Potentials and bottlenecks of using drones in agriculture

Drones have the potential to modernize the way we do agriculture. The use of drones in agriculture is already widespread worldwide for numerous applications, including surveillance, field survey, crop scouting, spraying, and spreading applications.

These remotely piloted aircraft systems (RPAS), which are either remotely controlled over wireless communication or programmed to travel the predefined path using navigation algorithms running on onboard controllers, are designed to carry payload such as cameras and sensors with digital imaging capabilities that can provide real-time, accurate information about the crop status, that can lead to an efficient decision-making process.

Using this data, farmers can precisely calculate their land sizes, classify crop types and verities, develop an understanding of soil conditions, plant health, and crop yield prediction, along with pest management, disease control, irrigation, and fertilization, and adequately plan the harvesting of their crops. This improves the scale of operation and productivity and replaces labor-intensive and hazardous conventional methods.

Potentials

  • Soil analysis for field planning: Drones can be used for soil and field analysis for irrigation, planting planning, and nitrogen level in the soil. Along with this, the drone helps produce accurate 3-D maps that can be used to conduct soil analysis on soil properties, moisture content, and soil erosion.
  • Crop monitoring: Crop monitoring is the biggest headache for farmers and various other stakeholders associated with agriculture operations. This challenge has also worsened with the rise of unpredictable weather patterns, leading to rising crop loss risks and maintenance costs. Drones can be used to set their monitoring routes by gathering multispectral geospatial and temporal datasets at pre-defined scales related to crop development and health. Data analytics help in getting insights on crop health much before being visible by manual field scouting.
  • Seed pod planting: Although invented but seldom prevalent just yet, some companies have come up with additional attachment below the drone systems able to shoot pod containing seed and plant nutrients into the already prepared soil. This is helping to reduce planting costs.
  • Crop spraying: Drones can carry suitably sized reservoirs, which can be filled with fertilizers, herbicides, or pesticides for crop spraying on large areas in less time. Crop spraying is much safer and cost-effective by its autonomous and pre-programmed run on specific schedules and routes. Drones are also programmed to self-adjust their altitude and speed using ultrasonic echoing, TOF lasers, and GNSS signals to achieve a uniform and optimum spraying results across varying topography. Smart farms use drones for agriculture spraying, which reduces human contact with fertilizers, pesticides, and other harmful chemicals. Drones are also un-comparable when it comes to spotting treatment automated with stress detection technology, which uses sensors and cameras and works on them while leaving the healthy parts intact. Drones enhance spraying capacity up to five times faster than with traditional machinery.
  • Crop health assessment: Plants reflect visible & near-infrared light, and its intensity varies with health status and stress levels experienced by plants. Drones fitted with sensors capable of scanning crops using visible and near-infrared light can be used to track crop health over time and monitor response to remedied measures.
  • Irrigation: Drones loaded with thermal, multispectral, or hyperspectral sensors can identify the parts of the field with moisture deficits using multispectral indices. This helps in planning timely irrigation to the identified areas with precision.
  • Crop surveillance: It is nearly impossible to estimate the overall state of crops in large fields. Drones based agriculture mapping can help farmers remain area-wise updated on the plants status and point out which field areas require attention. Drones inspect the field with infrared cameras and determine light absorption rates to estimate the state of crops. Based on real-time and accurate information, farmers can improve plants’ condition in any spot of the field. This feature of crop surveillance and crop health assessment also forms the basis of drones’ use for enhancing agricultural insurance tools for cross verifying farmers’ insurance claims.
  • Tree/crop biomass estimation: Crop/tree canopy density and distance from the ground surface can be measured using ultra-compact LiDAR sensors mounted on drones. This enables assessment of the tree/crop biomass change derived from differential height measurements that form the basis for estimating timber production in forest and production estimates in crops like sugarcane.
  • Controlling weed, insect, pest, and diseases: Apart from soil conditions, drones can also detect and inform farmers about field areas inflicted by weeds, disease, and insect pests. Based on this information, farmers can optimize the use of chemicals needed to fight infestations, reducing the expenses, and contributing to better field health.
  • Scaring birds: Birds are the major problem after sowing seeds of many crops. This needs labor to protect the field. A couple of drone flights can scare the birds away from the field.

Bottlenecks

Despite these potentials, drones come with their own challenges and bottlenecks, such as:

  • Flight time and range: Due to relatively higher payloads, the flight duration of drones used in agriculture is short, ranging from 20-60 minutes. This results in limited coverage of land with every charge. The cost of drones increases significantly with the longer flight time.
  • Connectivity: Online coverage is mostly unavailable in arable farms. Under such a situation, any farmer intending to use drones has to invest in connectivity or buy a drone with local data storing capability in a format that can be transferred and processed later.
  • Initial cost: Mostly, agricultural drones used for surveying have fixed wings and may cost up to $25000 (Precision Hawk’s Lancaster) based on features and sensors necessary for executing their intended use. Some drones are costlier as it includes the cost of imaging sensors, software, hardware, and tools. The initial cost is also proportional to the payload and flight duration capacities, apart from sensors and features.
  • Weather dependence: Under windy or rainy conditions, flying drones is not easy, unlike traditional aircraft. Drones are weather dependent.
  • Knowledge and skill: An average farmer cannot analyze the drone images as it requires specialized skills and knowledge to translate them to any useful information. Under these circumstances, the farmer must acquire the skills and knowledge of image processing software or hire skilled personnel conversant with the analysis software.

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