DISCRIMINATION OF SOME CAATINGA TREES BASED ON NEAR-INFRARED SPECTROSCOPY OF BARK SAMPLES

Abstract

The Caatinga biome has a high deforestation rate, so the correct identification of species is important to conserve resources. We evaluated the potential of NIR spectroscopy to distinguish the species Anadenanthera colubrina, Cenostigma pyramidale, Capparidastrum frondosum, Commiphora leptophloeos, Mimosa tenuiflora, Manihot baccata, Guapira sp. and Aspidosperma pyifolium based on bark samples. Three trees of each species were felled and the trunk was cut at six positions to obtain bark sample discs: 0%, DBH (1.30 m from ground), 25%, 50%, 75% and 100% of commercial height. Spectra were collected with resolution of 4 cm^-1 and wavenumber ranging from 10 000 to 4 000 cm^-1 using a probe with 2 mm aperture. All discs obtained from the six positions were approximately 5 mm from the probe, and 24 spectra were collected from each disc, for a total of 144 per tree and 432 per species. Classification methods were based on all spectra and only the DBH position, by applying LDA, SVM and K-NN. Better results were obtained with K-NN and first derivative spectra, with accuracy of 0.91 (all tree positions) and 0.85 (only DBH). NIR spectroscopy with multivariate analysis has potential to discriminate Caatinga species based on spectra of bark samples.