BOLZON DE MUÑIZ, G. I.

BRAGA, J. W. B.

BRESSAN, O. A.

CAMARGOS, J. A. A.

CORADIN, V. T. R.

DAVRIEUX, F.

MAGALHAES, W. L. E.

OKINO, E. Y. A.

PASTORE, T. C. M.

English

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XIII Congreso Forestal Mundial Buenos Aires, Argentina,18-23 Octubre 2009Titulo: NIRS A POTENTIAL TOOL FOR MONITORINGHARVESTING AND TRADE OFSIMILAR WOODS. A CASE STUDY FOR DISCRIMINATIONOF MAHOGANY, CEDAR,AND CRABWOOD.Autores: Pastore, Tereza C. M.; Braga, Jez W. B.; Coradin,Vera T. R.: Magalhaes, Washington L.E.; Okino, Esmeralda Y. A.; Camargos, José A. A.; Mufiiz,Graciela I. B. De; Davrieux, Fabrice:Bressan, Otdvio A.Tema: 5. Oportunidades de DesarrolloSubtema: 5.4 Comercio de productos forestalesResumen: Mahogany is one of the most valuable woodsand was widely used until 2003, when itwas included in Appendix II of CITES endangered species.As a consequence, in Brazil, sometimesmahogany is traded under different names or somesimilar woods belonging to the Meliaceae familywhich are traded as “mahogany”or as being of a “mahogany pattern”.In order to investigate thefeasibility of a tool for wood instrumental identification, themahogany (Swietenia macrophyllaKing.), crabwood or andiroba (Carapa guianensisAubl.), and cedar (Cedrela odorata L.) woods, inmill form were submitted to Near Infrared Spectroscopy (NIRS)and chemometric analyses bypartial least squares discriminant analysis (PLS-DA).The discrimination model was developedbased on 81 calibration samples (24, 21 and 36 for mahogany,cedar and andiroba, respectively) and28 validation samples (9, 7 and 12 for mahogany, cedarand andiroba, respectively). Optimization ofthe most appropriate wavelength regions and preprocessingmethods was performed using theOPUS® software package followed by posterior statistical analysisusing Matlab®. Thediscriminations were performed with a single PLS-DA modelwith three dependent variables (y).each one corresponding to the discrimination of a woodclass (where the value of y was set as 1)from the others (y=0). The observed root mean square errorsof predictions (RMSEP), estimatedwith the validation samples, were 0.12, 0.11 and 0.10 fordiscriminations of mahogany, cedar andandiroba, respectively, and the separations of the classesobtained with a difference in the predictedvalues of at least 0.45. Therefore, a large separation betweenthe classes was obtained comparedwith the error of the model, showing that the application ofNIR and PLS-DA is able to perform asafe discrimination of these three woods. The results showedthat with this degree of separation andlow prediction errors the probability of misclassify a sampleis very low. The results alsodemonstrate the importance of research in this area. Thecontributions to the development of newmethodologies for qualitative and quantitative analysis lead tobetter accuracy, faster and non-destructive methods. Equipping those involved in forest managementwill lead to improvements intraffic control and trading activities using a non-subjectivediscrimination tool.Email: tereza.pastore @ gmail.com, jez@unb.br, vera.coradin@florestal.gov.br,wlmagalh@ncsu.edu, esmeralda.okino @florestal.gov.br,Jose.camargos @florestal.gov.br,gbmunize @ufpr.br, davrieux @cirad.fr, fiodagansa@hotmail.com

NIRS a potential tool for monitoring harvesting and trade of similar woods: a case study for discrimination of mahogany, cedar, and crabwood.

http://www.alice.cnptia.embrapa.br/bitstream/doc/574280/1/SP-5443.pdf

NIRS a potential tool for monitoring harvesting and trade of similar woods: a case study for discrimination of mahogany, cedar, and crabwood.

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