Detection of Endangered Species Using the Agilent Resolve Raman Analyzer

Importance of the Topic

Illicit trade in endangered species is valued at over 7.8 billion USD and threatens biodiversity, depletes wild populations, and fuels organized crime networks. Rapid, reliable identification of animal-derived products at ports of entry and in the field is essential to enforce wildlife protection laws and preserve vulnerable ecosystems.

Study Objectives and Overview

This application note evaluates the Agilent Resolve handheld Raman analyzer, incorporating spatially offset Raman spectroscopy (SORS), for on-site detection of concealed endangered species products. Key aims include:

• Demonstrate detection of ivory beneath paint or varnish layers.
• Differentiate genuine ivory and bone from synthetic substitutes.
• Categorize confiscated animal parts into mineral-based and protein-based groups.
• Apply principal components analysis (PCA) to resolve closely related protein-derived samples.

Used Instrumentation

• Agilent Resolve handheld Raman analyzer with proprietary SORS functionality.
• On-board Standard spectral library for common chemicals and materials.
• Agilent Command Fleet Management Software for custom library creation.
• Principal components analysis software module for multivariate spectral interpretation.

Methodology

Samples comprising ivory, bone, animal scales, horns, dried seahorse, and fish bladders were measured in two modes: conventional surface Raman and through-barrier SORS. The Standard on-board library provided reference spectra, while SORS minimized interference from paints and coatings. Spectra were grouped by chemical composition into mineral-based (hydroxyapatite) and protein-based (keratin/amides) classes. PCA was then employed to highlight subtle spectral variations among protein-based products.

Main Results and Discussion

• SORS successfully revealed ivory signatures hidden under colored paints and varnishes, enabling through-barrier identification.
• Surface Raman differentiated real ivory and bone from plastic tusk substitutes with distinct spectral features.
• Mineral-based materials (ivory, bone, teeth, armadillo scale) shared hydroxyapatite spectra and required complementary methods for fine discrimination.
• PCA of protein-based samples (rhino horn, pangolin scale, seahorse, totoaba bladder) produced clear clustering, demonstrating reliable subclass separation.

Benefits and Practical Applications

• Rapid field analysis: results delivered within two minutes without sample preparation or consumables.
• High portability: handheld design allows deployment at customs checkpoints, wildlife markets, and remote enforcement sites.
• Custom library creation: users can expand detection capability for emerging illicit wildlife products.
• Noninvasive and nondestructive testing preserves evidence integrity.

Future Trends and Potential Applications

Integration of expanded spectral libraries and advanced machine-learning algorithms could enhance automated classification of wildlife products. Miniaturization and connectivity improvements may facilitate cloud-based spectral matching and real-time data sharing among enforcement agencies. Emerging SORS adaptations could also address new concealment strategies and complex matrices.

Conclusion

The Agilent Resolve handheld Raman analyzer, coupled with SORS and PCA, provides a robust, rapid, and field-deployable solution for identifying concealed endangered species materials. Its ability to distinguish authentic animal-derived products from synthetic imitations and to classify complex protein-based samples underscores its value in wildlife law enforcement and conservation efforts.

References

1. U.S. Immigration and Customs Enforcement (ICE), End Wildlife Trafficking, August 22, 2023.
2. Customs Outwits Contraband Goods by Air, Advanced Instruments Pull Out Tiger Teeth, Singtao, September 12, 2021.
3. Hargreaves M.; MacLeod N.; Brewster V.; Munshi T.; Edwards H.; Matousek P. Application of Portable Raman and Benchtop SORS to Concealed Biomaterials, J. Raman Spectrosc., 2009.
4. Movasaghi Z.; Rehman S.; Rehman I. Raman Spectroscopy of Biological Tissues, Appl. Spectrosc. Rev., 2007, 42.