Review on Application of Drone in Spraying Pesticides and Fertilizers

DOI : 10.17577/IJERTV10IS110034

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Review on Application of Drone in Spraying Pesticides and Fertilizers

Sane Souvanhnakhoomman

De La Salle University-

Graduate program in Mechanical Engineering, Manila, Philippine

Abstract: In today's agriculture, there are far too many innovations involved. One of the emerging technologies is pesticide spraying using drones. Manual pesticide spraying has a number of negative consequences for the people who are involved in the spraying operation. The result of exposure symptoms can include minor skin inflammation and birth abnormalities, tumors, genetic modifications, nerve and blood diseases, endocrinal interference, coma or death. However, Drone can be used to automate fertilizer application, pesticide spraying, and field tracking. This paper provides a concise overview of the use of drones for field inspection and pesticide spraying. displays different methodologies and controllers of agriculture drone and explains some essential Drone Hardware, Software elements and applications.

Keywords: Drone technology, spraying pesticides, crop monitoring


    The explosion of the human population makes high productivity, high performance and sustainable agriculture more important [1]. In the modern environment, agriculture is essential for the subsistence of more than 60 percent of total of the world's population. [2]. It is a critical element in the protection of the environment in the developed world. The agricultural modernisation is mandatory when demand and food supply are increased. Drone are one of the most advantageous equipment for modern agriculture.

    The pesticides and fertilizers are critical components in the control of insects and the development of crops. Spraying pesticides and fertilizers by hand causes tumors, hypersensitivity, allergies, and other illnesses in people. Hence, Drone can be used to automate fertilizer application, pesticide spraying, and field tracking, which is also used for many applications such as search and rescue, police, code inspections, Emergency Management, fire. Other advantages of drones include their fast maneuverability, improved payload, high lifting power, and stability [3]. It comes with a universal sprayer for spraying both liquid and solid contents. The global nozzle sprays all pesticides and fertilizers, but the tension pump is only used when spraying pesticides and not when spraying fertilizer. In wide fields, the GPS can be used to automatically direct the quadcopter and power it remotely. A quad copter is piloted by an

    Water Level Monitoring sensors. As a result of this experiment, they eventually concluded that with proper implementation of UAVs in the agricultural sector, savings in terms of water, chemical abuse, and labour can be projected to range between 20% and 90%. [7].

    autopilot controller, and the payload is driven by an RF transmitter and motors. The figure 1 illustrates the pesticides spraying mechanism [4].

    Figure 1: Pesticide spraying mechanism

    This paper usually depicts the characteristics of appropriate Drones for a particular agricultural purpose. Furthermore, it will be clear as to which Drone archetype is needed for specific farming tasks. The systematic review of this article is based on basic keyword and abstract searches in Scopus, WOS (Web of Science), and Google Scholar databases. Several trustworthy websites were also consulted for subject-related material.


    Yallappa (2017) improved an hexacopter with 6 BLDC motors and two LiPo batteries of 6 cells- 8000 mAh. Their research also includes a performance assessment of spray liquid discharge and pressure, spray liquid depletion, and droplet size and density determination. By means of their project, they eventually created a drone that can hold 5.5 L of liquid and has a 16-minute endurance period [5].

    Dongyan (2015) investigated successful swath width and droplet distribution uniformity over aerial spraying systems such as the M-18B and Thrush 510G. The agricultural planes flowered respectively at 5m and 4m high, and by this experiment they conclude the disparity in swath width of M- 18B and Thrush 510G in flight height [6].

    Prof. B. Balaji (2018) created a hexacopter UAV for pesticide spraying as well as crop and environmental surveillance using Raspberry Pi and the Python programming language. Their UAV also has a variety of sensors, including DH11, LDR and

    Kurkute (2018) used basic cost-efficient equipment to work with UAV quadcopter and its spraying system. Spraying with both liquid and solid material is done using the universal sprayer method. During their analysis, they also compared various agricultural controllers and came to the

    conclusion that the quadcopter system with the Atmega644PA is the most suitable due to its successful implementation [8].

    Huang (2015) developed a low-volume sprayer that can be used in unmanned helicopters. The helicopter has a 3 m main rotor diameter and a payload capacity of 22.7 kg. It used to take at least a gallon of gas every 45 minutes. This research paved the way for the development of UAV aerial application systems for crop production with a higher goal rate and a larger VMD droplet scale [9].

    Shilpa Kedari has suggested a low-cost, lightweight Quadcopter (QC) framework. The quadcopter is also known as Unmanned Aerial Vehicle (UAV). This quadcopter is compact and can be used for both indoor and outdoor crops. The quadcopter is an unmanned flight that uses an android smartphone to spray pesticides and fertilizer. The contact between the quadcopter and the android smartphone is achieved in real time using a Bluetooth device. This method is used to reduce agricultural field problems while still increasing agricultural yield [10].

    Sadhana improved on the above approaches and created the quadcopter UAV and shower module, which can be used to spray pesticides in agriculture fields to increase efficiency

    and protect materials. The total load for this project is 1 kg and is used to spray low altitude pesticide quadruple copter lift. The Arduino UNO AT mega328 and Brushless Direct Current (BLDC), Electronic Speed Control (ESC), MPU- 6050, which combines a MEMS accelerometer and a MEMS gyro into a single chip, Radio receiver, LIPO battery, and pesticide spraying module control this quadcopter [11].


    • Methodologies

    The main board in the drone is the flight controller, which is loaded with cutting-edge firmware and is in charge of the actual flight. The flight controller controls a lot during the flight or drone at the same time. It has been designed and connected with a micro controller to the four motors without brush motor. BLDC motor attach in the Drone setup model with the rotors. These BLDC motors are controlled by the Electronic Speed controllers (ESC). The drone is powered by the transmitter and receiver of the radio network. There are several platforms for individual drone control activities for any RC transmitter. A sample block diagram shown in Fig 4. Different methodologies and controllers of Drone are shown in Table 3.

    Figure 4. The main components of methodologies drone

    Table 1. Different methodologies and controllers of Drone


    Implementation Details



    Nozzle Type


    Load (L-Litres)

    Munmun Ghosal (2018) [12]

    Monitoring the exact place in which GPS module is notable for air pollution.

    ESC, BLDC motor, sensor such as LM35, AM1001, LDR, MQ6, and MQ135.

    Arduino Uno ATmega328

    It is a low-cost, high-efficiency model.

    Sabikan (2016)


    A platform for the autonomous UAV quad copter was built for open- source projects.

    IMU, 2.4GHz

    telemetry, ESC.

    ArduPilotMega (APM) 2.6

    The quad copter OSP offers both software and hardware as a comprehensive framework and also flexibility design for research or project purposes.

    Shilpa Kedari (2016) [10]

    A quad copter is deployed on Android smartphone. These android applications control the quad-copter for pesticide and fertiliser spraying.

    IMU , barometer, accelerometer, gyroscope.

    Arduino board

    Reduces the problem of the health of farmers during pesticides and fertilizer application.

    Sadhana B (2017)


    Developed the quad copter and sprayer module


    6050 sensor.

    Arduino Uno ATmega328

    Mini nozzle

    High stability and increased power lifting. It is easy to compare the quad copter control to a miniature helicopter or vehicle.


    Parth N. Patel (2016) [14]

    The quad copters enable the fabrication of unique folding frames for safe transport and convenient packaging of cylindrical cushioned boxes.

    Accelerometer, gyroscope, IMU, Infrared camera, BLDC, ESC

    Atmel AVR microcontroller

    It is adaptable, allows function performance to be modified and also allows technological integration.

    Weicai Qin (2019)


    Study the effect in different heights and sprayers of the spraying system.

    GPS, digital temperature, humidity indicator, water sensitive.

    N-3 type

    Rotary atomizer

    In this UAV the pesticides were initially employed in low altitude and low volume.

    25 lit

    Tanga (2018) [16]

    Determining the deposition of droplets in various forms.

    Digital temperature, Humidity indicator, Water sensitive Sensors.

    Anemometer, Filter papers.

    UAV ZHKU- 0404-01

    Flat fan

    For wind speed measurement. The indicator is used for air humidity measurement.

    15 L

    Tejas S. Kabra (2017) [17]

    Suggest Quad Copter [QC] to be introduced. The quad copter reduces the problem of farming


    This procedure reduces the medical problem created by hand sprinkling.

    1.5 to 3 L

    Rahul Desale (2019) [18]

    This project is being utilized by UAV in agriculture to spray insecticides.

    BLDC, ESC, ratio controller, Transmitter.

    Flight Controller

    Fog nozzle

    The benefit of this project is that it frame to spray pesticides in a safe place by utilizing drone.

    Shaik. Khamuruddeen (2019) [19]

    This type is used for quad copter spraying of insecticides.

    BLDC, ESC,

    Transceiver, Infrared Camera.

    PID Micro Controller

    To identify less work where PSQ is used.

    • Hardware and software Components

    Drones are an array of sophisticated hardware, software and advanced technology. In general, many software and hardware components are used to properly control the drone according to Drone's startling variants. The unified body or structural components are usually referred to as hardware. Drone hardware shows the technical components of the Drone enough and takes software applications guidance. Furthermore, the software may be referred to as a Drone's brain. The software is supposed to tell the Drone whether or

    not to go and what to do. As a potential method of speculating and combining all of the Drone's critical data, a complicated structure benefits from the software portion. Drone software consists of a large number of different applications, processes, and operations. It also has a specific liability, as shown by its hardware components. The Drone is correctly controlled by a special combination of hardware and software. Tables 1 and 2 show some of the underlying hardware and software components respectively.

    Table 2. The following are some of the most important drone hardware components and implementations.

    Name of the Element



    BLDC motor

    Movement control

    [5][7][11][12][14] [17-19]

    Flight Controller

    control fixed-wing drone



    For use radio signals to transmit commands wirelessly



    Regulates the speed of BLDC



    Movement of drone


    Water Pump:

    for spraying water






    Record video or capture image



    For measure the acceleration Gyro



    For rotational motion or Maintaining orientation and angular velocity



    Measuring the strength and direction of the magnetic field.



    Retaining power



    Sensing environmental conditions


    Table 3. The following are some of the most widely used Drone Software components and implementations.

    Name of the Element




    Image processing



    Image-processing and analysis


    Adobe Photoshop

    Distortion emendation



    Capturing and analysing spatial and geographic data.

    [25] [26]


    Communicating with UAVs



    Vegetation calculation and 3-D models construction

    [29] [30]


    Control system





The evaluation provided in Table 1 supports the use of Unmanaged Aerial Vehicle (UAV) in different quadcopters and improves the agricultural accuracy method the pesticides and fertilisers in agricultural fields in various crops. However, table 2 and 3 displayed some of the most important drone hardware components and implementations and the software is supposed to tell the Drone whether or not to go and what to do. As a potential method of speculating and combining all of the Drone's critical data. Drone software consists of a large number of different applications, processes, and operations

Drone is still in its early stage in precision agriculture and maybe a scope for additional improvement both in technology and in agriculture. It is expensed to develop Drone's innovation, improved ways of image processing, lower prices, flying times, battery, new camera models, small volume spraying systems and kinds of nozzles.


  1. Popescu, D.; Stoican, F.; Stamatescu, G.; Ichim, L.; Dragana, C. Advanced UAVWSN System for Intelligent Monitoring in Precision Agriculture. Sensors 2020, 20, 817.

  2. Zavatta, G.; Perrone, T.; Figus, C. Agriculture Remains Central to The World Economy. 60% of the Population Depends on Agriculture for Survival. 2020. Available online: remainscentral- to-the-world-economy.html

  3. Dr. K. Gayathri Devi1, N. Sowmiya2, Dr.K. Yasoda3, Dr.K. Muthulakshmi4, Mr.B. Kishore5. Review on application of Drone for crop health monitoring and spraying pesticides and fertilizers. Journal of Critical Reviews. ISSN- 2394-5125. Vol 7, Issue 6, 2020, 667-672

  4. Sadhana, B., Naik, G., Mythri, R. J., Hedge, P. G., & Shyama, K.

    S. B. Development of quad copter based pesticide spraying mechanism for agricultural applications. International Journal of Innovation Research Electrical Electronics Instrumentation Control Engineering, Vol.5, No.2, pp.121-123, 2017.

  5. Yallappa D., M. Veerangouda, Devanand Maski, Vijayakumar Palled and M. Bheemanna, Development and Evaluation of Drone mounted sprayer for Pesticides Applications to crops. Oct. 2017,

    Research Gate, Conference paper

  6. Zhang Dongyan, Chen Liping, Zhang Ruirui, Xu gang, Lan Yubin, Wesley Clint Hoffmann, Wang Xiu, Xu Min, Evaluating effective swath width and droplet distribution of aerial spraying systems on M18B and Thrush 510G airplanes, April 2015, Int J. Agric. & Bio Eng, Vol 8 No.21.

  7. Prof. B.Balaji, Sai Kowshik Chennupati, Siva Radha Krishna Chilakalapudi, Rakesh Katuri, kowshik Mareedu, Design of UAV (Drone) for Crops, Weather Monitoring and For Spraying Fertilizers and Pesticides., Dec 2018, IJRTI, ISSN: 2456-3315.

  8. S.R. Kurkute, B.D. Deore, Payal Kasar, Megha Bhamare, Mayuri Sahane, Drones for Smart Agriculture: A Technical Report, April 2018, IJRET, ISSN: 2321-9653.

  9. Huang, Y. Hoffmann, W.C. Lan, Y. Wu and Fritz, B.K, Development of a spray system for an unmanned aerial vehicle

    platform, Dec 2015, Applied Engineering in Agriculture, 25(6):803-809.

  10. Kedari, S., Lohagaonkar, P., Nimbokar, M., Palve, G., & Yevale,

    P. Quadcopter-A Smarter Way of Pesticide Spraying. Imperial Journal of Interdisciplinary Research, Vol.2, No.6, 2016.

  11. Sadhana, B., Naik, G., Mythri, R. J., Hedge, P. G., & Shyama, K.

    S. B. Development of quad copter-based pesticide spraying mechanism for agricultural applications. International Journal of Innovation Research Electrical Electronics Instrumentation Control Engineering, Vol.5, No.2, pp.121-123, 2017.

  12. Ghosal, M., Bobade, A., & Verma, P. A Quadcopter Based Environment Health Monitoring System for Smart Cities. Second International Conference on Trends in Electronics and Informatics (ICOEI) ,pp. 1423-1426, 2018.

  13. Sabikan, S., & Nawawi, S. W.. Open-source project (OSPs) platform for outdoor quadcopter. Journal of Advanced Research Design, Vol.24, pp. 13-27, 2016.

  14. Patel, P. N., Patel, M. A., Faldu, R. M., & Dave, Y. R. (2013). Quadcopter for agricultural surveillance. Advance in Electronic and Electric Engineering, 3(4), 427-432.

  15. Qin, W., Xue, X., Zhang, S., Gu, W., & Wang, B. (2018). Droplet deposition and efficiency of fungicides sprayed with small UAV against wheat powdery mildew. International Journal of Agricultural and Biological Engineering, 11(2), 27-32.

  16. Tang, Y., Hou, C. J., Luo, S. M., Lin, J. T., Yang, Z., & Huang, W.

    F. Effects of operation height and tree shape on droplet deposition in citrus trees using an unmanned aerial vehicle. Computers and electronics in agriculture, Vol.148, pp. 1-7, 2018.

  17. Kabra, T. S., Kardile, A. V., Deeksha, M. G., Mane, D. B., Bhosale,

    P. R., & Belekar, A. M. Design, Development & Optimization of a Quad-Copter for Agricultural Applications. International Research Journal of Engineering and Technology, Vol. 04 No.07, 2017.

  18. Rahul Desale, Ashwin Chougule, Mahesh Choudhari, Vikrant Borhade, S.N. Teli. Unmanned Aerial Vehicle For Pesticides Spraying. International Journal for Science and Advance Research In Technology, Vol 5, No. 4, pp.79-82, 2019.

  19. Shaik.Khamuruddeen, K.Leela Rani, K.Sowjanya, Brahmaiah Battula. Intelligent Pesticide Spraying System using Quad Copter International Journal of Recent Technology and Engineering, Vol.7, No.5S4, 2019.

  20. Bassine, F.Z.; Errami, A.; Khaldoun, M. Real Time Video Processing using RGB Remote Sensing by Drone. In Proceedings of the International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), Kenitra, Morocco, 56 December 2018; pp. 15.

  21. Hentschke, M.; Pignaton, E.; Hennig, C.H.; Da Veiga, I.C.G.; Da Veiga, I.G. Evaluation of Altitude Sensors for a Crop Spraying Drone. Drones 2018, 2, 25.

  22. Gao, P.; Zhang, Y.; Zhang, L.; Noguchi, R.; Ahamed, T. Development of a Recognition System for Spraying Areas from Unmanned Aerial Vehicles Using a Machine Learning Approach. Sensors 2019, 19, 313.

  23. Tsouros, D.C.; Bibi, S.; Sarigiannidis, P.G. A review on UAV- based applications for precision agriculture. Information 2019, 10, 349.

  24. Tsouros, D.C.; Triantafyllou, A.; Bibi, S.; Sarigannidis, P.G. Data Acquisition and Analysis Methods in UAV based Applications for Precision Agriculture. In Proceedings of the 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini Island, Greece, 2931 May 2019; pp. 377384.

  25. Budiharto, W.; Chowanda, A.; Gunawan, A.A.S.; Irwansyah, E.; Suroso, J.S. A Review and Progress of Research on Autonomous Drone in Agriculture, Delivering Items and Geographical Information Systems (GIS). In Proceedings of the 2ndWorld Symposium on Communication Engineering (WSCE), Nagoya, Japan, 2023 December 2019; pp. 205209.

  26. Stojcsics, D.; Domozi, Z.; Molnár, A. Automated evaluation of agricultural damage using UAV survey. Acta Univ. Sapientiae Agric. Environ. 2018, 10, 2030.

  27. Atoev, S.; Kwon, K.-R.; Lee, S.-H.; Moon, K.-S. Data analysis of the MAVLink communication protocol. In Proceedings of the International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, Uzbekistan, 24 November 2017; pp. 13.

  28. Kim, J.; Kim, S.; Ju, C.; Son, H.I. Unmanned Aerial Vehicles in Agriculture: A Review of Perspective of Platform, Control, and Applications. IEEE Access 2019, 7, 105100105115.

  29. Stateras, D.; Kalivas, D. Assessment of Olive Tree Canopy Characteristics and Yield Forecast Model Using High Resolution UAV Imagery. Agriculture 2020, 10, 385.

  30. Singh, K.K.; Frazier, A. A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications. Int. J. Remote Sens. 2018, 39, 50785098.

  31. Basso, M.; Stocchero, D.; Henriques, R.V.B.; Vian, A.L.; Bredemeier, C.; Konzen, A.A.; Pignaton, E. Proposal for an Embedded System Architecture Using a GNDVI Algorithm to Support UAV-Based Agrochemical Spraying. Sensors 2019, 19, 5397

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