Assessing utility of handheld laser induced breakdown spectroscopy as a means of Dalbergia speciation.

Many species of Dalbergia are prized hardwoods, generally referred to as 'Rosewood,' and used in high-end products due to their distinctive hue and scent. Despite more than 58 species of Dalbergia being listed as endangered in Appendix 1 of The Convention on International Trade in Endangered Species of Fauna and Flora (CITES), the illegal logging and trade of this timber is ongoing. In this work, a handheld laser induced breakdown spectrometer (LIBS) was used to analyze seven Dalbergia species and two other exotic hardwood species to evaluate the ability of handheld LIBS for rapid classification of Dalbergia in the field. The KNN model of the classification presented 80% to 90% sensitivity for discriminating between Dalbergia species in the training set. PLS-DA models were based on a binary decision tree structure. Cumulatively, the PLS-DA decision tree model showed greater than 97% sensitivity and 99% selectivity for prediction of Dalbergia species included in the training set. The data presented in the following study are promising for the use of handheld LIBS devices and both KNN and PLS-DA models for applications in customs screenings at the port of entry of hard woods, among others.

Distinguishing wild from cultivated agarwood (Aquilaria spp.) using direct analysis in real time and time of-flight mass spectrometry.

RATIONALE: It is important for the enforcement of the CITES treaty to determine whether agarwood (a resinous wood produced in Aquilaria and Gyrinops species) seen in trade is from a plantation that was cultivated for sustainable production or was harvested from natural forests which is usually done illegally. METHODS: We analyzed wood directly using Direct Analysis in Real Time (DART™) ionization coupled with Time-of-Flight Mass Spectrometry (TOFMS). Agarwood was obtained from five countries, and the collection contained over 150 samples. The spectra contained ions from agarwood-specific 5,6,7,8-tetrahydro-2-(2-phenylethyl)chromones as well as many other ions. The data was analyzed using either kernel discriminant analysis or kernel principal component analysis. Probability estimates of origin (wild vs cultivated) were assigned to unknown agarwood samples. RESULTS: Analysis of the DART-TOFMS data shows that many of the chromones found in cultivated and wild agarwood samples are similar; however, there is a significant difference in particular chromones that can be used for differentiation. In certain instances, the analysis of these chromones also allows inferences to be made as to the country of origin. Mass Mountaineer™ software provides an estimate of the accuracy of the discriminate model, and an unknown sample can be classified as cultivated or wild. Eleven of the thirteen validation samples (85%) were correctly assigned to either cultivated or wild harvested for their respective geographic provenance. The accuracy of each classification can be estimated by probabilities based on Z scores. CONCLUSIONS: The direct analysis of wood for the diagnostic chromones using DART-TOFMS followed by discriminant analysis is sufficiently robust to differentiate wild from cultivated agarwood and provides strong inference for the origin of the agarwood.

Evaluating agarwood products for 2-(2-phenylethyl)chromones using direct analysis in real time time-of-flight mass spectrometry.

RATIONALE: Agarwood is the resinous material harvested from threatened Aquilaria species. We investigated how many protonated 2-(2-phenylethyl)chromone ions were sufficient to make an accurate identification of agarwood. Analysis of 125 reference samples was carried out by direct analysis in real time time-of-flight mass spectrometry (DART-TOFMS). The identification criteria developed were applied to commercial samples. METHODS: We developed a technique that uses DART-TOFMS to detect 2-(2-phenylethyl)chromones. Additionally, we developed a set of criteria to infer the presence of Aquilaria in commercial samples of wood chips, sawdust, incense and liquids. Additionally, we examined other fragrant woods to determine if they contained a chemical profile that could be falsely identified as agarwood. RESULTS: Analysis of reference and commercial samples (n = 151) established that DART-TOFMS provides reproducible mass spectra that are useful for inferring the genus of suspected agarwood samples. We identified 17 ions which were useful for authenticating agarwood. Comparison of the number of chromone ions detected by direct analyses of dry wood chips versus eluent analysis of methanol-extracted wood showed that results were similar. Lastly, analysis of 25 scented woods of other species did not give false positive results. CONCLUSIONS: Reliable criteria for inferring agarwood include the presence of diagnostic ions, m/z 319.118 or 349.129, in addition to ten or more ions characteristic of 2-(2-phenylethyl)chromones. Wood anatomists challenged with difficult morphological identifications can use this tool to assist in their analyses. Published 2012. This article is a US Government work and is in the public domain in the USA.

Analysis of select Dalbergia and trade timber using direct analysis in real time and time-of-flight mass spectrometry for CITES enforcement.

RATIONALE: International trade of several Dalbergia wood species is regulated by The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). In order to supplement morphological identification of these species, a rapid chemical method of analysis was developed. METHODS: Using Direct Analysis in Real Time (DART) ionization coupled with Time-of-Flight (TOF) Mass Spectrometry (MS), selected Dalbergia and common trade species were analyzed. Each of the 13 wood species was classified using principal component analysis and linear discriminant analysis (LDA). These statistical data clusters served as reliable anchors for species identification of unknowns. RESULTS: Analysis of 20 or more samples from the 13 species studied in this research indicates that the DART-TOFMS results are reproducible. Statistical analysis of the most abundant ions gave good classifications that were useful for identifying unknown wood samples. CONCLUSIONS: DART-TOFMS and LDA analysis of 13 species of selected timber samples and the statistical classification allowed for the correct assignment of unknown wood samples. This method is rapid and can be useful when anatomical identification is difficult but needed in order to support CITES enforcement. Published 2012. This article is a US Government work and is in the public domain in the USA.