Use of Near Infrared Spectroscopy (NIRS) as a tool to discriminate species of the genus Dimorphandra Schott (Leguminosae: Caesalpinioideae)

Abstract

This work aimed to use near-infrared spectroscopy (NIRS) as a tool to discriminate species of the genus Dimorphandra Schott (Leguminosae, Caesalpinioideae). Spectra were collected from 315 individuals (six readings per individual) distributed in 20 species of Dimorphandra using a Thermo Nicollet spectrophotometer, FT-NIR Antaris II Method Development System (MDS) in the INPA (National Institute of Amazonian Research) Herbarium. Absorbance values comprise the wavenumbers from 4,000 to 10,000 cm^-1, corresponding to the near infrared region, recorded for 16 scans at a resolution of 8 cm^-1. Principal Component Analysis (PCA) was used to visualize the spectral distribution. Discriminant functions were generated in order to evaluate the potential of the data to correctly distinguish the species and the 70-30 cross-validation technique was used to validate the generated models, with selections randomized 1, 10, 50 and 100 times. Excellent results were obtained in the PCA, with prediction values of 95-92%, using the 70-30 validation test in the linear discriminant analyses (LDA), thus indicating high predictive power in the discrimination of species of the genus Dimorphandra. Thus, it is inferred that NIRS contributes to the discrimination of species of the genus and elucidation of taxonomic problems.