Near Infrared Spectroscopy for Estimating Wood Basic Density (original) (raw)
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Rapid Prediction of Basic Wood Properties by Near Infrared Spectroscopy*
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The optimal utilisation of a wood raw material is dependent on the wood properties. In this study near infrared (NIR) spectroscopy was used to nondestructively predict density, modulus of elasticity, and modulus of rupture for small clear specimens cut from Picea abies (L.) Karst. (Norway spruce) trees. NIR spectra were recorded directly on the wood surface of each specimen as close as possible to the fracture developed during the bending test. Models were calibrated using partial least squares regression. The validation method was test set validation by data splitting. The correlation between predicted and measured values was highest for modulus of elasticity (0.86), followed by modulus of rupture (0.84) and density (0.79). The validation of the models showed that the average accuracies of predictions were 20.3 kg/m3 for density, 1.1 GPa for modulus of elasticity, and 6.1 MPa for modulus of rupture. Results are comparable to what has been found for other tree species, such as Pinus...
Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review
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Aims of study: Forestry-related companies require quality monitoring methods capable to pass a large number of samples. This review paper is dealing with the utilization of near infrared (NIR) technique for wood analysis.Area of study: We have a global point of view for NIR applications and characterization of different kind of wood species is considered.Material and methods: NIR spectroscopy is a fast, non-destructive technique, applicable to any biological material, demanding little or no sample preparation. NIR spectroscopy and multivariate analysis serve well in laboratories where the conditions are controlled. The main challenges to NIR spectroscopy technique in field conditions are moisture content and portability.Results: In this review, the methods and challenges for successfully applying NIR spectroscopy in the field of wood characterization are presented. Portable equipment need to record NIR spectra with low noise and low sensitivity to temperature and humidity variations...
Assessing Trees, Wood and Derived Products with near Infrared Spectroscopy: Hints and Tips
Journal of Near Infrared Spectroscopy, 2016
Wood is a renewable and valuable resource for a variety of end-use application areas. However, rapid and reliable assessments are needed to identify the quality of the tree, timber or wood product at all stages of production and processing. The ideal technology for assessing wood and wood products must provide reliable data, be user-friendly, cost-competitive and provide a rapid analysis. The ultimate application of near infrared (NIR) spectroscopy of wood or wood products is to substitute for costly and time-consuming reference measurements in order to aid process optimisation or determine properties and genetic traits on large numbers of individual samples. Increased interest in the application of NIR spectroscopy in various research fields including wood is observed nowadays. A vast number of publications highlight the potential of NIR spectroscopy for the characterisation of wood in a broad area of uses. The Journal of Near Infrared Spectroscopy has published two special issues ...
Near Infrared Spectroscopy ( NIRS ) as a Tool for Effective Classification of Wood
2008
Wood from different tree species is commonly similar in visual appearance but still have considerable differences in machining and wood properties. Even heartwood and sapwood from the same tree species may be difficult to separate visually, but the wood properties important for the quality of the final products may differ. Hence, within the forest products industry there is a great need to non-destructively evaluate wood quality prior to and during manufacturing in order to ensure effective allocation of raw material, and to obtain consistent and well defined quality of the end products. Near infrared spectroscopy is a promising technique because it requires minimal, if any, sample preparation and provides results rapidly, even when used on intact, opaque biological samples. In this paper we use near infrared spectroscopy combined with multivariate statistical analyses for classification of wood types. Case I considers heartwood and sapwood from Scots pine. On freshly cut wood heart...
Ability of near infrared spectroscopy to monitor air-dry density distribution and variation of wood
2005
Process control of wood density with near infrared spectroscopy (NIR) would be useful for pulp mills that need to maximize pulp yield without compromising paper strength properties. If models developed from the absorbance at wavelengths in the NIR region could provide density histograms, fiber supply personnel could monitor chip density variation as the chips enter the mill. The objectives of this research were to a) develop density histograms from actual density versus density histograms developed through NIR modeling, and b) determine the precision of density models developed from absorbance in the NIR region with a recommendation for the sample size needed to estimate the standard deviation of density at a given precision. Models for density were developed from calibration samples (n= 170) and then validated with 93 randomly held aside samples. The samples were systematically removed from 10 longleaf pine trees of equal age, but different growth rates. The histogram patterns for actual density almost paralleled the histogram patterns developed from predictive models. Subsequently, the validation data set was randomly categorized into groups of three, and the standard deviations of density were measured. For three measurements per data point, the predicted standard deviation covaried with the actual standard deviation of density with an R' = 0.61 and 0.55 for the calibration and validation data set, respectively. A sample size of 30 was recommended to estimate the standard deviation of density with a precision of 0.01 gicm3.
Journal of Near Infrared Spectroscopy, 2018
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-year-old Eucalyptus hybrids. The basic density values determined by the conventional method were then...
A review of near-infrared spectroscopy for monitoring moisture content and density of solid wood
Forestry Chronicle, 2013
This review article examines past and current research on the application of near-infrared (NIR) reflectance/transmittance spectroscopy (NIRS) for real-time monitoring of moisture content and density of solid wood. Most of the applications of NIRS on solid wood have focussed on the application of multivariate statistics as exploratory tools for the prediction of physical, chemical and mechanical properties, such as moisture content, density, stiffness, cellulose and lignin content. However, very few studies on the development of optical models and the use of NIRS transmittance techniques on solid wood have been reported. NIRS technology has the potential to be used as a rapid tool that could be employed for at-line measurement and monitoring of wood properties in the forest products industry.
Determination of radial profiles of wood properties using a near infrared scanning system
Journal of Near Infrared Spectroscopy, 2020
A near infrared (NIR) spectrometer, equipped with a 2-mm diameter fiber optic probe, was used to develop a rapid and automated method for determining the radial profiles of wood properties for six tree species of the boreal forest of eastern Canada. Partial least squares regressions were performed using individual spectra, collected every 5 mm, from the pith to the bark, using 1,538 samples previously scanned by SilviScan to provide reference data. Results obtained for density (r2 of 0.57 to 0.65; SE of 21 to 33 kg/m3), microfibril angle (0.56 to 0.82, 2.3 to 4.8°) and modulus of elasticity (0.71 to 0.85, 1.3 to 1.8 GPa) were suitable for the purpose of this study. This method was then applied to more than 30,000 tree cores and the resulting radial profiles of the properties were consistent with literature. Area-weighted average predictions also gave reliable estimates at the disk scale. NIR-estimated values were strongly correlated to the measured density (r of 0.83 to 0.93) and mo...