Near infrared spectroscopy (NIRS) as a potential tool for monitoring trade of similar woods: Discrimination of true mahogany, cedar, andiroba, and curupixá

Abstract

Mahogany is one of the most valuable woods and was widely used until it was included in Appendix II of the Convention on International Trade in Endangered Species as endangered species. Mahogany wood sometimes is traded under different names. Also, some similar woods belonging to the Meliaceae family are traded as “mahogany” or as being of a “mahogany pattern”. To investigate the feasibility of the use of near infrared spectroscopy for wood discrimination, the mahogany (Swietenia macrophylla King.), andiroba or crabwood (Carapa guianensis Aubl.), cedar (Cedrela odorata L.), and curupixá (Micropholis melinoniana Pierre) woods were examined. Four discrimination models based on partial least squares-discriminant analysis were developed based on a calibration set composed of 88 samples and a test set with 44 samples. Each model corresponds to the discrimination of a wood species from the others. Optimization of the model was performed by means of the OPUS® software followed by statistical analysis software (Matlab®). The observed root mean square errors of predictions were 0.14, 0.09, 0.12, and 0.06 for discriminations of mahogany, cedar, andiroba, and curupixá, respectively. The separations of the species obtained based on the difference in the predicted values was at least 0.38. This makes it possible to perform safe discriminations with a very low probability of misclassifying a sample. This method can be considered accurate and fast.

Rapid Detection of Knot Defects on Wood Surface by Near Infrared Spectroscopy Coupled with Partial Least Squares Discriminant Analysis

“…As a nondestructive detection technology, near-infrared (NIR) spectroscopy coupled with discriminant analysis is an effective tool with several uses: to discriminate blue-stained wood (Via et al 2008), to classify the type of fungal decay in wood (Fackler et al 2007;Yang et al 2008), to identify the type of preservatives in wood (So et al 2004), and to identify the wood species (Schimleck et al 1996;Tsuchikawa et al 2003;Pastore et al 2011). In many discriminant analysis methods, partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) have been the most common methods used to analyze the data of NIR spectroscopy.…”

Near-infrared spectroscopy as a potential quality assurance tool for the wood preservation industry

“…NIRS-based methods have been developed to measure a wide range of wood characteristics (Tsuchikawa 2007). It has been used to estimate extent of decay (Fackler et al 2007, Stirling et al 2007) and durability (Flaete andHaartveit 2004, Gierlinger et al 2004), and to differentiate wood species (Tsuchikawa et al 2003, Pastore et al 2011 and treated wood waste (Feldhoff et al 1998, So et al 2004. Models have been developed to measure linseed oil uptake (Eriksson et al 2011), retention of borate and coppercontaining preservatives (So et al 2007, Taylor andLloyd 2007), and to differentiate untreated wood and wood treated with CBP formulations containing 3-iodo-2-propynyl butylcarbamate (IPBC)/cypermethrin, IPBC/propiconazole, and permethrin, propiconazole, and tebuconazole (Zahri et al 2008).…”

Identification of Pinus species related to historic architecture in Korea using NIR chemometric approaches

“…Antti et al [10] determined that a PLS model could be used to distinguish individual species from mixed wood chips including Swedish pine, Swedish spruce, and Polish pine. Pastore et al [11] discriminated true mahogany from similar species using PLS-DA, Horikawa et al [12] used NIR spectroscopy in combination with multivariate analysis to distinguish between P. densiflora and P. thunbergii, and Hwang et al [13] also reported that the identification of P. densiflora and P. densiflora for. erecta could be possible using chemometric approaches.…”