Preliminary Study of Wood Species Identification by Nir Spectroscopy (original) (raw)
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J Indian Acad Wood Sci, 2014
Research on wood technological properties using near infrared (NIR) spectroscopy has shown promising results. The aim of this study was to evaluate the efficiency of NIR spectroscopy for estimating chemical properties of mangium wood (Acacia mangium). NIR spectra were obtained from 150 wood meal samples of mangium trees that were 5–7-years-old. A multivariate data analysis method of partial least squares was used to develop calibration regression models for predicting chemical properties based on NIR spectra. The results showed a good relationship between values derived from laboratory analyses and those predicted by NIR spectroscopy for a-cellulose and hemicellulose content. The calibration models had high values for the coefficient of determination (R2[0.80) and the ratio of performance to deviation (RPD[2.0). Meanwhile, lignin and extractive content were poorly predicted; calibration validation revealed R2\0.60 and RPD = 1.0. This study indicated that NIR spectroscopy analysis on wood meal of A. mangium could be reliably used to predict a-cellulose and hemicellulose.
Wood species identification by near-infrared spectroscopy
International Wood Products Journal, 2016
An optimum artificial neural network and a partial least square with discriminant analysis regression were developed and tested for accuracy in distinguishing two wood species by using near-infrared (NIR) spectrum. A mixed population of kiln-dried wood boards of western hemlock (Tsuga heterophylla (Raf.) Sarg.) and amabilis fir (Abies amabilis (Dougl.) Forbes) were scanned by NIR and then a random subset was water saturated under vacuum conditions and scanned again. This design aimed to capture the effect of moisture content above the fibre saturation point on the separation algorithms. Our results revealed that both modelling techniques can be effective tools for species recognition achieving correct identification of over 86% for fir and 94% for hemlock on either kiln-dried or fully saturated boards.
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 ...
Quality assessment of heat-treated wood by NIR spectroscopy
Holz als Roh- und Werkstoff, 2008
NIR spectroscopy was tested for predicting the properties of heat treated wood using pine (Pinus pinaster) and eucalypt (Eucalyptus globulus) woods with two types of treatment: in oven and in a steam autoclave. Mass loss, equilibrium moisture content, dimensional stability, MOE, bending strength, colour CIELAB parameters and extractives content were determined. NIR spectra were obtained using a fibre probe on the radial surface of the samples. NIR models for mass loss showed very high coefficients of determination (R 2) for cross validation ranging from 96-98%. The models obtained for wood properties were in general good with coefficients of determination ranging from 78-95% for equilibrium moisture content, 53-78% for dimensional stability, 47-89% for MOE, 75-77% for bending strength and 84-99%, 52-96% and 66-98% for colour parameters L, a * and b * , respectively. R 2 of the models for extractive content varied between 41.9-79.8% for pine and between 35.3-82.2% for eucalypt wood. NIR spectroscopy showed a good potential for quality control and characterization of heat treated woods.
Energy & Fuels, 2017
The pellet energy market is expanding rapidly in Europe and also at the global level, in response to the continuously growing energy demand and because of the high degree of reliability, the easy handling, and the cheap and simple logistics, in comparison to other solid biomasses. The fast growth of this market has highlighted the problem of product quality, which has strong repercussions for technical, environmental, and economic aspects. The biomass quality is defined by several chemical−physical parameters that are directly measurable in the laboratory. In addition, there are quality attributes related to origin and source, difficult to investigate through traditional analyses, such as the type of wood (hardwood/softwood) and the presence of bark. The development of a rapid technique able to provide this information could be an advantageous tool for the energy sector proving indications on biofuel traceability and sustainability. More than 90 samples belonging to three of the most common European species for the energy pellet sector (fir, pine, and beech) have been collected and analyzed by means of Fourier transform near-infrared (FT-NIR) coupled with Principal Component Analysis (PCA). The results show that the main variation in the data is due to both differences between bark and wood, as well as differences between hardwood and softwood. The differences are mainly linked to changes in composition and amounts of cellulose, hemicellulose, lignin, and extractives. Moreover, 30 wood/bark blends (2%−20% (w/w)) were analyzed, indicating the ability of the system to recognize blends from pure material. This study has shown that spectroscopy coupled with multivariate data analysis is a useful tool verifying the compliance of producer declarations and assisting experts in evaluation of the biomass quality.
Maderas. Ciencia y tecnología, 2018
The modification of wood by thermal treatments produces characteristic changes in its chemical composition and surface color and can improve the structural and esthetic quality. The objective of this paper is to evaluate the potential of near infrared and visible spectroscopy to predict the modifications in chemical composition of Eucalyptys grandis and Pinus taeda after thermal treatment. Near infrared and visible spectra were collected directly on the longitudinal surface of wood samples. The thermally modified wood of both species showed higher content of lignin and extractives than the untreated wood. There was darkening of thermally modified wood, as a result of chemical modification caused by heat. The Near infrared/visible technique identified the groups that were modified by treatment. NIR and visible spectroscopy can be used to predict chemical composition of natural or thermally treated Eucalyptus grandis and Pinus taeda.