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AOBPreview published online on November 2, 2009
Annals of Botany, doi:10.1093/aob/mcp270
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© The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Wood identification of Dalbergia nigra (CITES Appendix I) using quantitative wood anatomy, principal components analysis and naïve Bayes classification

Peter Gasson1,*, Regis Miller2, Dov J. Stekel3, Frances Whinder1 and Kasia Zieminska1

1 Jodrell Laboratory, Royal Botanic Gardens Kew, Kew Road, Richmond, Surrey TW9 3DS, UK
2 Forest Products Laboratory, One Gifford Pinchot Drive, Madison, WI 53726-2398, USA
3 School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leics LE12 5RD, UK

* For correspondence. E-mail P.Gasson{at}kew.org

Received: 17 August 2009    Returned for revision: 14 September 2009    Accepted: 5 October 2009   

Background and Aims: Dalbergia nigra is one of the most valuable timber species of its genus, having been traded for over 300 years. Due to over-exploitation it is facing extinction and trade has been banned under CITES Appendix I since 1992. Current methods, primarily comparative wood anatomy, are inadequate for conclusive species identification. This study aims to find a set of anatomical characters that distinguish the wood of D. nigra from other commercially important species of Dalbergia from Latin America.

Methods: Qualitative and quantitative wood anatomy, principal components analysis and naïve Bayes classification were conducted on 43 specimens of Dalbergia, eight D. nigra and 35 from six other Latin American species.

Key Results: Dalbergia cearensis and D. miscolobium can be distinguished from D. nigra on the basis of vessel frequency for the former, and ray frequency for the latter. Principal components analysis was unable to provide any further basis for separating the species. Naïve Bayes classification using the four characters: minimum vessel diameter; frequency of solitary vessels; mean ray width; and frequency of axially fused rays, classified all eight D. nigra correctly with no false negatives, but there was a false positive rate of 36·36 %.

Conclusions: Wood anatomy alone cannot distinguish D. nigra from all other commercially important Dalbergia species likely to be encountered by customs officials, but can be used to reduce the number of specimens that would need further study.

Key words: Dalbergia nigra, Brazilian rosewood, CITES, wood anatomy, PCA, naïve Bayes analysis


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