Труды по прикладной ботанике, генетике и селекции (May 2024)

Methodological aspects of using NIR spectroscopy to assess biochemical indicators in barley grain

  • V. S. Popov,
  • T. V. Shelenga,
  • O. N. Kovaleva,
  • V. I. Khoreva

DOI
https://doi.org/10.30901/2227-8834-2024-1-109-117
Journal volume & issue
Vol. 185, no. 1
pp. 109 – 117

Abstract

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Background. The possibility of applying near-infrared reflectance (NIR) spectroscopy for rapid assessment of various biochemical parameters in barley varieties and forms is discussed. The data obtained by the Biochemistry and Molecular Biology Department of VIR served to construct calibration models for the content of protein, starch, oil, beta-glucans, and total phenolic compounds (PhC) in grain, facilitating further screening of various barley samples.Materials and methods. The chemical composition of grain was studied in naked and covered spring barley (Hordeum vulgare L.) accessions grown in 2022 in the northwest of Russia. Calibration models were developed to measure the content of protein, oil, starch, beta-glucans, and PhC (80 accessions) in barley grain with the Matrix-I IR analyzer (Bruker Optics, Germany). The models were constructed on the basis of the data obtained by conventional techniques of chemical analysis. The protein/ nitrogen content was assessed using the Kjeldahl method, oil according to the method of defatted dry residue modified by S. V. Ruszkovsky, starch by the polarimetric method according to Evers, beta-glucans by gravimetric analysis, and the total PhC content by the Folin–Ciocâlteu method modified by Singleton and Rossi.Results. Statistical significance of the constructed calibration tests was compared with the results of measuring protein, starch, oil, beta-glucan and PhC levels by chemical methods. It was shown that the data of calibration techniques for protein and starch were significant, while the remaining models required improvement.Conclusion. The proposed method helps to preserve valuable source material, increases labor efficiency, and does not require chemical reagents. Scanning each sample makes it possible to obtain data for several indicators at once, with a specified replication and standard deviation.

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