IDENTIFICATION OF FLAX OIL BY THE LINEAR MULTIVARIATE METHODS OF SPECTRAL ANALYSIS
Abstract
A multivariate model has been developed for calibrating the content of flax oil in a binary mixture with unrefined sunflower oil using the optical density spectra in the UV, visible and near IR ranges. The proposed model, based on the principal component analysis, cluster analysis and the linear method of interval projection to latent structures, is characterized by a smaller root-mean-square error (0.12%) compared to the classical interpretable model (0.42%) and the multivariate model (0.63%) applying the full measured spectral range.
About the Authors
М. A. Khodasevich
B. I. Stepanov Institute of Physics of the National Academy of Sciences of Belarus
Belarus
Belarus
68-2 Nezavisimosti Prosp., Minsk, 220072
D. A. Borisevich
B. I. Stepanov Institute of Physics of the National Academy of Sciences of Belarus
Belarus
Belarus
68-2 Nezavisimosti Prosp., Minsk, 220072
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Review
For citations:
Khodasevich М.A., Borisevich D.A. IDENTIFICATION OF FLAX OIL BY THE LINEAR MULTIVARIATE METHODS OF SPECTRAL ANALYSIS. Zhurnal Prikladnoii Spektroskopii. 2019;86(6):880-884. (In Russ.)
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