Chemical Fingerprinting of Wood Sampled along a Pith-to-Bark Gradient for Individual Comparison and Provenance Identification

Interlaboratory and cross-platform accessibility of time-of-flight wood identification database

The mass spectral database of tree species built by US Fish and Wildlife Service has thousands of entries and has been a valuable resource to combat illegal logging and international trade. The database was and continues to be constructed using a particular ambient ionization time-of-flight mass spectrometry (TOF-MS) platform in the agency branch in Ashland, OR, with which queries of unknown wood samples are investigated exclusively. Laboratories that operate different MS instruments also have an interest in using the database if they can produce valid matches to known samples compatible with the database. Four species were selected for inter-laboratory comparison using Orbitrap MS instruments and the equivalent TOF-MS platform with direct analysis in real time ionization of institution-sourced wood samples. Identities of the known samples were confirmed by examination of their microscopic wood anatomy. Orbitrap analysis was able to identify each species as confidently as the TOF instruments, often with less variation in spectra but not necessarily greater mass accuracy or better-matched signal abundance to the control database. The Orbitrap program also had to be doubled to two scanned mass ranges appended for greater peak intensity, before spectra could be correctly matched to the database, but the program was successful.

Non-destructive wood identification using X-ray µCT scanning: which resolution do we need?

BACKGROUND

Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1 µm, 3 µm, 8 µm and 15 µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features.

RESULTS

For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1 µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3 µm, the scans at 1 µm and 8 µm were successful in more than half of the studied cases, and even the 15 µm resolution showed a high potential for 40% of the samples.

CONCLUSIONS

The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species.

Retrieving complete plastid genomes of endangered Guibourtia timber using hybridization capture for forensic identification and phylogenetic analysis

The high economic value and increased demand for timber have led to illegal logging and overexploitation, threatening wild populations. In this context, there is an urgent need to develop effective and accurate forensic tools for identifying endangered Guibourtia timber species to protect forest ecosystem resources and regulate their trade. In this study, a hybridization capture method was developed and applied to explore the feasibility of retrieving complete plastid genomes from Guibourtia sapwood and heartwood specimens stored in a xylarium (wood collection). We then carried out forensic identification and phylogenetic analyses of Guibourtia within the subfamily Detarioideae. This study is the first to successfully retrieve high-quality plastid genomes from xylarium specimens, with 76.95-99.97% coverage. The enrichment efficiency, sequence depth, and coverage of plastid genomes from sapwood were 16.73 times, 70.47 times and 1.14 times higher, respectively, than those from heartwood. Although the DNA capture efficiency of heartwood was lower than that of sapwood, the hybridization capture method used in this study is still suitable for heartwood DNA analysis. Based on the complete plastid genome, we identified six endangered or commonly traded Guibourtia woods at the species level. This technique also has the potential for geographical traceability, especially for Guibourtia demeusei and Guibourtia ehie. Meanwhile, Bayesian phylogenetic analysis suggested that these six Guibourtia species diverged from closely related species within the subfamily Detarioideae ca. 18 Ma during the Miocene. The DNA reference database established based on the xylarium specimens provides admissible evidence for diversity conservation and evolutionary analyses of endangered Guibourtia species.

Clay and soil organic matter drive wood multi-elemental composition of a tropical tree species: Implications for timber tracing

Forensic methods to independently trace timber origin are essential to combat illegal timber trade. Tracing product origin by analysing their multi-element composition has been successfully applied in several commodities, but its potential for timber is not yet known. To evaluate this potential the drivers of wood multi-elemental composition need to be studied. Here we report on the first study relating wood multi-elemental composition of forest trees to soil chemical and physical properties. We studied the reactive soil element pools and the multi-elemental composition in sapwood and heartwood for 37 Azobé (Lophira alata) trees at two forest sites in Cameroon. A total of 46 elements were measured using ICP-MS. We also measured three potential drivers of soil and wood elemental composition: clay content, soil organic matter and pH. We tested associations between soil and wood using multiple regressions and multivariate analyses (Mantel test, db-RDA). Finally, we performed a Random Forest analysis of heartwood elemental composition to check site assignment accuracy. We found elemental compositions of soil, sapwood and heartwood to be significantly associated. Soil clay content and organic matter positively influenced individual element concentrations (for 13 and 9 elements out of 46 respectively) as well as the multi-elemental composition in wood. However, associations between wood and topsoil elemental concentrations were only significant for one element. We found close associations between element concentrations and composition in sapwood and heartwood. Lastly, the Random Forest assignment success was 97.3 %. Our findings indicate that wood elemental composition is associated with that in the topsoil and its variation is related to soil clay and organic matter content. These associations suggests that the multi-elemental composition of wood can yield chemical fingerprints obtained from sites that differ in soil properties. This finding in addition to the high assignment accuracy shows potential of multi-element analysis for tracing wood origin.

Rapid identification of wood species using XRF and neural network machine learning

An innovative approach for the rapid identification of wood species is presented. By combining X-ray fluorescence spectrometry with convolutional neural network machine learning, 48 different wood specimens were clearly differentiated and identified with a 99% accuracy. Wood species identification is imperative to assess illegally logged and transported lumber. Alternative options for identification can be time consuming and require some level of sampling. This non-invasive technique offers a viable, cost-effective alternative to rapidly and accurately identify timber in efforts to support environmental protection laws and regulations.

Wood profiling by non-targeted high-resolution mass spectrometry: Part 1, Metabolite profiling in Cedrela wood for the determination of the geographical origin

The determination of the geographical origin of wood can be highly relevant for several reasons: On the one hand, it can help to prevent illegal logging and timber trade, on the other hand, it is of special interest for archaeological artefacts made of wood, as well as for a variety of biological questions. For this reason, different extraction methods were first tested for the analysis of polar and non-polar metabolites using liquid chromatography coupled electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). A two-phase extraction with chloroform, methanol and water proved to be particularly successful. Subsequently, cedrela (Cedrela odorata) samples from South America were measured to distinguish geographic origin. Using multivariate data analysis, numerous origin-dependent differences could be extracted. The identification of the marker substances indicated that several metabolic pathways were affected by the geographical influences, some of them probably indicating pest infections.