Elucidating the Effect of Geolocation on Species Identification of Timber with Handheld Laser Induced Breakdown Spectroscopy

Monday, October 6, 2025

5:10 PM - 5:30 PM EDT

Location: Meeting Room #7

Presenting Author(s)

CC

Caelin Celani, PhD (he/him/his)

Postdoctoral Fellow
University of Delaware
Claymont, Delaware, United States

Non-Presenting Author(s)

EM

Erin McClure-Price

US Forest Service International Programs Wood Identification and Screening Center
Ashland, Oregon, United States
HC

Helder V. Carneiro

PhD Candidate
University of Delaware
Newark, Delaware, United States
FD

Fernanda F. Delgado

Chair
University of Delaware
Newark, Delaware, United States
KC

Kierra Cano

United States Forestry Service Wood Identification and Screening Center
Ashland, Oregon, United States
MK

Michael E. Ketterer, PhD

Professor Emeritus
Northern Arizona University
Flagstaff, Arizona, United States
CL

Cady Lancaster

United States Forestry Service
Ashland, Oregon, United States
EE

Edgard Espinoza

National Fish & Wildlife Forensic Laboratory, US Fish and Wildlife
Ashland, Oregon, United States
JJ

James Jordan

United States Geological Survey
Reston, Virginia, United States
TC

Ty Coplen

United States Geological Survey
Reston, Virginia, United States
KE

Kent Elliott

US Forest Service International Programs Wood Identification and Screening Center
Ashland, Oregon, United States

Project Lead(s)

KB

Karl S. Booksh, PhD

Professor
University of Delaware
Newark, Delaware, United States

Submitter(s)

CC

Caelin Celani, PhD (he/him/his)

Postdoctoral Fellow
University of Delaware
Claymont, Delaware, United States

In fifteen words or less, explain the significance of this contribution (Novel Aspect).: Using multivariate analysis, both timber species and geolocation can be identified at ports of entry.

Abstract Text:

Laser-induced breakdown spectroscopy (LIBS) combines a simple optical train, rapid analysis, and minimal sample preparation, making it attractive for field-based applications. One pressing need is the forensic identification of illegally traded timbers at ports of entry to enforce international regulations such as the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Coupled with chemometric analysis, LIBS enables accurate classification of both timber species and geographic origin. This presentation will trace the development of handheld LIBS for this application, beginning with proof-of-concept studies using partial least squares discriminant analysis (PLS-DA) for species-level identification. Subsequent work evaluated sampling strategies and modeling approaches to improve species and geolocation classification. Results include the differentiation of identical timber species sourced only 11 km apart, achieved using PLS regression and support vector machine discriminant analysis (SVM-DA). Together, these studies demonstrate that handheld LIBS, when paired with multivariate models, provides a practical, field-deployable tool for rapid timber identification and provenance determination, with measurement speed and reliability comparable to laboratory-based techniques such as ICP-MS.