Use of UAVs in Agriculture for Monitoring and Management of Cereal Crops

Traditional crop monitoring methods are labor-intensive, time-consuming, and costly, while satellite imagery is constrained by dependence on weather conditions, low spatial resolution, and infrequent revisit times. In contrast, unmanned aerial vehicles (UAVs) off er rapid, high-resolution monitoring that enables the timely detection of anomalies and disruptions in crop development. (Research purpose) To develop an information model for real-time crop monitoring and decision support based on data collected by unmanned aerial vehicles (UAVs). (Materials and methods) Data obtained from UAVs support key crop management operations, including variable-rate spraying based on treatment zone maps, site-specific and zonal fertilization guided by the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Red Edge Index (NDRE), early detection of diseases and pests, and yield forecasting through statistical analysis of time series. A systematic content analysis of existing literature was conducted. Given the large volume and diversity of associated with UAV application in agriculture, particularly in cereal crop production, an appropriate information modeling approach was identified and substantiated. (Results and discussion) The advantages and limitations of UAV use were identified. It was shown that UAV-based agricultural monitoring generates vast and diverse datasets that require systematic collection, structuring, and efficient processing. The study substantiates and proposes an information model scheme for real-time crop monitoring and decision support in precision agriculture. The model includes modules for data collection and preprocessing, a computational module for mathematical analysis incorporating modeling and machine learning, and an expert system that generates recommendations for agro-technical interventions. (Conclusions) The study demonstrates that the effective integration of UAVs into crop management processes can reduce the consumption of fuel, water, fertilizers, and pesticides. Additionally, the use of UAVs increases yield potential and improves labor efficiency by enabling precise monitoring, automation, and optimization of agro-technical operations.

1. Habarina D.S., Tishaninov I.A. Analysis of the use of various types of unmanned aerial vehicles (UAVs) in agriculture. Science Without Borders.2021. N4(56). 78-83 (In Russian).

2. Tsench Yu.S., Kurbanov R.K., Zakharova N.I. Evolution of flight control systems and aerial photography in unmanned agricultural aircraft. Agricultural Machinery and Technologies. 2024. Vol. 18. N2. 11-19 (In Russian). DOI:10.22314/2073-7599-2024-18-2-11-19.

3. Tsench Yu.S., Kurbanov R.K. History of unmanned aircraft flight controller development. Agricultural Machinery and Technologies. 2023. Vol. 17. N3. 4-15 (In Russian). DOI: 10.22314/2073-7599-2023-17-3-4-15.

4. Starovoytov S.I., Tsench Yu.S., Korotchenya V.M., Lichman G.I. Technical systems for digital soil quality control. Agricultural Machinery and Technologies. 2020. N14(1). 16-21 (In Russian). DOI: 10.22314/2073-7599-2020-14-1-16-21.

5. Urasova A.A., Glezman L.V., Fedoseeva S.S. The use of agricultural unmanned aerial vehicles in the Russian Federation: assessment of consumer preferences. Economy of Regions. 2023. N19(4). 1146-1160 (In Russian). DOI: 10.17059/ekon.reg.2023-4-15.

6. Kovalev A.S., Litvinov A.A. The experience of fungicidal treatment of sunflower with XAG agrodrons in Agro-Siberia LLC.Agrarian Policy. 2025. Vol. 2. 44-47 (In Russian).

7. Zhang R., Hewitt A., Li L. et al. Editorial: advanced technologies of UAV application in crop pest, disease and weed control. Frontiers in Plant Science. 2023. Vol. 14. 1-3 (In English). DOI: 10.3389/fpls.2023.1253841.

8. Dorokhov A.S., Starostin I.A., Eschin A.V. Development prospects for methods and technical means of farm crop protection. Agricultural Engineering. 2021. N1 (101). 26-35 (In Russian). DOI: 10.26897/2687-1149-2021-1-26-35.

9. Meng Ya., Zhong W., Liu Yu et al. Droplet distribution of an autonomous UAV-based sprayer in Citrus Tree Canopy. Journal of Physics: Conference Series. 2021. Vol. 2203. 2 (In English). DOI: 10.1088/1742-6596/2203/1/012022.

10. Lan Y., Qian S., Chen S. et al. Influence of the downwash wind field of plant protection UAV on droplet deposition distribution characteristics at different flight heights. Agronomy. 2021. Vol. 11(12). 2399. 1-13 (In English). DOI: 10.3390/agronomy11122399.

11. Gibbs J., Peters T.M., Heck L.P. Comparison of droplet size, coverage, and drift potential from UAV application methods and ground application methods on row crops. Trans ASABE. 2021. Vol. 64(3). 819-828 (In English). DOI: 10.13031/trans.14121.

12. Subramanian K.S., Pazhanivelan S., Srinivasan G. et al. Drones in insect pest management. Frontiers in Agronomy. 2021. Vol. 3. 1-12 (In English). DOI: 10.3389/fagro.2021.640885.

13. Guebsi R., Mami S., Chokmani K. Drones in precision agriculture: A comprehensive review of applications, technologies, and challenges. Drones. 2024. Vol. 8(11). 686. 1-30 (In English). DOI: 10.3390/drones8110686.

14. Dorokhov A.S., Starostin I.A., Eshchin A.V., Kurba nov R.K. Technical means for chemical protection of plants: current state and development prospects. Agricultural Engineering. 2022. N24(3). 12-18 (In Russian). DOI: 10.26897/2687-1149-2022-3-12-18.

15. Bershitsky Yu.I., Saifetdinov A.R., Maksimenko A.A., Elfimov D.A. Economic efficiency of using unmanned aerial vehicles as an element of digitalization of crop production. Bulletin of the Academy of Knowledge. 2024. Vol. 2(61). 66-69 (In Russian). EDN: DDRCKH.

16. Raj M., Harshini N.B., Gupta Sh. et al. Leveraging precision agriculture techniques using UAVs and emerging disruptive technologies. EnergyNexus. 2024. Vol. 14. 1-25 (In English). DOI: 10.1016/j.nexus.2024.100300.

17. Yadrovskaya M.V. Revisiting computer modeling. Advanced Engineering Research. 2020. Vol. 20. N3. 332-345 (In Russian). DOI: 10.23947/2687-1653-2020-20-3-332-345.

18. Salaev B.K., Seregin A.A., Eviev V.A. et al. Analysis of using unmanned aerial vehicles in agriculture. Don Agrarian Science Bulletin. 2022. N15-4(60). 29-44 (InRussian). DOI: 10.55618/20756704_2022_15_4_29-44.

19. Makam S., Komatineni Bh.K.,Meena S.S., Meena U. Unmanned aerial vehicles (UAVs): an adoptable technology for precise and smart farming. Discover Internet of Things. 2024. Vol. 4. N12. 1-30 (In English). DOI: 10.1007/s43926-024-00066-5.

20. Liu J., Wang W., Li Ju. et al. UAV remote sensing technology for wheat growth monitoring in precision agriculture: comparison of data quality and growth parameter inversion. Agronomy. 2025. Vol. 15(1). 159. 1-24 (In English). DOI: 10.3390/agronomy15010159.