The aim of this work is to demonstrate that Fourier transform near infrared spectroscopy, with multivariate data analysis, can be used to distinguish between preservative treated wood and non-treated wood. This technique is quick, easy to use and has the potential to be non-destructive and portable. For this research, a set of calibration models for the elements boron, chromium, copper and cadmium and the organic preservative cypermethrin have been created using principal component analysis and soft independent modelling of class analogy. The actual metal contamination levels in the wood samples were determined by induction coupled plasma-atomic emission spectroscopy. It is shown that these models can be used to classify samples of wood on the basis of the presence of these chemical substances.
Anonymous. 2003. Guide de gestion des déchets de bois et assimilés en France. CTBA, collection, FCBA Paris, France.
2.
BarnesRJ, DhanoaMS, ListerSJ. 1999. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra.Appl. Spectrosc. 43(5): 772–777.
3.
Bellon-MaurelV, McBratneyA. 2011. Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – critical review and research perspectives.Soil Biol. Biochem. 43(7): 1398–1410.
4.
BlassinoM, Solo-GabrieleH, TownsendT. 2002. Pilot scale evaluation of sorting technologies for CCA treated wood waste.Waste Manag. Res. 20: 290.
5.
BouslamtiA, IrleM, BelloncleC, SalvadorV, CaronB, QannariEM. 2011. Classification of wood materials using Fourier Transform Near Infrared Spectroscopy and multivariate analysis. Christchurch: International Research Group on Wood Protection.
6.
FFB/ADEME. 1999. C&D waste: availability in France. Paris: FFB/ADEME.
7.
ChenleiL, HanshengW. 2009. On general adaptive sparse principal component analysis.J. Comput. Graph. Stat. 18(1): 201–215.
8.
Chi-LeungS, LebowST, GroomLH, RailsTG. 2003. The application of near infrared (NIR) spectroscopy to inorganic preservative-treated wood.Wood Fiber Sci.36(3): 329–336.
EN 71-3/A. 2003. Safety of toys – Part 3: Migration of certain elements. London: British Standards Institute.
11.
EPF. 2001. The use of recycled wood for wood-based panels. European Panels Federation Position Paper, Brussels: European Panels Federation.
12.
FeldhoffR, Huth-FehreT, CammannK. 1998. Detection of inorganic wood preservatives on timber by near infrared spectroscopy.Near Infrared Spectrosc.6: 171–173.
13.
GeladiP, MacDougalD, MartensH. 1989. Linearization and scatter correction for near-infrared reflectance spectra of meat.Appl. Spectrosc. 39(3): 491–500.
14.
TripathiMM, El BarbaryHM, YuehF-Y, JagdishSP, SteelePH, IngramL L2009. Reflection–absorption-based near infrared spectroscopy for predicting water content in bio-oil. Sens.Actuators B. 136(1/2): 20–25.
15.
MehrotraR, SinghP, KandpalH. 2010. Infrared spectroscopic investigation of the thermal degradation of wood.Thermochim. Acta. 507: 60–65.
16.
MerlA, HumarM, OkstadT, PicardoV, SteiererF, RibeA. 2007. Amounts of recovered wood in COST E31 countries and Europe. Proc. 3rd Eur. COST E31Conf. on ‘Management of recovered wood’. Klagenfurt, Austria. Pages 79–116.
RuneFG, GrungB, KvalheimOM. 2004. A method for validation of reference sets in SIMCA modelling.Chemometr. Intellig. Lab. Syst. 72: 101–109.
19.
SandakA, SandakJ, ZborowskaM, PraądzyńskiW. 2010. Near infrared spectroscopy as a tool for archaeological wood characterization.J. Archaeol. Sci. 37: 2093.
20.
SavitskyA, GolayMJE. 1964. Smoothing and differentiation of data by simplified least squares procedures.Anal. Chem. 36: 1627–1639.
21.
SmidtE, MeisslK, SchwanningerM, LechnerP. 2007. Classification of waste materials using Fourier transform infrared spectroscopy and soft independent modeling of class analogy.Waste Manag.28: 1699–1710.
22.
Solo-GabrieleHM, TownsendT, HahnD, MoskalT, HoseinN, JambeckJ, JacobiG. 2004. Evaluation of XRF and LIBS technologies for on-line sorting of CCA-treated wood waste.Waste Manag. Res. 24: 413–424.
23.
American Wood Preservation Association. 2010. Standard for wet ashing procedures for preparring wood for chemical analysis. Birmingham: American Wood Preservation Association.
24.
TaylorA, LloydJ. 2007. Potential of near infrared spectroscopy to quantify boron concentration in treated wood.Forest Prod. J. 57(1/2): 116–117.
25.
UhlA, LoebeK, KreuchwigL. 2001. Fast analysis of wood preservers using laser induced breakdown spectroscopy.Spectrochim. Acta. 56(6): 795–806.
26.
WoldS, SjostromM. 1977. SIMCA: a method for analysing chemical data in terms of similarity and analogy. ACS Symposium Series 52.
