- PII
- S2500208225020032-1
- DOI
- 10.31857/S2500208225020032
- Publication type
- Article
- Status
- Published
- Authors
- Volume/ Edition
- Volume / Issue number 2
- Pages
- 12-16
- Abstract
- Identification of seed varieties is necessary to ensure the purity and yield of the variety. In this paper, the possibilities of determining the varietal characteristics of the photoluminescence of soybean seeds for the subsequent creation of a methodology for its varietal identification are investigated. Seeds of early and medium-early soybean varieties were taken for research. The spectral characteristics of excitation and photoluminescent radiation were measured using a CM2203 diffraction spectrofluorimeter with specialized software. The integral parameters (absorption capacity and luminescence flux) and the Stokes shift were calculated. Seed excitation occurs in the range of about 300-500nm with the main maxima at 365nm and 424nm and a small side 520nm. The difference in the integral absorption capacity by grades is up to 2.31 times, and in some ranges up to 2.66 times. The use of absorption ratios for varietal identification as relative values independent of the level of the photo signal is more preferable, but the varietal differences Ηλ1/Ηλ2 are only 1.5-1.6 times. Photoluminescence fluxes differ by 1.56 times for different varieties, which will also make it possible to distinguish the seeds of some varieties. The Stokes shift for the studied varieties differs slightly and cannot be a parameter for seed identification. It was found that the luminescent characteristics of the studied soybean varieties have noticeable quantitative differences, but less significant qualitative ones related to the ratio of excitation maxima. It is possible to identify soybean seed varieties by their luminescent properties by the magnitude of the photoluminescence flux when excited by 424nm radiation, while it is advisable to use a difference in quantitative parameters. The value of the ratio of the integral absorption abilities when excited by radiation of 424nm and 365nm, respectively, can be used. Determination of the soybean seed variety by luminescent properties will speed up the identification process and significantly reduce time and material costs.
- Keywords
- соя сортовая идентификация спектр возбуждения спектр люминесценции поток фотолюминесценции
- Date of publication
- 17.09.2025
- Year of publication
- 2025
- Number of purchasers
- 0
- Views
- 4
References
- 1. Беляков М.В. Люминесцентный метод и оптико-электронные устройства экспресс-диагностики качества семян агрокультур: специальность 05.20.02 “Электротехнологии и электрооборудование в сельском хозяйстве”: диссертация на соискание ученой степени доктора технических наук Смоленск, 2021. 438 с.
- 2. Клименков Ф.И., Клименкова И.Н., Иванова Л.П. и др. Лабораторный сортовой контроль в практике первичной селекции и семеноводства, идентификации и сортовой чистоты семян зерновых культур // Аграрная Россия. 2023. № 12. С. 23–28. https://doi.org/10.30906/1999-5636-2023-12-23-28
- 3. Лобачевский Я.П., Дорохов А.С. Цифровые технологии и роботизированные технические средства для сельского хозяйства // Сельскохозяйственные машины и технологии. 2021. Т. 15. № 4. С. 6–10. https://doi.org/10.22314/2073-7599-2021-15-4-6-10
- 4. Смоликова Г.Н., Шаварда А.Л., Алексейчук И.В. и др. Mетаболомный подход к оценке сортовой специфичности семян Brassica napus L. // Вавиловский журнал генетики и селекции. 2015. № 19(1). С. 121–127. https://doi.org/10.18699/VJ15.015
- 5. Ториков В.Е., Шпилев Н.С., Клименков Ф.И. Использование электрофоретических методов для идентификации сортов зерновых культур // Вестник Алтайского государственного аграрного университета. 2019. № 2(172). С. 5–12.
- 6. Шаззо А.А., Корнена Е.П., Кабалина Е.В. Экспресс-способ идентификации современных сортов и гибридов семян подсолнечника на основе спектрального анализа контура изображения // Известия высших учебных заведений. Пищевая технология. 2009. № 1(307). С. 111–112.
- 7. Bu Y., Jiang X., Tian J. et al. Rapid nondestructive detecting of sorghum varieties based on hyperspectral imaging and convolutional neural network // J Sci Food Agric. 2023. Vol. 103. PP. 3970–3983. https://doi.org/10.1002/jsfa.12344
- 8. Fu L., Sun J., Wang S. et al. Identification of maize seed varieties based on stacked sparse autoencoder and near-infrared hyperspectral imaging technology // Journal of Food Process Engineering. 2022. Vol. 45. No. 9. e14120. https://doi.org/10.1111/jfpe.14120
- 9. Li H., Zhang L., Sun H., et al. Identification of soybean varieties based on hyperspectral imaging technology and one-dimensional convolutional neural network // Journal of Food Process Engineering. 2021. Vol. 44. No. 8. e13767. https://doi.org/10.1111/jfpe.13767
- 10. Singh T., Garg N.M., Iyengar S. R. S. Nondestructive identification of barley seeds variety using near-infrared hyperspectral imaging coupled with convolutional neural network // Journal of Food Process Engineering. 2021. Vol. 44. No. 10. e13821. https://doi.org/10.1111/jfpe.13821
- 11. Sun J., Zhang L., Zhou X. et al. A method of information fusion for identification of rice seed varieties based on hyperspectral imaging technology // Journal of Food Process Engineering. 2021. Vol. 44. No. 9. e13797. https://doi.org/10.1111/jfpe.13797
- 12. Wang Y., Song S. Variety identification of sweet maize seeds based on hyperspectral imaging combined with deep learning // Infrared Physics & Technology. 2023. Vol. 130. 104611. https://doi.org/10.1016/j.infrared.2023.104611
- 13. Zhao X., Que H., Sun X. et al. Hybrid convolutional network based on hyperspectral imaging for wheat seed varieties classification // Infrared Physics & Technology. 2022. Vol. 125. 104270. https://doi.org/10.1016/j.infrared.2022.104270
- 14. Zhou Q., Huang W., Tian X., et al. Identification of the variety of maize seeds based on hyperspectral images coupled with convolutional neural networks and subregional voting // J Sci Food Agric, 2021. Vol. 101. PP. 4532–4542. https://doi.org/10.1002/jsfa.11095
