Use of drones in precision pest management

Introduction

Insect pest prevalence in fields, crops, and orchards sometimes shows non-uniform or aggregated regional distributions. There is proof that some pests, like aphids, have their highest population densities near field boundaries (Nguyen and Nansen 2018) [1] . The brown plant hopper concentrates at the base of the rice stem, just above the waterline. Abiotic stressors such as drought and nutrient deficiencies also tend to have higher populations of two-spotted spider mites in fields (West and Nansen 2014) [2] . Therefore, in order to effectively manage pests that are spatially aggregated, precision pest management techniques should be used. Precision pest management is based on making decisions based on precise subfield-scale information about pest infestations instead of pest density averages at the field scale (Naud et al 2020) [3] . Precision pest management yields two key benefits for agricultural sustainability: it reduces the use of pesticides and increases the use of non-chemical techniques targeted at populations in particular sectors of the field. Only implementing control measures in areas and at the times when pest numbers approach economic thresholds is termed as precision pest management (Park et al 2007) [4] . In certain pest management scenarios, precision management may reduce the number of resources required because the spatial distribution of various insects is aggregated (Park et al 2007) [4] . Subfield management zones are the foundation of precision pest management systems. The zones, based on plant development and health, represent uniform field regions. Therefore, the two primary objectives of precision pest management are: (1) identifying plant attack zones by detecting groups of plants that have been attacked by insects (using groundbased, airborne, or orbital remote sensing technologies) and ( 2) implementing localized control measures on plants that have been harmed by insects (natural enemies, pesticide, sterile insects).

Basic technologies like visual inspection and global positioning technology can be used to assess the distribution of insects and damaged plants. Spectral remote sensing has been proposed as a tool to identify damaged plants more recently (Nansen and Elliott, 2016) [5] . In this review paper, we are discussing about use of drones in precision pest management.

What is drone?

Drone means 'dynamic remotely operated navigation equipment'. They can fly autonomously or be piloted remotely and can be expendable or recoverable. A UAV (Unmanned Aerial Vehicle) is a flying device that can fly a pre-set course with the help of an autopilot and GPS coordinates Drones are uncrewed aerial vehicles (UAVs), which are used in various sectors such as, mining, construction and military. In agriculture, they can be applied for analyzing images, ground monitoring, and in-depth situation analysis of a crop. In precision pest management, they are used from detection and delineation of pest injury and pest habitat to delivery of organisms and materials to mitigate pest concerns. Two rotors make up a single rotor; one is small and fixed on the tail, and the other is an additional, oversized rotor on top. A multirotor system can be a quadcopter, hexacopter, octocopter, or tricopter, depending on the number of rotors and intended use. Drones using multiple or a single rotor (helicopters) do not need special infrastructure to take off or land. They can also hover and manoeuvre with agility, which makes them useful in situations (such as pesticide treatments or crop and orchard inspections) when precise movement or the capacity to keep a long-term sight on a target are necessary. Drones with many motors in particular are often inexpensive and simple to operate. Compared to rotor-based systems, fixed-wing aircraft are often bigger and quicker. Drones used for detection of pest hotspots are here referred to as sensing drones, while drones used for precision distribution of solutions are referred to as actuation drones. Both types of drones could communicate to establish a closed-loop IPM solution. Importantly, use of drones in precision pest management could be cost-effective and reduce harm to the environment. Sensing drones could reduce the time required to scout for pests, while actuation drones could reduce the area where pesticide ap plications are necessary, and reduce the costs of dispensing natural enemies.

History of drones in precision pest

Use of Drones in Precision

Pest monitoring

Traditional field scouting for pest infestations is often expensive and time-consuming (Hodgson et al 2004 [6] , Dara 2019 [7] ). When dealing with arthropod pests that are too tiny to perceive with the naked eye, live in the soil, or are found in towering trees, it might be practically difficult. In some farming systems, a deficiency of trustworthy pest sampling methods makes scouting less successful. Using remote sensing technology, precision pest management may be used to monitor crops and detect pest-affected areas. Based on this information, control measures like pesticide spraying can be implemented to avoid infections.

Remote sensing is the detection of energy emitted or reflected by various objects, either in the form of acoustical energy or in the form of electromagnetic energy (including ultraviolet [UV] light, visible light, and infrared light) (Usha and Singh 2013) [8] .

It is a non-invasive, relatively labour-extensive method that could be used to detect plant stress before changes are visible by eye. For crops, remote sensing equipment generally assesses the spectral range of visible light or photosynthetically active radiation (PAR, 400-700 nm) and near infrared light (NIR, 700-1,400 nm), with most studies referring to the 400-1,000 nm range (Nansen 2016) [9] . Particular stressors, such as arthropod infestations, induce physiological plant responses, causing changes in the plants' ability to perform photosynthesis, which leads to changes in leaf reflectance in parts of this spectral range.

Compared to conventional platforms for remote sensing, such as ground-based, aerial (with manned aircraft) and orbital (with satellites such as Landsat [30 m spatial resolution], Sentinel 2 [10 m] or RapidEye [5 m]; Mulla 2013) [10] , Sensing drones are becoming popular for use in precise pest monitoring because of their many benefits. Sensing drones can cover a larger area than portable, ground-based equipment. Because they may travel at lower altitudes than human aircraft and orbital systems, pictures have better spatial resolution and fewer mixed pixels. Moreover, they are less expensive to acquire and deploy than satellites and manned planes, and they may use higher monitoring frequencies due to their shorter revisit times than satellites (Maes and Steppe 2019) [11] . Drones outfitted with RGB (red, green, blue) sensors, hyperspectral sensors (which have hundreds of small spectral bands), or multispectral sensors (which have three to twelve wide spectral bands) can be used for airborne remote sensing. While inexpensive, an RGB sensor only provides a small amount of spectrum information. More spectrum information is produced by a multispectral sensor, but a hyperspectral sensor often distinguishes minute variations in canopy reflectance considerably more clearly than a multispectral sensor. Hyperspectral sensors would, however, need to be mounted on drones designed to carry bigger payloads because they are often larger. Additionally, they are often more costly, and data processing takes more expertise and time, which limits their usage for individual farmers.

In combination, these sensors can give a 3D GPS accurate model of your field and data that the human eye cannot pick up on much less track easily over time. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge (NDRE). NDVI is basically a measure of plant health based on how a plant reflects light at specific frequencies. Healthy plants reflect large amounts of near-infrared light (NIR) where unhealthy plants absorb more. Hence, one of the main drivers for the implementation of dronebased remote sensing technologies into agriculture is the potential time saved by automatizing crop monitoring, making the technology cost-effective for growers.

Pesticide application

Helicopters driven by humans are usually used for aerial spraying. Several restrictions on terrestrial ecosystems are addressed by aerial spraying. They don't require any passageways. Spraying may cover a vast area on a single trip.

There are drawbacks to aerial spraying. The human aircraft must be flown at notably higher heights, which will increase the aircraft's distance from the crop. When pesticides are sprayed from such heights, they are unable to target the insect on the crop, which causes spray drifts that contaminate the environment. (Xue et al 2016) [12] . With this premise, UAVs are being investigated as a safe and high precision alternative for spraying pesticides (Huang et al 2009) [13] . The downwash impact of UAVs aids in directing spray towards crop canopies and plantations even if they are not equipped with pilots. As part of the lifting process, downwash in aeronautics refers to the activity of altering the direction of air diverted by the aerodynamic aerofoil, wing, or rotor in motion. (Yang et al 2018) [14] .

Parameters to be considered in drone for pesticide application

The set operational parameters such as flight speed, height, and endurance need to be optimized to use drones appropriately in agriculture and allied sectors. In addition, parameters related to drone-based spraying such as droplet size, spread, density, uniformity, deposition, and penetrability should also be factored in when implementing drone-based mitigation strategies (Subramanian et al 2021, Zhang et al 2015) [15,16] . Further, meteorological parameters like wind speed, temperature, and relative humidity can affect the efficacy of pesticide sprays under field conditions (Wang et al 2018) [17] . One of the critical factors to be considered for the effectiveness of drone-enabled spray is droplet deposition. The parameters used for measuring the effectiveness of droplet deposition include density, area coverage, and arithmetic mean of droplet size and variation coefficient (Zhu et al 2011) [18] .

Drones for Desert Locust Control in India

• Used for spot application, including high trees, dense plantation and inaccessible areas • 15 drones each equipped with 10 L tank and supplied with eight batteries to treat 1 hectare in 15 min • Flat fan nozzles for spraying a mixture of two insecticides (100-120 ml), 5% lambda-cyhalothrin and 2.8% deltamethrin

Advantages of drones in pesticide application

• To reduce spray drift • To make it easy for pesticide application in large areas • To make it convenient for pesticide application in areas where labour is costly or not available

• To reduce amount of pesticide used • To reduce time taken in pesticide application • To ensure safety of the operator

Release of Biological Control Agents

An environmentally friendly substitute for the use of pesticides is biological control. According to Van Lenteren et al. (2018) [17] , augmentative biological management, which depends on the widespread release of natural enemies to provide instant pest control, may benefit greatly from the deployment of drones. By distributing the natural enemies precisely where they are required, they may improve the effectiveness of biocontrol agents and cut down on distribution expenses. The suggested method of dispersing Phytoseiulus persimilis, an essential natural opponent of the two-spotted spider mite, is to sprinkle the contents onto individual plants. The plant material is available in bottles combined with the mineral substrate vermiculite. Trichogramma species are commonly used to combat the European corn borer, a significant pest of sugarcane and sweet corn.

Release of Sterile Insects

A potential new area for use of drones in pest management is the release of sterile insects. Codling moth (Cydia pomonella) is a major problem in apple orchards (Judd and Gardiner, 2005) [20] , and pilot programs to release sterile insects with drones have been successful in controlling codling moth populations in New Zealand, Canada, and the United States (Timewell, 2018) [21] . Through irradiation, the sterile insect technique (SIT) creates sterile or partially sterile insects. There are either no offspring or sterile offspring after mating with wild insects, which lowers pest numbers. SIT is a crucial IPM strategy since it is speciesspecific, ecologically harmless, and works well with other management techniques like biological control (Simmons et al 2010) [22] . Drone release of the sterile insects may be cheaper and faster than ground release, which occurs for instance by means of all-terrain vehicles, or release by manned aircraft (Tan and Tan, 2013) [23] .

Advantages of drones

Future thrust

There is need to study the compatibility of different formulations for spraying, along with pesticide effects on non-target organisms. There should be awareness promotion and demonstrations of drones in rural areas. Multi-disciplinary research with collaboration of agricultural scientists and engineers should be there. There is need to develop software programs to diagnose specific insect pests and for data analysis.

References

1. Nguyen HDD, Nansen C. Edge-biased distributions of insects: A review. Agronomy for Sustainable Development. 2018;38:11.
2. West K, Nansen C. Smart use of fertilizers to manage spider mites (Acari: Tetranychidae) and other arthropod pests. Plant Science. 2014;1:161-164.
3. Park YL, Krell RK, Carroll M. Theory, technology, and practice of site-specific insect pest management. J Asia Pac Entomol. 2007;10:89-101.
4. Nansen C, Elliott N. Remote sensing and reflectance profiling in entomology. Annu Rev Entomol. 2016;61:139158.
5. Hodgson EW, Burkness EC, Hutchison WD, Ragsdale DW. Enumerative and binomial sequential sampling plans for soybean aphid (Homoptera: Aphididae) in soybean. J Econ Entomol. 2004;97:2127-2136.
6. Dara SK. The new integrated pest management paradigm for the modern age. J Integr Pest Manag. 2019;10:12.
7. Usha K, Singh B. Potential applications of remote sensing in horticulture: A review. Scientia Horticulturae. 2013;153:71-83.
8. Nansen C. The potential and prospects of proximal remote sensing of arthropod pests. Pest Manag Sci. 2016;72:653659.
9. Mulla DJ. Twenty-five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps. Biosyst Eng. 2013;114:358-371.
10. Maes WH, Steppe K. Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture. Trends Plant Sci. 2019;24:152-164.
11. Xue X, Lan Y, Sun Z, Chang C, Hoffmann WC. Development of an unmanned aerial vehicle-based automatic aerial spraying system. Comput Electron Agric. 2016;128:58-66.
12. Huang H, Deng J, Lan Y, Yang A, Deng X, Zhang L, et al. A two-stage classification approach for the detection of spider mite-infested cotton using UAV multispectral imagery. Remote Sens Lett. 2018;9:933-941.
13. Yang S, Yang X, Mo J. The application of unmanned aircraft systems to plant protection in China. Precision Agric. 2018;19:278-292.
14. Subramanian KS, Pazhanivelan S, Srinivasan G, Santhi R, Sathiah N. Drones in insect pest management. Front Agron. 2021;3:640-685.
15. Zhang SC, Xue XY, Qin WC, Sun Z, Ding SM, Zhou LX. Simulation and experimental verification of aerial spraying drift on N3 unmanned spraying helicopter. Trans Chin Soc Agric Eng. 2015;31:87-93.
16. Wang J, Lan YB, Zhang HH, Zhang YL, Wen S, Yao WX. Drift and deposition of pesticide applied by UAV on pineapple plants under different meteorological conditions. Int J Agric Biol Eng. 2018;11:5-12.
17. Zhu H, Salyani M, Fox RD. A portable scanning system for evaluation of spray deposit distribution. Comput Electron Agric. 2011;76:38-43.
18. Van Lenteren JC, Bolckmans K, Köhl J, Ravensberg WJ, Urbaneja A. Biological control using invertebrates and microorganisms. Biol Control. 2018;63:39-59.
19. Judd GJR, Gardiner MGT. Towards eradication of codling moth in British Columbia by complementary actions of mating disruption, tree banding and sterile insect technique: five-year study in organic orchards. Crop Prot. 2005;24:718-733.
20. Timewell E. Dropped in for fruitless sex. The New Zealand Institute for Plant and Food Research; 2018. Available from: https://www.plantandfood.co.nz/page/news/media_release/s tory/dropped-in-for-fruitless-sex/
21. Simmons GS, Suckling DM, Carpenter JE, Addison MF, Dyck VA, Vreysen MJB. Improved quality management to enhance the efficacy of the sterile insect technique for lepidopteran pests. J Appl Entomol. 2010;134:261-273.
22. Tan LT, Tan KH. Alternative air vehicles for sterile insect technique aerial release. J Appl Entomol. 2013;137:126141.