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Buckwheat Identification by Combined UV-VIS-NIR Spectroscopy and Multivariate Analysis

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The application of UV-VIS-NIR spectroscopy combined with multivariate analysis for the classification and identification of buckwheat groats was analyzed. Samples of buckwheat groats differing in harvest time, kernel size, roasting method, and storage time were divided into groups using a cluster analysis method. The principal components method revealed absorption bands in UV-VIS-NIR spectra corresponding to functional groups of the composition components and contributing most to differentiation of the samples into buckwheat quality categories. Discriminant analysis confirmed a hypothesis on dividing the buckwheat samples into groups and formulating a classification function to identify and sort buckwheat groats.

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Authors and Affiliations

  1. Plekhanov Russian University of Economics, Moscow, Russia

    Yu. T. Platov, D. A. Metlenkin & R. A. Platova

  2. All-Russian Scientific-Research Institute of Mineral Resources named after N. M. Fedorovsky, Moscow, Russia

    V. A. Rassulov

  3. Biysk Technological Institute, Subsidiary of Polzunov Altai State Technical University, Biysk, Russia

    A. I. Vereshchagin & V. A. Marin

Authors
  1. Yu. T. Platov
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  2. D. A. Metlenkin
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  3. R. A. Platova
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  4. V. A. Rassulov
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  5. A. I. Vereshchagin
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  6. V. A. Marin
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Correspondence to Yu. T. Platov.

Additional information

Translated from Zhurnal Prikladnoi Spektroskopii, Vol. 88, No. 4, pp. 541–549, July–August, 2021.

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Platov, Y.T., Metlenkin, D.A., Platova, R.A. et al. Buckwheat Identification by Combined UV-VIS-NIR Spectroscopy and Multivariate Analysis. J Appl Spectrosc 88, 723–730 (2021). https://doi.org/10.1007/s10812-021-01231-2

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  • DOI: https://doi.org/10.1007/s10812-021-01231-2

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