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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles containing the keyword 'multivariate modelling'.

Category: Research article

article id 9996, category Research article
Mulualem Tigabu, Mostafa Farhadi, Lars-Göran Stener, Per C. Odén. (2018). Visible + Near Infrared Spectroscopy as taxonomic tool for identifying birch species. Silva Fennica vol. 52 no. 4 article id 9996. https://doi.org/10.14214/sf.9996
Highlights: Multivariate modelling of visible + near infrared (NIR) reflectance spectra of single seeds distinguished Betula pubescens and B. pendula with 100% and 99% accuracy, respectively; The results demonstrate the feasibility of NIR spectroscopy as taxonomic tool for classification of species that have morphological resemblance.

The genus Betula L. is composed of several species, which are difficult to distinguish in the field on the basis of morphological traits. The aim of this study was to evaluate the taxonomic importance of using visible + near infrared (Vis + NIR) spectra of single seeds for differentiating Betula pendula Roth and Betula pubescens Ehrh. Seeds from several families (controlled crossings of known parent trees) of each species were used and Vis + NIR reflectance spectra were obtained from single seeds. Multivariate discriminant models were developed by Orthogonal Projections to Latent Structures – Discriminant Analysis (OPLS-DA). The OPLS-DA model fitted on Vis + NIR spectra recognized B. pubescens with 100% classification accuracy while the prediction accuracy of class membership for B. pendula was 99%. However, the discriminant models fitted on NIR spectra alone resulted in 100% classification accuracies for both species. Absorption bands accounted for distinguishing between birch species were attributed to differences in color and chemical composition, presumably polysaccharides, proteins and fatty acids, of the seeds. In conclusion, the results demonstrate the feasibility of NIR spectroscopy as taxonomic tool for classification of species that have morphological resemblance.

  • Tigabu, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, Box 49, SE-230 52 Alnarp, Sweden ORCID ID:E-mail: mulualem.tigabu@slu.se (email)
  • Farhadi, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, Box 49, SE-230 52 Alnarp, Sweden ORCID ID:E-mail: mostafa.farhadi@gmail.com
  • Stener, The Forestry Research Institute of Sweden, Ekebo 2250, SE-268 90 Svalöv, Sweden ORCID ID:E-mail: lars-goran.stener@skogforsk.se
  • Odén, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, Box 49, SE-230 52 Alnarp, Sweden ORCID ID:E-mail: per.christer.oden@slu.se

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