Wood species identification from Atlantic forest by near infrared spectroscopy

  • José-Henrique Camargo Pace Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.
  • João-Vicente de Figueiredo Latorraca Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.
  • Paulo-Ricardo Gherardi Hein Universidade Federal de Lavras: Lavras, MG.
  • Alexandre Monteiro de Carvalho Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.
  • Jonnys Paz Castro Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.
  • Carlos-Eduardo Silveira da Silva Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.


Aim of study: Fast and reliable wood identification solutions are needed to combat the illegal trade in native woods. In this study, multivariate analysis was applied in near-infrared (NIR) spectra to identify wood of the Atlantic Forest species.

Area of study: Planted forests located in the Vale Natural Reserve in the county of Sooretama (19 ° 01'09 "S 40 ° 05'51" W), Espírito Santo, Brazil.

Material and methods: Three trees of 12 native species from homogeneous plantations. The principal component analysis (PCA) and partial least squares regression by discriminant function (PLS-DA) were performed on the woods spectral signatures.

Main results: The PCA scores allowed to agroup some wood species from their spectra. The percentage of correct classifications generated by the PLS-DA model was 93.2%. In the independent validation, the PLS-DA model correctly classified 91.3% of the samples.

Research highlights: The PLS-DA models were adequate to classify and identify the twelve native wood species based on the respective NIR spectra, showing good ability to classify independent native wood samples.

Keywords: native woods; NIR spectra; principal components; partial least squares regression.


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Author Biography

José-Henrique Camargo Pace, Universidade Federal Rural do Rio de Janeiro: Seropedica, RJ.

Forestry Engineer
PhD and MS in Environmental and Forestry Sciences
Drying, preservation and identification of wood
Nanomaterials and wood


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How to Cite
PaceJ.-H. C., LatorracaJ.-V. de F., HeinP.-R. G., CarvalhoA. M. de, CastroJ. P., & SilvaC.-E. S. da. (2019). Wood species identification from Atlantic forest by near infrared spectroscopy. Forest Systems, 28(3), e015. https://doi.org/10.5424/fs/2019283-14558
Research Articles