Abstract
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.
Highlights
The use of Atlantic Forest reforestation woods as a source of income and raw material aims to supply the domestic market of native wood, protect the few biome remnants and stimulate the forestry of timber species (Brancalion et al, 2012)
Through the Principal Component Analysis (PCA) it was possible to identify the best way to work with the database, reducing the noise contained in the spectra
It can be noticed that the model calibration using the PLS-R provided a very significant modeling, due to the high values for the coefficients of determination (R2c) for the species, so that the robustness of the database allowed to obtain values between 0.74 to 0.94, corroborated by the small values of the cross-validation error (RMSEcv), not exceeding 0.15. These results demonstrate that the model generated by PLS-DA presents a significant capacity to classify the native woods of different
Summary
The use of Atlantic Forest reforestation woods as a source of income and raw material aims to supply the domestic market of native wood, protect the few biome remnants and stimulate the forestry of timber species (Brancalion et al, 2012). Illegal trade stems from the lack of proper wood identification (Bisschop, 2012), often because of limitations on the domain of the wood anatomical, physical and visual aspects (Ramalho et al, 2018). The traditional process to wood identification, depending on the species and location, involves costs and a long period of time, generating doubts in the wood commercialization and inspection in pile deposits and sawmills (Soares et al, 2017).
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