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Title: Discrimination of taxonomic identity at species, genus and family levels using Fourier Transformed Near-Infrared Spectroscopy (FT-NIR)
Authors: Lang, Carla
Almeida, Danilo Roberti Alves de
Costa, Flávia Regina Capellotto
Keywords: Discriminant Analysis
Fourier Transforms
Near Infrared Spectroscopy
Plants (botany)
Infrared Devices
Discriminant Analysis
Ftir Spectroscopy
Identification Method
Infrared Spectroscopy
Species Identification
Issue Date: 2017
metadata.dc.publisher.journal: Forest Ecology and Management
metadata.dc.relation.ispartof: Volume 406, Pags. 219-227
Abstract: Fourier Transformed Near-Infrared Spectroscopy (FT-NIR) has previously been shown to be effective in species discrimination of plant species, this prompted us to ask if higher taxonomic levels could also be discriminated, and if discrimination based on branch pieces would be equally efficient or better than based on leaves. We tested this with a sample of 384 branches and 349 leaves of 40 Amazonian species. We obtained spectral readings of dry branch and leaf material, and compared the rate of correct predictions of species, genera and family with a classifier based on Linear Discriminant Analysis (LDA). Discrimination of species, genus and family with Fourier Transformed Near-Infrared Spectroscopy (FT-NIR) was good using either branches or leaves. We obtained an average of 90.8% correct species identifications over all species based on branch FT-NIR profiles, and 94.1% based on leaves. Also, we obtained more than 95% correct genus and family identifications. Most of the identification errors occurred among species, genera and families of distinct clades. Near-infrared spectroscopy has great potential for discriminating species from branch samples and is suitable to discriminate a diverse range of genera and families of Amazonian trees. © 2017 Elsevier B.V.
metadata.dc.identifier.doi: 10.1016/j.foreco.2017.09.003
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