Development of a drone-based sowing technology for oilseed radish as a green manure crop

Serhii Zhuravel, Mykola Kravchuk, Svitlana Zhuravel, Karyna Razumna, Mykhailo Kyianychenko
Received: 05.05.2025 Revised: 21.09.2025 Accepted: 29.10.2025
Retrieved from Vol. 28, No. 11, 2025 Pages: 58-66
Download article Read article

Abstract

The aim of the study was to experimentally justify a drone-based surface sowing technology for oilseed radish as a green manure crop under the conditions of the Polissia region of Ukraine. The methodology included laboratory testing of seed quality, NDVI field monitoring, a field experiment with variable flight height, sowing rate and soil preparation type, as well as statistical assessment of variability and survival using ANOVA (p ≤ 0.05). High physiological quality of the Raiduha seeds was confirmed (94.0% germination energy; 99.0% laboratory germination rate), which ensured stability of the initial plant stand. Spatial unevenness of sowing caused by aerodynamic seed drift was investigated; the coefficient of variation reached 68.3%, indicating pronounced asymmetry of the agrophytocenosis. The influence of two sowing rates (320 and 560 plants/m2 ) and two flight heights (3 and 5 m) was analysed, establishing that the optimal combination consisted of a rate of 320 plants/m2 , a 5 m flight height and glyphosate-based soil preparation, which resulted in 13.4% viable plants. Herbicide application accelerated phenological development and reduced inter-species competition. A technological solution was analytically proposed in the form of drone-based crossseeding to compensate for aerodynamic seed displacement and stabilise plant stand density. The practical value of the research lies in its applicability for developing a UAV-based sowing standard for green manure crops within precision farming and post-war agricultural rehabilitation programmes

Keywords

aerodynamic seed drift; agrophytocenosis density; phenological monitoring; precision agriculture; sowing variability; post-war agricultural recovery

  1. Adithya, K., Ramesh, T., Rathika, S., Vanniarajan, C., & Raja, K. (2024). Exploring the feasibility of using drones for seeding of rice (Oryza sativa. L.). Plant Science Today, 11(sp4), 1-10. doi: 10.14719/pst.4826.
  2. Berner, B. (2020). Fertilization and sowing from unmanned aerial vehicle. Modern Agriculture, 2, 18-22. doi: 10.15199/180.2020.2.2.
  3. Cavadini, J.S., & Kladivko, E.J. (2025). Oilseed radish/cereal cover crop bicultures and soil phosphorus distribution. Journal of Soil and Water Conservation, 80(1), 76-90. doi: 10.1080/00224561.2024.2429960.
  4. Convention on Biological Diversity. (1992, June). Retrieved from https://surl.li/tqztsb.
  5. Guebsi, R., Mami, S., & Chokmani, K. (2024). Drones in precision agriculture: A comprehensive review of applications, technologies, and challenges. Drones, 8(11), article number 686. doi: 10.3390/drones8110686.
  6. Han, Y. (2024). Application of unmanned aerial vehicle remote sensing for agricultural monitoring. E3S Web of Conferences, 553, article number 02022. doi: 10.1051/e3sconf/202455302022.
  7. Helander, M., Pauna, A., Saikkonen, K., & Saloniemi, I. (2019).  Glyphosate residues in soil affect crop plant germination and growth. Scientific Reports, 9, article number 19653 doi: 10.1038/s41598-019-56195-3.
  8. Hereshko, H., Voloshchuk, I., Voloshchuk, O., Hlyva, V., & Bilonizhka, K. (2021). Oilseed radish – valuable crop of a wide range use. Foothill and Mountain Agriculture and Stockbreeding, 70(2), 8-17. doi: 10.32636/01308521.2021-(70)-2-1.
  9. Istiak, M., Syeed, M., Hossain, M., Uddin, M., Hasan, M., Khan, R., & Azad, N. (2023). Adoption of Unmanned Aerial Vehicle (UAV) imagery in agricultural management: A systematic literature review. Ecological Informatics, 78, article number 102305. doi: 10.1016/j.ecoinf.2023.102305.
  10. Li, H. (2023). Design of precision seeding device based on hexarotor UAV platform and its application in hard soil. Theoretical and Natural Science, 25, 127-135. doi: 10.54254/2753-8818/25/20240942.
  11. Liu, H., Chen, Z., Wang, Z., & Li, J. (2023). An effective precision afforestation system for UAV. Sustainability, 15(3), article number 2212. doi: 10.3390/su15032212.
  12. Luu, T.H., Nguyen, Th.T., Ngo, Q.H., Nguyen, H.C., & Phuc, Ph.N.K. (2025). UAV-based estimation of post-sowing plant density using RGB imagery and deep learning across multiple altitudes. Frontiers in Computer Science, 7, article number 1551326. doi: 10.3389/fcomp.2025.1551326.
  13. Mohan, M., et al. (2021). UAV-supported forest regeneration: Current trends, challenges and implications. Remote Sensing, 13(13), article number 2596. doi: 10.3390/rs13132596.
  14. Muñoz, G., Abaunza, H., Lozoya, C., & Castañeda, H. (2025). Experimental evaluation of an observer-based controller for an unmanned aerial vehicle in reforestation activities. Journal of Field Robotics, 42(3), 867-879. doi: 10.1002/rob.22503.
  15. Nordin, M.N., Jusoh, M.Sh.M., Ghazali, M.Sh.Sh.M., Desa, M.F.M., Bookeri, M.A.M., Zolkafli, A.K., & Ishak, M.K.I. (2022). Study on distribution pattern of drone spreader by different altitude. International Journal of Agriculture, Forestry and Plantation, 12(2), 18-23.
  16. Qi, P., et al. (2022). Development of multifunctional unmanned aerial vehicles versus ground seeding and outplanting: What is more effective for improving the growth and quality of rice culture? Frontiers in Plant Science, 13, article number 953753. doi: 10.3389/fpls.2022.953753.
  17. Reddy, D., Sahoo, R., Kondraju, T., Rejith, R., Ranjan, R., Bhandari, A., Moursy, A., Tripathi, S., & Kumar, N. (2025). Drone-based multispectral imaging for precision monitoring of crop growth variables. Biology and Life Sciences Forum, 41(1), article number 10. doiЖ 10.3390/blsf2025041010.
  18. Stroud, J.L., Irons, D.E., Watts, C.W., Storkey, J., Morris, N.L., Stobart, R.M., Fielding, H.A., & Whitmore, A.P. (2017). Cover cropping with oilseed radish (Raphanus sativus) alone does not enhance deep burrowing earthworm (Lumbricus terrestris) midden counts. Soil and Tillage Research, 165, 11-15. doi: 10.1016/j.still.2016.07.013.
  19. Tsytsiura, Y. (2024a). Influence of biochemical composition of above-ground biomass of oilseed radish on the expediency of its green manure application. Agrology, 7(2), 61-72. doi: 10.32819/202409.
  20. Tsytsiura, Y. (2024b). Evaluation of ecological adaptability of oilseed radish (Raphanus sativus L. var. oleiformis Pers.) biopotential realization in the system of criteria for multi-service cover crop. Journal of Ecological Engineering, 25(7), 265-285. doi: 10.12911/22998993/188603.
  21. Vavlas, N.C., Porre, R., Meng, L., Elhakeem, A., van Egmond, F., Kooistra, L., & De Deyn, G.B. (2024). Cover crop impacts on soil organic matter dynamics and its quantification using UAV and proximal sensing. Smart Agricultural Technology, 9, article number 100621. doi: 10.1016/j.atech.2024.100621.
  22. Wang, X., Zhiyan, Zh., Boqian, Ch, Jinfeng, Zh., Xiaolong, F., & Hewitt, A. (2024). Distribution uniformity improvement methods of a large discharge rate disc spreader for UAV fertilizer application. Computers and Electronics in Agriculture, 220, article number 108928. doi: 10.1016/j.compag.2024.108928.
  23. Zhang, S., Huang, M., Cai, C., Sun, H., Cheng, X., Fu, J., Xing, Q., & Xue, X. (2022). Parameter optimization and impacts on oilseed rape (Brassica napus) seeds aerial seeding based on unmanned agricultural aerial system. Drones, 6(10), article number 303. doi: 10.3390/drones6100303.
  24. Zhijun, W., Yu, C., Shi, S., Hao, D., Liao, X., & Lijia, X. (2023). Design and experimental analysis of drone rice direct seeding device. Journal of Engineering Science and Technology Review, 16(5), 132-139. doi: 10.25103/ jestr.165.16.
  25. Zhou, H., Yao, W., Su, D., Guo, S., Zheng, Z., Yu, Z., Gao, D., Li, H., & Chen, C. (2024). Application of a centrifugal disc fertilizer spreading system for UAVs in rice fields. Heliyon, 10(8), article number e29837. doi: 10.1016/j. heliyon.2024.e29837.
Zhuravel, S., Kravchuk, M., Zhuravel, S., Razumna, K., & Kyianychenko, M. (2025). Development of a drone-based sowing technology for oilseed radish as a green manure crop. Scientific Horizons, 28(11), 58-66. https://doi.org/10.48077/scihor11.2025.58