Economic Effects of Drone Usage in Plant Protection: Comparison
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Please note this is a comparison between Version 2 by Camila Xu and Version 1 by Aleksandar Ivezić.

Drones equipped with thermal cameras can detect temperature differences in plants, which can be an early indicator of pests or diseases.

  • climate smart agriculture
  • biocontrol agents
  • drones
  • legislative

1. Introduction

The Western Balkans region covers an area of approximately 218,800 km2 and includes the Republic of Serbia, Albania, Bosnia and Herzegovina, Montenegro, and the Republic of North Macedonia. Agriculture is a significant economic sector in Western Balkans, representing a share of nearly 10% of the gross domestic product (GDP), owing to its favorable agro-ecological conditions (https://agriculture.ec.europa.eu/, accessed on 7 August 2023). As in many Western Balkan countries (WBC), almost half the population live in rural areas. Officially, almost one fifth of the workforce is employed in agriculture. In recent years, the share of agriculture in Serbia’s GDP has increased and is now twice as high as that of the new EU members from Central and Eastern Europe (www.stat.gov.rs/en-us, accessed on 12 April 2023). Crop production accounts for the largest share of the value of agricultural production, comprising around 67% [1]. The primary economic crops cultivated in WBC are corn, wheat, sunflower, sugar beet, and soybeans [2]. However, the current use of approximately 8.6 million hectares of agricultural land, while providing significant economic benefits, also results in many unintended consequences (https://agriculture.ec.europa.eu/, accessed on 7 August 2023). Large areas of crop cultivation are very conducive to the reproduction of certain pests, which are tropically closely related to specific crops and cause large economic losses in food production [3]. To reduce these losses, pest control management includes various methods and techniques that prevent the action or minimize the impact of agricultural pests. Due to their relatively low cost and ease of application, chemical insecticides are still the main method of pest control used in WBC, despite being proven to impact negatively on the environment. Excessive use of insecticides can lead to residues in crop yields, which can have direct or indirect impacts on human health through the food chain. Moreover, the drift of pesticides during their application or runoff can be toxic to a range of organisms in the soil, waterways, and beyond, including birds, fish, and beneficial insects [4].
As the scale and production of agriculture reach new global records, society’s environmental awareness is, fortunately, also on the rise [5]. In modern and environmentally conscious societies, there is a growing demand for high-quality food production without the presence of pesticide residues and other harmful substances. There is also an ecological issue underlying the use of renewable energy sources and the preservation of natural resources and the environment. The modern trend of sustainable agricultural production imposes the need to change the technological process of production with the application of techniques and the usage of tools that pollute the environment less and contribute to health security in general [5]. Numerous studies and social initiatives are calling for conversion to more sustainable agricultural practices due to their favorable effect on ecosystems, biodiversity, and human health [6]. An approach that supports such initiatives is the concept of agricultural management based on the application of information technologies in agriculture, also known as precision agriculture [7]. Precision agriculture, or precision farming, can be defined as a process of agricultural production that includes the application of information technologies and various types of sensors, satellite navigation, the monitoring of working machines, the analysis of collected data, and the decision-making process [7]. Such an approach has clear advantages for optimizing production efficiency and increasing quality, as well as for minimizing environmental impact and risk. In the field of precision agriculture, one tool is gaining popularity due to its versatility and applicability in different environmental and working conditions. This particular interest has recently been devoted to the use of lightweight unmanned aircraft systems (UAS) or unmanned aerial vehicles (UAVs), also known as drones, which were originally developed for military purposes but are now frequently used in civil and research applications. In the last 20 years, the use of drones in different natural resource sectors has increased, including environmental biology, agriculture, agroforestry, and forestry [8,9,10,11,12][8][9][10][11][12]. The use of drones in various areas of industry is growing rapidly, which consequently leads to their development. The trend for further improvements of drones in the agri-food sector, along with the automatization of agricultural production, has also been recognized and exploited by the research and business communities [13]. The first reports of drones in agriculture appeared around 1998, and their numbers have grown dramatically in the last decade. Until 2020, the global drone market value was around USD 6.8 billion, and it is expected to reach a value of USD 14.3 billion by 2028 [11]. In agriculture, UAS can not only improve the speed and efficacy of pest monitoring, but they may also be invaluable to pest management as a less expensive means of targeted application of insecticides, biocontrol agents, or even sterile insects to disrupt pest reproduction [11]. In terms of its effectiveness, even the United Nations recently highlighted the potential benefits of UAS use in agriculture for monitoring and protecting agriculture, forest, and fishery resources [14].

2. Economic Effects of Drone Usage in Plant Protection

Recently, drones have become increasingly popular for personal and professional use in all areas of society and the economy. Their professional usage is more obvious in advanced countries, while in developing countries, the use of drones is more often present in scientific and research work. The situation is quite similar in plant protection management, where drones gain an important purpose primarily due to their ability to access hard-to-reach areas and cover large areas quickly and efficiently [15,16,17][15][16][17]. One of the main advantages of drones is their ability to access areas that may be difficult or dangerous for humans to reach. This can be particularly useful for monitoring and protecting trees in forests or orchards, as well as for monitoring crops or medicinal and aromatic plants (MAPs) in hilly or mountainous regions. In plant protection, drones can be used to collect data and monitor plant health, as well as detect and address pests and diseases. In addition to monitoring and detecting problems, drones can also be used to apply pesticides and other plant protection products, such as biocontrol agents. Using drones for this purpose can be more time efficient and environmentally friendly than traditional methods, as it reduces the amount of chemicals needed and the risk of over-application [11]. One of the main advantages of using drones for plant protection is their ability to monitor large areas in a short amount of time. Drones equipped with thermal cameras can detect temperature differences in plants, which can be an early indicator of pests or diseases. Similarly, drones equipped with hyperspectral cameras can also detect changes in the chemical composition of plants, which are most likely indicators of numerous problems such as diseases or a lack of water [18]. Drone images in combination with land data play a pivotal role in precision agriculture, offering ample opportunities for scientific research and development. These technologies provide valuable insights and enable more precise and efficient agricultural practices [18]. UAS have particularly been applied in fruit growing, viticulture, and vegetable production, where it is necessary to conduct detailed monitoring of plants and the areas of interest are significantly smaller than in crop production. This approach brought new weed control strategies, such as weed mapping, which are based on machine learning and processing large quantities of data collected by drones. With the assistance of appropriate algorithms, pixel recognition, and the adoption of semantic segmentation techniques in plant recognition and leaf classification, these strategies could be used for more precise disease and weed mapping in the future [19,20][19][20]. Using UAV-mounted sensors, farmers can timely capture remote sensing data, which is ideal for capturing a vast volume of raw data that can be used further for assessing plant conditions, including water status, biodiversity estimations, biomass estimation, and vigor assessment [21,22][21][22]. Therefore, drones provide numerous new options and possibilities for fast and easy retrieval of crop state information, which can be the foundation for the future of precise agriculture [23]. When it comes to analyzing the financial dimension of drone spraying in agriculture, two primary cases can be identified: autonomous spraying and service-based spraying. These cases represent two distinct approaches to using drones for crop spraying, each carrying specific economic implications. This analysis, based on a case study taken for Serbia, will not consider the cost of pesticides and water.
  • Autonomous Drone Spraying: Autonomous spraying involves farmers owning and utilizing their own drones for crop spraying. This approach brings benefits such as reduced service costs, greater flexibility in work scheduling, and rapid response in emergencies. However, challenges include the initial costs of acquiring the drone and technical training. Additionally, maintaining the drone requires additional resources. The cost depends on the drone model used and the necessary accompanying equipment for that specific model. For the purpose of a general economic analysis, the example of the DJI Agras T30 drone will be considered, currently widely used in Serbia. Costs associated with autonomous spraying include fuel for the generator, fuel for transporting the drone (e.g., by car with a trailer) to the field, and costs allocated for drone depreciation. To charge the DJI Agras T30 drone battery during operation, an approximate 9.5 kW generator is required. In the case of a gasoline generator, fuel consumption ranges from 0.4–0.5 L/ha of treated land. According to the Price List of Machinery Services for 2023 published by the Cooperative Union of Vojvodina [24], which will be used as a reference for this analysis, the average price of 1.62 €/L of unleaded gasoline with 100 octanes. Based on this calculation, the cost of fuel consumed during battery charging while spraying ranges from €0.64–0.80 L/ha. According to current market conditions, an approximate depreciation cost of 7.5 €/ha can be considered [24]. Therefore, excluding costs of water, pesticides, drone transport, and pesticide solution to the treated field, as well as labor costs, the cost of operating the DJI Agras T30 crop spraying drone can be estimated at 8.22 ± 5% €/ha.
  • Service-Based Drone Spraying: Service-based spraying involves farmers hiring professional service providers who use their drones for crop spraying. This approach eliminates initial costs of drone procurement and training, provides expertise from service providers, and allows scalability based on the treated area. However, service costs can be a significant factor, along with dependence on service availability and lack of direct control over spraying timing. The cost of annual formation of spraying services in Serbia can be compared with the Price List of Machinery Services for 2023 published by the Cooperative Union of Vojvodina [24].

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