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<p>Illegal logging poses a significant threat to ecosystems and undermines legal timber markets. Efforts to combat the issue are often hindered by the lack of robust tools for species-level wood authentication. Traditional methods such as anatomical observations and DNA analysis frequently struggle to achieve accurate species-level identification. Chemical profiling of wood metabolites has emerged as a promising alternative. Two powerful techniques, Direct Analysis in Real Time Time-of-Flight Mass Spectrometry (DART-TOFMS) and Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry (GC×GC-TOFMS) offer unique strengths for wood identification. DART-TOFMS enables rapid chemical analysis with minimal sample preparation. GC×GC-TOFMS, known for its exceptional separation capabilities, allows for detailed chemical profiling that may enhance species-level discrimination. Despite their potential, direct comparisons of these two techniques for species-level classification have not been done yet. In this study, we present a comparative analysis using 60 wood core samples from two <i>Quercus</i> (Oak) species and 60 stemwood samples from three <i>Picea</i> (Spruce) species. Each sample was analyzed using both DART-TOFMS and GC×GC-TOFMS. Partial Least Squares Discriminant Analysis (PLS-DA) was employed for classification modeling, with feature selection based on VIP scores. Our results show that both techniques demonstrated strong classification performance in differentiating both <i>Quercus</i> and <i>Picea</i> species. Notably, GC×GC-TOFMS yielded slightly higher classification accuracy in this study, which may be attributed to its enhanced separation capabilities and ability to resolve structurally similar compounds such as isomers. The findings from this work will contribute to a deeper understanding of the capabilities of both techniques in wood metabolomics, with applications in forensic science and efforts to combat illegal logging.</p>

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Assessing analytical techniques for wood metabolomics through a comparison of DART-TOFMS and GC×GC-TOFMS for species-level wood identification

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Seo Lin Nam,
  • Erin R. Price,
  • Martin Williams,
  • Isabelle Duchesne,
  • Nathalie Isabel,
  • James J. Harynuk

摘要

Illegal logging poses a significant threat to ecosystems and undermines legal timber markets. Efforts to combat the issue are often hindered by the lack of robust tools for species-level wood authentication. Traditional methods such as anatomical observations and DNA analysis frequently struggle to achieve accurate species-level identification. Chemical profiling of wood metabolites has emerged as a promising alternative. Two powerful techniques, Direct Analysis in Real Time Time-of-Flight Mass Spectrometry (DART-TOFMS) and Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry (GC×GC-TOFMS) offer unique strengths for wood identification. DART-TOFMS enables rapid chemical analysis with minimal sample preparation. GC×GC-TOFMS, known for its exceptional separation capabilities, allows for detailed chemical profiling that may enhance species-level discrimination. Despite their potential, direct comparisons of these two techniques for species-level classification have not been done yet. In this study, we present a comparative analysis using 60 wood core samples from two Quercus (Oak) species and 60 stemwood samples from three Picea (Spruce) species. Each sample was analyzed using both DART-TOFMS and GC×GC-TOFMS. Partial Least Squares Discriminant Analysis (PLS-DA) was employed for classification modeling, with feature selection based on VIP scores. Our results show that both techniques demonstrated strong classification performance in differentiating both Quercus and Picea species. Notably, GC×GC-TOFMS yielded slightly higher classification accuracy in this study, which may be attributed to its enhanced separation capabilities and ability to resolve structurally similar compounds such as isomers. The findings from this work will contribute to a deeper understanding of the capabilities of both techniques in wood metabolomics, with applications in forensic science and efforts to combat illegal logging.