylation is not available. This article reports the use of near infrared spectroscopy (NIR) and thermogravimetric analysis (TGA) to make partial least square prediction models for determining the furfurylation level (the percentage of FA polymer formed within the wood structure). A total of 115 individual samples of furfurylated Scots pine (Pinus sylvestris) originating from 115 production batches were used for modelling. As much as 81 samples were randomly selected for the calibration set and 34 samples for the validation set. Both NIR and TGA gave good predictions when validated by a separate test set. The r ² for NIR and TGA are 0.93 and 0.94, respectively, and the root mean square errors of predictions are 1.025 and 0.958, respectively. However, the number of principal components for the NIR and TGA models is two and six, respectively. The NIR method is preferred because only two principal components are used and sampling is fast.     

Comparison of <Emphasis Type="Italic">Pinus taeda</Emphasis> L. whole-tree wood property calibrations using diffuse reflectance near infrared spectra obtained using a variety of sampling options

A necessary objective for tree-breeding programs, with a focus on wood quality, is the measurement of wood properties on a whole-tree basis, however, the time and cost involved limits the numbers of trees sampled. Near infrared (NIR) spectroscopy provides an alternative and recently, it has been demonstrated that calibrations based on milled increment cores and whole-tree data can provide good estimates of whole-tree properties. Several options exist for sampling standing trees and the aim of this study was to compare wood property calibrations based on NIR spectra collected from samples obtained using different sampling methods. Calibrations for whole-tree lignin and basic specific gravity based on NIR spectra from whole-tree chips (milled or intact) had the strongest statistics, calibrations based on NIR spectra from milled increment cores were similar. Other options for sampling the tree (drill shavings, etc.) gave errors that were too large for practical applications. If an increment core is going to be used to estimate whole-tree properties, it is recommended that it be dried and milled prior to analysis.     

High accuracy rapid prediction and feasibility of on-site nondestructive estimation of Para rubber quality by spectroscopic methods

The aim of this study was to investigate convenient spectroscopic evaluation method of Para rubber quality. Ultra violet–near infrared (UV–NIR 370–1085 nm) spectra of latex were measured in transmittance mode. Calibrations for total solid content (TSC) and dry rubber content (DRC) were developed using spectral data set with aid of partial least square regression analysis using 57 samples. UV–NIR spectra of latex provided good regression models between measured and predicted values of TSC and DRC with determination coefficient for cross-validation of 0.96 and 0.97, respectively. The ranks were 2 and 1, respectively. This study suggests high accuracy in-line quality control of latex using UV–NIR spectroscopy. The long wavelength NIR spectra of bark were scanned to check the feasibility of on-site evaluation of latex quality by measuring the NIR spectra of standing tree. From the observation of near infrared spectra, it was shown that there was more latex signal in outer part of wood bark than in inner part of wood bark. This result suggests that the focal point should be on the outer part of bark to get the signal of latex when we measure the spectra of standing tree.     

Gluability of thermally modified beech (Fagus silvatica L.) and birch (Betula pubescens Ehrh.) wood

Abstract

One of the main disadvantages of wood is hygroscopicity resulting from its polar character. The sorption–desorption of water causes unwanted swelling and shrinkage in wood. Thermal modification substantially reduces this inconvenient feature. Unfortunately, the same chemical changes that reduce water sorption alter the polar character of the material and result in poorer wetting of thermally treated wood by waterborne adhesives. Gluability of thermally modified beech (Fagus silvatica L.) and birch (Betula pubescens Ehrh.) wood with two commercial amino resins, melamine–urea–formaldehyde (MUF) and melamine–formaldehyde (MF), and a two-component polyurethane (PUR) adhesive was investigated. Both wood species were modified according to two temperature regimes: 160°C and 190°C. Shear strengths of the joints were then determined according to EN 205:2003 standard. The results showed that thermally modified beech and birch wood can be effectively glued not only with commercially available PUR adhesives, but also with aqueous MF and MUF resins. The resultant shear strengths of the joints were limited by the strength of the thermally modified substrate.     

Non-destructive assessment of <Emphasis Type="Italic">Pinus</Emphasis> spp. wafers subjected to <Emphasis Type="Italic">Gloeophyllum trabeum</Emphasis> in soil block decay tests by diffuse reflectance near infrared spectroscopy

The use of calibrated near infrared (NIR) spectroscopy for measuring and predicting the advancement of wood decay in Pinus spp. sapwood wafers that were subjected to Gloeophyllum trabeum for periods ranging from 1 to 10 days was investigated. NIR spectra were obtained from the center of the cross-sectional face of each sample before and after decay tests. Mass loss and compression tests were also used to measure the progression of decay. Calibrations were created from NIR spectra, mass loss, and compression strength data using untreated and mathematically treated (multiplicative scatter correction and first and second derivative) spectra. Strong relationships were derived from the calibrations with the strongest R ² values being 0.98 (mass loss) and 0.97 (compression strength). Calibrations for mass loss showed the strongest statistics for predicting wood decay of a separate test set (0.85 raw, second derivative to 0.76 multiplicative scatter correction (MSC), while predictions for compression strength of the decayed samples resulted in R ² of 0.69 (raw) to 0.54 (MSC). Calibrations created from the amount of time the samples were decayed showed strong statistics, indicating that NIR spectroscopy can predict the early stages of wood decay.     

Rapid prediction of wood crystallinity in <Emphasis Type="Italic">Pinus elliotii</Emphasis> plantation wood by near-infrared spectroscopy

Crystallinity is an important property of woody materials; it responds to tree growth traits, structure, and chemical composition, and has a significant effect on Young’s modulus, dimensional stability, density, and hardness, etc. The ability of near-infrared (NIR) spectroscopy coupled with multivariate analysis to rapidly predict the crystallinity of slash pine (Pinus elliotii) plantation wood was investigated. The results showed that the NIR data could be correlated with the X-ray diffraction (XRD)-determined crystallinity of slash pine wood by use of partial least squares (PLS) regression, producing excellent coefficients of determination, r ², and root mean square error of calibration, RMSEC. The use of either reduced spectral ranges or the selection of certain wavelengths consistent with known chemical absorptions did not have any detrimental effect on the quality of PLS models allowing the use of inexpensive, small, and portable spectrometers. These studies show that NIR spectroscopy can be used to rapidly predict the crystallinity of slash pine wood.