Unmanned aerial vehicle (UAV)-assisted pesticide application for pest and disease prevention and control in rice

Reddy Ragiman, Kiran Babu Talluri, Varma NRG, Vidya Sagar B

Abstract


Unmanned Aerial Vehicles (UAVs) have emerged as innovative tools in agriculture, revolutionizing crop protection practices and the use of pesticide combinations to aid the management of insect pests and diseases in a single application. This research delves into assessing the efficacy of drone-based pesticide spraying utilizing combinations of pesticides to combat insect pests and diseases in rice cultivation. In kharif 2022, the physically compatible combination of insecticides (chlorantraniliprole 18.5% SC and tetraniliprole 200 SC) with fungicides (picoxystrobin 7.5%+tricyclazole 22.5% SC and tebuconazole 50%+trifloxystrobin 25% WG) were administered via drones and compared with conventional Taiwan sprayer. The results indicated that tebuconazole+trifloxystrobin, when applied via drones, exhibited the highest control efficacy against the brown spot, sheath blight, and sheath rot (47.8%, 77.4%, and 75.2% respectively). Moreover, combination treatment i.e., tetraniliprole+(tebuconazole+trifloxystrobin), applied using a drone, achieved the most effective control (78.1%) against grain discoloration. Additionally, drone-based tetraniliprole application showed effectiveness against stem borer and whorl maggot (efficacy rates of 49.1%, 66.6%, and 60.7% for Dead Hearts, White Ear, and Whorl Maggot, respectively). Overall, the pesticide combination treatment i.e., tetraniliprole+(tebuconazole+trifloxystrobin) showed higher control efficacy against all the insect pests and diseases and recorded the highest grain yield of 7995 kg/hm2 with incremental cost benefit ratio (ICBR) of (1:5.63) when sprayed with a drone. Overall, this study underscores the potential of drone-assisted pesticide application in effectively managing multiple insect pests and diseases in rice offering superior precision, efficacy, efficiency, and yield.
Keywords: bio-efficacy, drone spraying, drone-based pest management, precision agriculture, pesticide combinations
DOI: 10.25165/j.ijabe.20241705.8640

Citation: Ragiman S, Talluri K B, NRG V, B Vidya S. Unmanned aerial vehicle (UAV)-assisted pesticide application for pest and disease prevention and control in rice. Int J Agric & Biol Eng, 2024; 17(5): 88-95.

Keywords


perior precision, efficacy, efficiency, and yield. Keywords: bio-efficacy, drone spraying, drone-based pest management, precision agriculture, pesticide combinations

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References


INDIASTAT. Rice production and productivity. 2021; Available: https://www.indiastat.com/Home/DataSearch?Keyword=Rice%20Production. Accessed on [2022-08-22].

Mondal D, Ghosh A, Roy D, Kumar A, Shamurailatpam D, Bera S, et al. Yield loss assessment of rice (Oryza sativa L.) due to different biotic stresses under system of rice intensification (SRI). Journal of Entomology and Zoology Studies, 2017; 5(4): 1974–1980.

Peshney N L. Compatibility of fungicides with some insecticides with reference to fungitoxicity and phytotoxicity.Punjabrao Krishi Vidyapeeth Research Journal, 1990; 14: 35–37.

Faical B S, Freitas H, Gomes P H, Mano L Y, Pessin G, de Carvalho A C P L F, et al. An adaptive approach for UAV-based pesticide spraying in dynamic environments. Computers and Electronics in Agriculture, 2017; 138: 210–223.

Tudi M, Daniel Ruan H, Wang L, Lyu J, Sadler R, Connell D, et al. Agriculture development, pesticide application and its impact on the environment. International Journal of Environmental Research and Public Health, 2021; 18(3): 1112.

Report 2021, Joint FAO/WHO meeting on pesticide residues. 2021; Available: https://openknowledge.fao.org/server/api/core/bitstreams/fad4f84a-d748-4d2a-bbef-1db01ac371dd/content. Accessed on [2022-10-05].

Chen C C, Li S G, Wu X Y, Wang Y X, Kang F. Analysis of droplet size uniformity and selection of spray parameters based on the biological optimum particle size theory. Environmental Research, 2022; 204: 112076.

GOI. Crop specific standard operating procedure (SOP) for the application of pesticides with drones. 2021; Available: https://farmech.dac.gov.in/New_Folder/TTC_SOP_2023-4.pdf. Accessed on [2022-07-05].

Anonymous, ET Government, Drone Ki Udaan. 2023; Available: https://government.economictimes.indiatimes.com/news/defence/drone-ki-udaan-will-train-15000-womens-self-help-groups-to-operate-drones-says-pm-modi/102743652. Accessed on [2023-08-15]

Anonymous, ANI News service, To fast track agri-drone adaptation. 2022; https://theprint.in/india/to-fast-track-agri-drone-adoption-centre-approves-477-pesticides-for-drone-usage/922920. Accessed on [2022-05-18].

Varma N R G, Babu T K, Ramprasad B, Ashwini D, Reddy T R, Sudhakar C, et al. Autonomous drones in agriculture: standard operating protocols for agrochemical application in field crops. Hyderabad: Professor Jayashankar Telangana State Agricultural University Press, 2022; Available: https://pjtsau.edu.in/files/notifications/2023/Circulars/sops-drone-pesticide-application-rice-pjtsau.pdf. Accessed on [2023-08-15]

Chanu T M, Ray D C. Comparative efficacy of different conventional pesticides against yellow stem borer under field condition on rice in Cachar district of Assam. Environment and Ecology, 2015; 33: 823–826.

IRRI, Title. Standard Evaluation System in Rice, 2014. Available: http://www.knowledgebank.irri.org/images/docs/rice-standard-evaluation-system.pdf. Accessed on [2022-06-08].

Rajeswaran J, Santharam G, Chandrasekaran S. Studies on compatibility and phytotoxicity of carbosulfan 25 EC with certain agrochemicals on cotton. Journal of Entomological Research, 2004; 28(3): 247–252.

Wang G B, Li X, Andaloro J, Chen P C, Song C C, Shan C F, et al. Deposition and biological efficacy of UAV-based low-volume application in rice fields. International Journal of Precision Agricultural Aviation, 2020; 3(2): 65–72.

Cox D, Gomez K A, Gomez A A. Statistical procedures for agricultural research. John New York: Wiley and Sons. 1984.

Sheoran O P, Tonk D S, Kaushik L S, Hasija R C, Pannu R S. Statistical software package for agricultural research workers. In Hooda D S (ed.). Recent Advances in information theory, Statistics & Computer Applications. Haryana: Hasija Department of Mathematics Statistics, Haryana Agricultural University. 1998; pp.139–143.

Wang C L, He X K, Liu Y, Song J, Zeng A. The small single-and multi-rotor unmanned aircraft vehicles chemical application techniques and control for rice fields in China. Aspects of Applied Biology. 2016; 132(3): 73–81.

Li J, Chen W T, Xu Y, Wu X M. Comparative effects of different types of tank-mixed adjuvants on the efficacy, absorption and translocation of cyhalofop-butyl in barnyard grass (Echinochloa crusgalli [L.] Beauv.). Weed Biology and Management, 2016; 16(1): 80–89.

Wang J, Lan Y B, Zhang H H, Zhang Y L, Wen S, Yao W X, et al. Drift and deposition of pesticide applied by UAV on pineapple plants under different meteorological conditions. Int J Agric & Biol Eng, 2018; 11(6): 5–12.

Chen S D, Lan Y B, Li J Y, Zhou Z Y, Liu A M, Mao Y D. Effect of wind field below unmanned helicopter on droplet deposition distribution of aerial spraying. Int J Agric & Biol Eng, 2017; 10(3): 67–77.




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