Recent Development Trends in Plant Protection UAVs: A Journey from Conventional Practices to Cutting-Edge Technologies—A Comprehensive Review

Abstract

Uncrewed aerial vehicles (UAVs) for plant protection play a vital role in modern agricultural operations. In recent years, advancements in UAVs and pest control technologies have significantly enhanced operational efficiency. These innovations have addressed historical challenges in agricultural practices by improving automation and precision in managing insect pests, diseases, and weeds. UAVs offer high operational efficiency, wide adaptability to different terrain, and safe applications. The development and demand for these technologies have increased to boost agricultural production. In agricultural settings where conventional machinery struggles to carry out farming operations, UAVs have transformed farming practices by providing high operational efficiency and significant profitability. The integration of UAVs and other smart technologies has driven advancements. The UAV sector has received substantial attention as a convergence of production, service, and delivery, introducing synergy through the presence of several developing areas. The market for this technology is expected to grow in the future. In this comprehensive review, we analyzed an overview of historical research, diverse techniques, the transition from conventional to advanced application, development trends, and operational milestones across diverse cropping systems. We also discussed adoption and subsidy policies. In order to properly understand UAV operational efficiency, we also analyzed and discussed smart atomization systems, spray drift, droplet deposition detection technologies, and the capabilities of related technologies. Additionally, we reviewed the role of software programs, data-driven tools, biodegradable materials, payloads, batteries, sensing technologies, weather, and operational and spraying factors. Regulatory limitations, operating and farmer’s training, economic effects, and guidelines were also acknowledged in this review. This review highlights deficiencies and provides essential knowledge of the use of UAVs for agriculture tasks in different regions. Finally, we examine the urgency of UAV technology implementations in the agricultural sector. In conclusion, we summarize the integration of UAVs and their related technologies with applications and future research prospects, offering directions for follow-up research on the key technologies of UAVs and encouraging the enhancement of agricultural production management in terms of efficiency, accuracy, and sustainability.

1. Introduction

Plant protection has undergone an immense transformation through the centuries, transitioning from basic manual techniques to cutting-edge strategies leveraging uncrewed aerial vehicles (UAVs). Historically, traditional practices such as handpicking pests and using sulfur were common. The old-time improvements in crop rotations, as well as companion planting, boosted pest and disease management [1]. The 19th century saw significant strides with the introduction of chemical pesticides and mechanical sprayers, resulting in much better efficiency in controlling pests. Modern development has revolutionized plant protection, enabling precise application of pesticides, real-time monitoring of plant health, and enhanced detection of pests and diseases [2]. These technologies not only enhance the effectiveness but also minimize environmental impacts while promoting sustainable farming methods. UAVs provide operational efficiency and adaptability to vast areas, which is critical for satisfying growing global nutritional demands amid challenges, including climate change and pest resistance [3]. Innovations like object detections, variable rate spraying technology, and smart atomization systems further optimize the use of pesticides and reduce drift, ensuring environmental and crop safety [4,5]. Recent technological advancements have introduced sophisticated tracking and inspection approaches, encompassing IoT and remote sensing technologies that facilitate active identification of pests and efficient administration [6,7,8,9]. These progressions assist in preventing plant infestations and significantly reducing crop losses, aiding in mitigating issues posed by diminishing arable land and changing climate patterns [10,11].

Several studies have demonstrated the effectiveness of UAVs in plant protection. Ahale et al. [12] found significant improvements in key technologies such as precision navigation, autonomous flight control, variable rate spraying, and multispectral imaging to achieve accurate pesticide spread over crops. Etezadi & Eshkabilov [13], it was highlighted that new UAVs are being implemented in large-scale agriculture operations to support farming, with legal structures established to ensure secure operating requirements. Adetunji et al. [14] reported technologies such as UAV design and miniaturization, AI data analytics, and batteries, which are making them faster, better, and stronger. This leads to future trends of automation, IoT interaction, sustainability, and the ability to customize based on a range of farm sizes as emphasized by He [15]. Furthermore, Khan et al. [16] discussed that tackling adoption barriers such as cost, and expertise will be key to ensure widespread use of UAVs. Commitment to long-term R&D will fuel innovation, especially in AI and sustainability.

Emerging UAV capabilities in agriculture encompass revolutionary developments in automated flight direction, extended battery lifespan, elevated payload capacity, and intelligent systems, exponentially boosting their flexibility and efficiency in industry assignments. Continuous scientific research and groundbreaking innovation in UAV engineering drive the rapid development of the agricultural sector, with present investigations focusing on refining functional and spreading arrangements to remarkably increase phytosanitary product performance and decrease unintended waste. This progressive shift from traditional practices to UAV-centered alternatives represents a major smart technological breakthrough in plant protection, offering novel views and understandings for stakeholders across the agricultural provision chain. This paper also underlines the significant role of sustained research advancement, interdisciplinary approach, and regulation as enhancers of UAV–agricultural-related integration. This initiative aims to guarantee food safety, advance best agricultural practices, and promote cohesion between ministries in compliance with legislation [17].

At present, there is still a lack of research on the development status and key technologies of UAVs. Many studies have shown the increasing influence of disease, insect pests, and weeds on worldwide crop yields [18]. Annually estimated losses due to these pest and disease problems are around 20–40%. This study acknowledges the pivotal research that has significantly contributed to UAV applications in plant protection. It compiles literature on the history, development, adoption, sensing technologies, constraints, incentives, benefits, and operational parameters of UAVs. Following this, the findings are analyzed, leading to research breakthroughs, policy implications, guideline updates, and recommendations for future pathways. Ultimately, this review concludes by outlining potential prospects and emphasizing the pivotal role of research in shaping industry direction. A systematic review of the intersection between existing UAVs and agricultural research was conducted. This paper can be seen as a valuable addition to the literature as it explores a new technology that is very important for developing countries like Asia and the Pacific, and that has the potential to reshape many dimensions of this sector. Also, the literature related to agricultural UAVs should be properly grouped and classified, paying attention to the most relevant and influential studies in the field of plant protection.

2. A Historical Voyage through Agriculture’s Status and Innovations

2.1. Evolutionary Journey of UAVs in Agriculture Development across Decades

Agriculture has a long history of innovation, and UAVs have quickly revolutionized the industry by providing growers with an overall picture of their fields to make data-driven decisions that will maximize yields. Innovative tools available today offer a level of flexibility previously unseen, empowering farmers to actively monitor, manage, and enhance their crops through various benefits, including yield optimization, economic incentives, and long-term land use sustainability. In 1951, China began building large agricultural aircraft. Thousands of rotorcraft (airplanes) and forestry-specific planes have been utilized for agricultural purposes. Large helicopters and fixed-wing aircraft were developed to spray pesticides, manage diseases and pests, and control weeds [1,19]. These vehicles are faster and more efficient to operate, covering millions of hectares. When China released its 863 National Plan in 2008, the Ministry of Agriculture and Science and Technology drafted a plan to develop single-rotor uncrewed aerial vehicles (UAVs) for pesticide applications. Recent UAV research has revealed tremendous technological innovations that have significantly reduced crop diseases and insect infestations [12,13,14,15,16]. In 2013, in response to these outcomes, the Ministry of Agriculture announced a national plan for the development of UAV technologies. As a result, agricultural UAVs were categorized as machinery for farming subsidies by the provincial governments of Jiangsu, Guangdong, Fujian, Shandong, Henan, and other provinces [8]. The No. 1 Central Document of 2014 called for the development of agricultural aviation infrastructure, driving Chinese industry experts to draft a joint initiative aimed at promoting the growth of commercial UAVs in agriculture. The initiative was presented to the State Council and the Ministry of Science and Technology. In 2015, the Chinese provinces of Hunan and Henan launched subsidies for UAV operations. Several Chinese agricultural UAV enterprises received private financing, leading to further refinement and promotion of UAVs. By the end of 2022, China developed more than 300 kinds of agricultural UAVs, with about 80,000 operational units covering millions of hectares [20,21].

2.2. From Dust to Sky: The Evolutionary Leap in Agriculture

In agriculture, plant protection is vital for sustaining crop health and yield in the face of pests, diseases, and adverse environmental conditions. Over the decades, technologies have evolved from outdated methods to cutting-edge innovations, significantly enhancing effectiveness and productivity (Figure 1).

China has historically relied on traditional methods including manual labor, chemical pesticides, and mechanical equipment, which have shown some effectiveness but also pose risks such as environmental pollution, health hazards, and pest resistance. China is now transitioning towards more sustainable practices in response to concerns about environmental degradation, resource conservation, food safety, public health, and the need to minimize chemical use in agriculture [22]. By integrating modern innovations such as GPS and sophisticated sensors with UAVs, growers can obtain real-time data on pests, diseases, and crop health. In China, UAV technology has altered plant protection strategies [23]. Additionally, UAV technology has increased output and reduced environmental impact (Figure 1). China, once a technology follower, has emerged as a global industry leader, securing the top position in terms of control area and number of UAVs [24,25,26]. Recent UAV research and development focus on drift-reducing technologies, plant pollination, soil moisture data optimization, and precise phytosanitary operations [27]. In addition, seed distributors assist in sustainable forest plantings and ensure security for workers in remote locations by utilizing advanced sensors for assessing soil nitrogen contents. For example, ten UAVs can plant several thousand trees per day [28,29]. UAVs with advanced cameras and spraying technologies can be used by growers to accurately monitor the health of crops, identify insect infestations, and apply targeted treatments [29]. This reduction in chemical use has made farming more efficient. A major positive development in agricultural technology in China is the application of integrated pest management (IPM), an approach that reduces reliance on chemical compounds, improves biodiversity, and enhances crop resilience. [30]. With skills training in analyzing data, plotting, and planning operation paths, UAVs can help small farmers to identify plant patterns or find diseases. This allows them to protect crops without the need for manual spraying, while also ensuring compliance with the regulations specific to their country [17,31,32]. The Chinese government has introduced incentives for sustainable agriculture, including support for research on green technologies and subsidies for organic farming methods [33]. China has encountered obstacles in achieving sustainable agriculture and production, such as inadequate farmer knowledge, insufficient research infrastructure, and reluctance to adopt new practices [34,35]. However, these constraints suggest the potential for cross-disciplinary contributions by agencies, academia, industry, and farmers [36,37]. IPM, precision agriculture, and eco-friendly solutions can provide food security, environmental sustainability, and resilience. Further progress and the future prosperity of Chinese agriculture will be greatly enhanced by continued investments in research, innovation, and capacity building.

2.3. Classifications of Plant Protection UAVs

UAV technology has significantly advanced agricultural research due to its rapid environmental sensing capabilities. Plant protection UAVs are classified based on their size and source of energy, with the primary types being fixed-wing and multi-rotor UAVs. A wide range of models with varying specifications is available on the market. Kim et al. [38] discussed the critical classification based on size ranging from micro to large UAVs. Most growers use small UAVs for limited ranges, primarily for crop health inspection, pest and disease detection, and spraying. Brewster et al. [39] UAVs have been used to enable growers to collect real-time data during the early stages of crop development and to perform spraying tasks efficiently. Conversely, large UAVs have powerful capabilities, allowing them to cover extensive agricultural areas and transport heavy payloads for spraying applications (see Section 5.2). UAVs can be classified using several methods (Figure 2). In terms of energy sources, UAVs are categorized into electric, fuel, and hybrid. Additionally, UAVs can be classified as single-rotor, multi-rotor, or fixed-wing [40]. Approximately 70% of UAVs use batteries as their energy source. The endurance duration of these batteries has gradually increased from 12 min in 2014 to over 25–30 min today, depending on the payload. Rotors on UAVs play a crucial role in energy efficiency and consumption. Gas-operated UAVs offer longer durability compared to electric UAVs, providing excellent range and substantial transportation capabilities. However, electric UAVs are more convenient, economical, and eco-friendly. Gas-operated UAVs are noisy, costly, and produce significant emissions. In contrast, multi-rotor UAVs are cost-effective, adaptable, and less disruptive, making them suitable for small field operations. Additionally, the payload capacity of UAVs has increased from 12 kg to 90 kg.

China currently possesses over 293 types of UAVs. Among them, 1% are fixed-wing types, approximately 29% are single-rotor types, and 74% are multi-rotor types [7,13]. Of these, 18% are gas-operated; however, 80% are powered by batteries, and only 2% are hybrid [41]. UAV operations are sustainable with higher efficiency. The smart atomization system generates a wide range of droplets according to the application requirement, ensuring uniform coverage. Meanwhile, droplet adherence and absorption are enhanced by the electrostatic charge technique used in electromagnetic sprayer UAVs [42]. Notable UAV manufacturing companies in China include Hanhe, (Wuxi, Jiangsu), XAG (Guangzhou), Quanfeng (Anyang, Henan), Hi-tech (Beijing), and DJI (Shenzhen, Guangdong). These local manufacturers, based in various provinces, are well-established and highly reputable, renowned for their high standards in the UAV industry. DJI and XAG contribute to over 80% of UAV sales in China. Multi-rotor UAVs are anticipated to continue their market leadership due to their reliability, cost, payload, and significant benefits regarding safe and efficient operations. UAVs can help to minimize chemical usage, improve crop yields, and promote sustainable practices. As technology develops, additional improvements are expected, paving the way for a greener future.

2.4. Mapping the Current Terrain of Plant Protection

Traditional methods in plant protection practices are deeply rooted in time-tested agricultural practices and sculpted meticulously by local environmental nuances and age-old cultural traditions. China has one of the largest agricultural sectors in the world, producing a wide variety of crops. Farmers face significant challenges in pest management, resulting in substantial yield losses and threatening crop security due to ongoing farming practices and periodic outbreaks of pests and diseases. Current research focuses on pest and disease-resistant crop varieties, genetic engineering, and precision agriculture technologies to mitigate disease risks. Technological innovation is increasingly important in transforming China’s agricultural sector. The Chinese government has prioritized agricultural modernization and rural revitalization, increasing productivity, promoting sustainable practices, improving infrastructure, and enhancing rural livelihoods. Key policies include the “Rural Vitalization Strategy” and the “Belt and Road Initiative” [43]. Despite progress, China’s agricultural sector faces several challenges, including land degradation, water scarcity, rural poverty, various pest-related challenges, and rapid environmental changes [44]. China’s rural population is aging, resulting in a shortage of agricultural labor. Advanced automation is in demand in the current era [45]. The demand for UAVs increased in 2014 due to their compatible design and costs. The quantity surged from over 4000 in 2016 to 160,000 in 2021, while the operational area increased from 6.67 million hectares in 2017 to 93.3 million hectares in 2021. According to the Chinese Civil Aviation Administration, 832,000 UAVs were registered in 2021, with 160,000 assigned for plant protection [46,47,48,49]. The overall development rate of the industry stands at 80% [50]. Figure 3 shows that the number and coverage area of UAVs in China has increased significantly over the last 8 years. The market is projected to experience a growth of over 50–60% in the upcoming period, which is expected to encompass 200,000 units and cover an operational area exceeding 133 million hectares. China’s collaboration and innovation in plant protection involve government agencies, research institutions, farmers, and industry stakeholders, fostering new pest control methods, crop varieties, and sustainable agricultural practices [50].

2.5. The Role and Impact of UAVs in Modern Agriculture and Scientific Research

Over the past twenty years, UAV, advancements have garnered significant academic interest across various fields, including engineering, computer science, environmental studies, and urban planning. UAVs are essential tools for remote sensing, data collection real-time monitoring, biodiversity, and precision agriculture. Their capability to access remote areas and collect high-resolution data makes them valuable in scientific research, promoting interdisciplinary collaboration among scientists, engineers, and policymakers [51]. UAVs function based on core principles of aerodynamics and control systems, utilizing advanced sensors and computational algorithms to ensure stability, maneuverability, and autonomous operation. UAVs have transformed data collection and monitoring across numerous disciplines, demonstrating their versatility and extensive range of applications. As illustrated in Figure 1, Figure 3 and Figure 4, the adoption of new technologies resulted in a significant transformation. UAVs allow growers to collect real-time data on crop health, nutrient deficiencies, and pest and disease infestations, facilitating timely and targeted interventions [52]. Additionally, UAVs can precisely apply pesticides, fertilizers, and other phytosanitary products using variable rate application (VRA) technology. This precision reduces chemical drift, impacts on non-target organisms, and environmental contamination. Enhanced pest control efficiency provides access to dense regions or difficult terrains [53]. Thermal and hyperspectral sensors in UAVs enable early detection and monitoring across various agricultural settings. These advanced sensors can detect subtle changes in plant metabolism and temperature, allowing growers to respond quickly and prevent significant damage. Continuous UAV surveillance provides real-time data, supporting predictive strategies for effective management. These data enable growers to manage pests and diseases efficiently in crops, orchards, and forests, ensuring timely and effective interventions [54]. These techniques additionally create complete farm simulations for resources, organization, and farming technique promotion. Moreover, these techniques offer statistics, direction, and recommendations for maintaining pesticide vigilance and compliance. UAVs can help to monitor and maintain environmental protection by assessing farming impacts on biodiversity and soil conditions. Additionally, recognizing regions that need improvements and promoting resilience to change helps in restoring habitat [55,56]. Operators can use data gathered by UAVs to improve their farming operations through robotic decision-making tools and information capabilities. Artificial intelligence systems help operators make intelligent choices regarding cultivation and pest control by integrating prior crop outcomes with weather predictions. By integrating these sophisticated technologies, UAVs have revolutionized agricultural practices, leading to enhanced productivity, sustainability, and overall efficiency in farming operations.

3. Adoption Trends in Plant Protection UAVs

The adoption of UAVs in plant protection has greatly increased worldwide due to the benefits of technological advances and sustainable solutions for agricultural production. China is a global leader in UAV utilization for pest control and field management through extensive government funding as well as the strong commitment of the Chinese industry to cultivate innovation-minded ag-tech entrepreneurs. UAV technology is becoming increasingly popular in agriculture in industrialized countries such as the United States. Farmers are using UAVs in precision agriculture to improve crop monitoring and targeted pesticide applications. In Europe, countries such as Germany and France are utilizing drone technology as part of precision agriculture, complemented by an evolving regulatory environment to ensure the safe and effective use of UAVs. Australia is using UAVs to manage large-scale agricultural production, especially in remote areas where traditional methods are less practical. Brazil, with its vast agricultural areas, is using UAVs to rationalize the use of agrochemicals and increase crop yields. Japan, which suffers from labor shortages, has incorporated UAVs into rice cultivation to improve efficiency and precision. In South Korea, UAV technology is being used to optimize crop health monitoring and pesticide use by advances in automation and artificial intelligence. Many Asian countries are progressively using UAVs to improve pest control and crop monitoring, and governments are taking steps to promote modern agricultural practices. Thailand, Vietnam, and Indonesia are exploring the potential of UAVs to revolutionize traditional agricultural practices, with a focus on pest control and disease management. These global and regional trends highlight the growing importance of drone technology in crop protection and emphasize the role of drone technology in promoting sustainable and resilient agricultural systems around the world. Observing a remarkable upsurge in recent years, the use of UAVs has been driven by many significant factors. Primarily, the modern technical progress of UAV flight control systems, battery life, and payload performance, in all respects has made UAVs and their related technologies more accessible and economical to farmers across the board. Additionally, custom-designed UAVs for plant protection operations are growing in availability and are equipped with good alien control systems and sensor multifocal lenses (Figure 3). Despite projected implementation times, the adoption of UAVs in plant protection has been delayed largely because of the widespread belief that this technology is complex and too costly. Secondly, there is an increasing demand for data support tools and experts that can provide the required information. However, such questions have become far less important because the countryside of China has been experiencing an epochal transformation due to an upsurge of household farms and the sprouting of new agricultural macro-economic methodologies. With the emergence of company-level crop management UAV models for UAVs, large-scale agricultural firms have also been created [57]. UAVs have seen a more rapid acceptance in agriculture than ever before. This means greater efficiency and lower costs for many businesses (see Figure 5) because of logical regulatory environments. At present, Japan’s evaluation standards for aircraft insurance and similar licensing requirements built on German law make it simple enough to introduce new products without barriers [9,58]. The use of UAVs in agriculture has provided important data for understanding crop performance, growth characteristics, and factors leading to stress. It has also offered critical insights such as where exactly to apply specific pesticides or fertilizers, resulting in more productive harvests plus efficiency of resource utilization. AI and machine learning algorithm integration into UAV systems holds tremendous potential for independent decision-making and adaptive control in plant protection operations (Figure 4). The result is a proactive management strategy based on dynamic data analysis in real time. When used together with ground-based sensors, weather systems, and agricultural machinery, this strategy affords a more systemic approach towards crop management that offers farmers more rational choices so that they may obtain both higher production yields as well as long-term sustainability. Lastly, by utilizing 5G services, farmers can collect information and decide how to proceed [34,59]. Agricultural methods are changing with the widespread application of UAVs, which offer precision, efficiency, and sustainability to the farmer. As their adoption surges due to technological breakthroughs, environmental consciousness, and regulatory frameworks, UAVs are poised to assume a pivotal role in ensuring global food security.

4. The Operational Milestones of UAVs in China

This smart technology has its roots in prevailing precision spraying techniques that have made significant progress in alleviating pesticide overloading, environmental contamination, and resource wastage [21]. These systems have been able to greatly reduce chemicals and their environmental impact by utilizing the latest technology. In light of the significance of agricultural aviation, the “12th Five-Year” scientific research plan intended to prioritize the construction of this field and the approval of a professional science investment plan by the Ministry of Agriculture and Committees and Science and Technology, China, was implemented in 2013 [60]. Thereafter, in 2016, a national project was initiated in all the provinces with the help of 4262 (multiple) UAVs, especially multi-rotor type, to protect crops. These UAVs demonstrated their adaptability and efficiency in covering large zones during 2015, providing economic benefits as well [59]. UAVs are very successful in operation in complex terrains where traditional ground-based equipment would be highly limited (Figure 6) [61]. UAVs offer significant potential, be it due to their vertical take-off and landing (VTOL) capabilities that greatly improve operational efficiency in situations where small farmland is obstructed by multiple obstacles such as trees, or more generally from the uniqueness that provides an advantage in terms of ease-of-use when acquiring data about tens of hectares at a resolution fine enough for precision farming applications [9,62]. These technologies, such as multispectral and thermal cameras, are used in the development of significant changes in the practices of crop management. Such technologies offer high-resolution aerial imagery that helps farmers carry out real-time monitoring of crop health, pest surveillance, and disease control, leading to a new regime of crop management practices. The implementation of flight and navigation that is provided by the autonomy of UAVs has revolutionized operational efficiency, resulting in pinpointed crop sprays through difficult obstacles or terrains, thus making it safer and more reliable in plant protection operations [63]. Artificial Intelligence (AI) is helping UAVs as a game-changer for real-time decision-making. AI algorithms parse through large-scale aerial imagery and sensor data in order to identify patterns in crop health or pest trends and guide farmers to make necessary pest control-related decisions as well as to implement resource planning strategies. This milestone, enabling UAVs to safely and precisely perform operations, represents advances toward sustainability. With more friendly regulation, midsized and small farmers increasingly consider UAVs as part of crop management. The operational firsts reveal ground-breaking innovations and game changers in agriculture, such as precision spraying solutions to AI-powered decision support solutions. Continual technological developments likely signify further improvements and emerging models promoting agriculture’s effects and efficiencies.

The Operational Milestones of UAVs in Diverse Cropping Systems

China’s agricultural sector is vast and diverse, encompassing a wide range of cropping systems. UAVs in China efficiently operate in various crops such as cotton, rice, wheat, corn, sugarcane, apple, citrus, and forest (Figure 3 and Figure 6). These UAVs have shown success in different agricultural production systems, contributing to sustainability and efficiency.

Xinjiang, a major cotton-producing region in China, faces challenges from diseases and pests due to ongoing farming. Xinjiang’s intensive cultivation practices make it suitable for field spraying using UAVs equipped with Beidou navigation systems [13,14,15,16,17]. UAVs equipped with high-resolution cameras and multispectral sensors are utilized to detect pests such as cotton bollworms and aphids in fields [64,65]. The use of UAVs has been proven effective in controlling cotton pests and diseases, reducing spray volume and operational costs [58]. UAVs were utilized in paddy fields for tasks such as data collection, fertilization, and spraying [66]. Hyperspectral technology was used in rice fields for precise fertilization mapping during UAV-variable topdressing. A lightweight rice ring spreader was developed for sowing in UAVs. DJI released the T-20 agricultural UAV with a 15 kg/min seed-sowing system. UAVs were tested in wheat fields for disease control, pest management, and irrigation [20,34,63]. Several studies have highlighted the potential of UAV-based technologies in pest monitoring and control in wheat fields. For instance, estimating grain yields and protein content [67], mapping wheat crop characteristics and controlling pests in different regions [38,53], different dosages [68], pest control, and reducing costs compared to traditional methods [69,70]. Qin et al. [71] reported that at an operation velocity of 5 m/s and a height of 1.5 m, higher depositions (coefficients of variation = 23%), uniform droplet distribution, and efficacy for pest-control ranging from 92% to 74% were observed after 3 to 10-day intervals. UAV spraying extends efficacy due to low volume and concentrated distribution, enhancing wheat field health, pests, diseases, nutritional content, vigor, and water stress analysis [72,73]. Research on UAVs in citrus orchards focuses on pest monitoring, disease control, and droplet distribution, with previous studies exploring operational parameters for effective pesticide spraying. For instance, a study conducted by Lan et al. [73] utilized UAVs to capture hyperspectral images of citrus orchards and developed a model to detect Huanglongbing (HLB). The study reveals that UAVs are effective in monitoring large-scale orchards and detecting pests and diseases [74,75,76]. Furthermore, the research conducted by Hou et al. [77] revealed that flight altitude and speed significantly impact droplet distribution in citrus orchards. In a separate study conducted by Lan et al. [78], it was observed that the structure of the citrus canopy also plays a significant role in droplet distribution. Meng et al. [79] analyzed the use of UAVs to analyze tank-mix adjuvants’ effects on droplet distribution and contact angle in citrus orchards. The results show satisfactory management and control, providing a foundation for effective pest and disease prevention strategies. Current research focuses on pest monitoring, pollination, and spray optimization in cornfields [80]. A study using UAV-based remote sensing and machine learning techniques successfully identified areas infected by corn armyworms, with the Random Forest model being the most effective, demonstrating its efficiency in pest and disease management [81]. Studies are underway in apple orchards in China for spraying parameters inside the orchard. The Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing China, and other related departments have performed active UAV research in citrus and apple orchards. The authors performed a comparative analysis of UAVs and other conventional sprayers, showing that UAVs can be feasible and efficient in obtaining uniform coverage with reduced operational costs, operation time reduction, and reduced spray volume. The highest pesticide application rate was 67.9% among the five tested spray UAVs [82,83]. After 7 days of spraying on a greenhouse plant, the response rate was substantially changed, being reduced to 87.7%, 68.0%, 72.5%, and 62.5% [84]. Qiao et al. [85] examined UAV parameters improving the efficiency of pesticide spraying in apple orchards. UAVs can perform pesticide spray tests more quickly and accurately than traditional equipment [86]. Sugarcane in China is mainly cultivated in Guangxi. Nonetheless, ongoing cultivation has resulted in significant borer infestation, which directly affects stem growth and sugar content. The major sugarcane borer species in Guangxi are Chilo infuscatellus, Chilo sacchariphagus, Tetramoera schistaceana, Sesamia inferens, and Scirpophaga intacta. Regarding the difficulty in controlling late-stage tall crops [84], according to research, 5–20% damage from borers will result in a loss of 2625–7950 kg/ha, which is calculated as an average range with subsequent losses ranging from 3.2 to 9.4% on sugarcane production assets. Yield loss caused by borers ranged between 25 and 35%, up to 9906–13,537.5 kg/ha [87,88], representing 11.7 to 15.9% of the production due to damage rates from Brazilara-infecta Walker and Astophantesgrandis (Rutherford), respectively, causing more than 30% of yield reduction in their respective host plant species. UAVs have hence long since become the perfect method for pest control. The versatility has resulted in the wide adoption of sugarcane fields. In addition, the continuous study of the sugarcane field focuses on below-canopy assimilation and coverage, weather parameters, and water quality mapping/visualization. China is the largest producer of cherries; however, cultivation is affected by many factors that lead to significant cherry production. An innovative method was implemented using a fleet of UAVs arranged in a Y-shaped hovering formation around cherry trees to apply rainwater evenly on all sides of the cherries, helping to manage precipitation levels and reduce fruit cracking [89,90].

The forests in China are critical to the country’s economy and environment [91]. The use of UAV technology from Heilongjiang Forest for pest and disease management and fire prevention has improved. UAVs can strategically plan flight routes to effectively control these issues while reducing pollution and health risks [92,93]. Notable progress in different cropping systems in China, as shown in Figure 5, highlights how UAVs are transforming agricultural practices and promoting sustainable development [66]. These data can be used to establish UAV-operated networks for pest and disease control. UAVs have been particularly instrumental in quickly collecting data in rice paddies, wheat fields, orchards, and vegetable farms, leading to better resource utilization and crop yields. As technology advances, the significance of UAVs in Chinese agriculture is expected to grow, bringing about more innovations and efficiency improvements in the future.

5. Vital Role of Automation Technologies

The collaboration of UAVs and sensing technology is revolutionizing plant protection practices with automated agricultural systems. In China, advanced AI and machine learning systems were used in UAVs to monitor crop conditions as well as detect pests and changes in the weather in real time. Auto-platforms gather field data and provide actionable insights to make recommendations for farmers’ custom-tailored solutions. Precision spraying mechanisms allow pinpointed pesticide applications directly, adjusted according to continuous updates and maps of farm sites. Variable dosage conserves chemicals and minimizes environmental impacts. Autonomous navigation in farmland relies on GPS, coupled with inertial sensors and terrain mapping to minimize human guidance effort. Combining data from various sources with cloud analysis and machine learning significantly enhances overall crop health management, helps detect infestations, and improves understanding of the surrounding environment. Integrating remote cameras with UAVs (unmanned aerial vehicles) enables continuous monitoring of plant health and early identification of potential epidemics, facilitating prompt and targeted interventions. Currently, researchers are focusing on improving GPS-guided spraying technology using variable rates and state-of-the-art nozzles to improve the accuracy and efficacy of chemical distribution. Advancements in positioning, navigation, flight attitude control, and route planning play a vital role in efficient pest control when using UAVs for mountain orchards. Optimizing energy efficiency algorithms for remote sensing and imaging systems is crucial for UAV operations in plant protection. Variable rate technologies integrated into UAV systems, utilizing RGB, multispectral sensors, thermal cameras, and LiDAR scanners, allow operators to modify spraying parameters based on signs of crop health, pest pressure levels, and surrounding environmental conditions. Several studies have demonstrated that automation in agricultural and forestry settings, such as intelligent agriculture management, plays an important role [94]. Additionally, Lin [67] explored SAR imaging, ground-moving target detection, height measurement, signal processing, and high-resolution imaging for object classification. Other studies explored anti-offset wireless charging [69], machine vision, orchards located in mountain areas [95], and Ozonated water [83,96]. Ampatzidis et al. [97] identified visual navigation, route planning, flight control, obstacle avoidance, and image acquisition. These studies all offer novel techniques, underscoring the significance of innovative applications. Autonomous navigation and flight governance systems empower UAVs to traverse agricultural fields while adhering to pre-defined flight paths with minimal human intervention [98]. Data analytics and decision support systems are critical for processing and analyzing the data obtained from UAVs, whereas communication technologies facilitate the real-time transmission of data and the operation of plant protection-focused UAVs. Leveraging remote sensing technologies helps UAV operators utilize insights driven by data to precisely target interventions [32]. Smartphone apps provide operators with unique data. Thermal cameras can help monitor crop health efficiently, detecting pests and diseases and offering timely insights into any concerns detected above. Automation technologies in plant protection are transforming farming practices by enabling data-driven approaches, boosting crop yields, and reducing environmental impact with enhanced resource efficiency, showing potential for sustainable food production in the future.

5.1. Development and Modifications in UAV Spraying Systems

Precise technologies permit targeted and efficient control of pests, diseases, and weeds while reducing environmental effects and resource utilization. By modifying spray variables like volume, droplet size, and application rate in real time, precision spraying rigs boost pesticide efficacy and minimize environmental effects. Numerous analyses emphasize the importance of implementing precise pesticide application technologies aboard UAVs to enhance application performance [8]. UAVs equipped with autonomous systems, sensors, pumps, and nozzles offer precise spraying capabilities, resulting in improved yields and flexibility in satisfying crop pesticide demands [98]. China certainly leads the world in pioneering innovative spray technologies [33,48]. These autonomous machines leverage GPS-guided navigation and variable rate technologies to deliver spray amounts to the targeted area with precision. These systems have the potential to reduce overall pesticide use [99]. Furthermore, the applications of deep neural network models and machine learning approaches would benefit the systems implemented for disease detection, and pesticide utilization optimization as well as improving the precision, sensitivity, and economic benefits, etc. [100]. Different methods can be based on future forecasted weather maps, but a distinct class of mathematical and machine learning-based weather map algorithm models can be used to help optimize the most likely places where pesticide needs to be applied. This method is efficient in terms of agricultural production and waste reduction in pesticides [101]. These technological needs highlight the imperative of upgrading UAVs for future precision plant protection using new cutting-edge technologies.

5.2. Flight Durations and Payload Capacities

Variations in spray volumes/payloads of UAVs have significant effects on the efficacy and efficiency of treatments. Higher spray volumes with proper coverage protect crops better and can help reduce the chances of resistance. On the other hand, when applying lower spray volumes, it increases operational efficiency by treating large areas faster and more efficiently [98]. These factors are essential for maximizing UAV application. Designed for autonomous operation in environments with obstacles, UAVs are uniquely optimized to efficiently deliver uniform distributions and avoid obstacles. However, flight time and payload capacity significantly affect their operational effectiveness in plant protection. The flight duration parameter is of great concern in the operation because it determines payload and work efficiency [99]. This parameter allows much longer flight times for more extensive agricultural areas, better field surveillance, crop health monitoring, and timely treatment for pests or diseases [100]. In addition, the flight time and efficiency depend on battery capacity, propulsion system efficiency, airframe structure, and mission load weight factors. However, advancements in technology remove these barriers. Advancements in batteries and efficient propulsion technologies have greatly increased the duration and effectiveness of extended flights to save energy [101]. Additionally, UAVs equipped with cameras and multispectral sensors provide an added advantage to capture aerial imaging, monitor crop health, and apply pesticides with more precision. Objectives for plant protection in relevant missions include crop monitoring, pest identification, and disease diagnosis for which the payload configuration includes high-resolution RGB cameras on board such as UAVs. Multispectral imaging allows for immediate feedback to farmers about the health, nutrient levels, or stress conditions of their crops as well as enabling them to make new management decisions with correct data. In contrast, the DJIFlycart30 is most effective at carrying heavy payloads and has demonstrated application in many other industries. It can deliver medical supplies to more complex locations. UAVs equipped with LiDAR and sensors can create highly detailed terrain maps. The payload depends on the crops, field size, environmental conditions, and task requirements. The flexibility and modularity make them a great tool for operators. Initially, these UAVs had limited payload capacity, which was subsequently improved by development [102]. The flight duration and payload configuration of UAVs have great impacts on their performance. Expected developments in UAV technology and revolutionary payload solutions are well-positioned to enhance the efficacy of these UAVs, for use not only in plant protection but also in different fields.

5.3. Navigation Systems and UAV Applications

In agriculture, effective plant protection operations cannot be carried out without sophisticated navigation systems. By making aviation better for tracking and monitoring crops, detecting pests, and spreading pesticides through environmentally friendly GPS and GNSS technology, operations have been dramatically enhanced. These technologies deliver accurate positioning, navigation, and timing solutions, enabling farmers to work with greater precision. They help navigate fields with precision using pre-defined flight paths and positions for optimal spraying or other operations. IMUs are crucial for operating UAVs as they provide the system with data for orientation and movement [103]. The use of real-time kinematic or differential GPS technology can further improve positioning accuracy, allowing for precise control over spraying patterns and reducing overlap in pesticide application. Integrating LiDAR, radar, or ultrasonic technology as obstacle detection and avoidance systems on UAVs simplifies the workload through automated path planning and collision avoidance, enhancing the safety of flight operations in complex agricultural environments. This can improve mapping practices and low-altitude flight tracking from a crop protection perspective (Figure 6 and Figure 7) as the flight routes are adjusted to fly parallel with the ground, ensuring accurate spray deposition evenly spread across target surfaces. Waypoint navigation and geofencing allow pilots to set waypoints and “fences” that provide control, increasing safety and compliance with regulations [104]. Real-time environmental data and dynamic route optimization algorithms modify flight paths to minimize travel time, energy usage, and pesticide consumption while maximizing coverage and treatment efficacy [26,105]. These navigational enhancements greatly improve the operational efficiency, accuracy, and safety of plant protection operations, making agricultural practices more sustainable. In the future, the combination of new generations of navigational technologies and route optimization techniques should enable plant protection UAVs to perform increasingly accurate work over agricultural fields with high levels of efficiency and sustainability.

5.4. Integration of Sensor Technologies in UAV Operations

Sensing technologies are important for making UAVs more effective by supporting tasks such as crop monitoring, pest and disease detection, optimization, and accurate pesticide application [106]. The sophisticated sensor types that are common in the field of agriculture include RGB, multispectral, hyperspectral, thermal, and LiDAR cameras, GNSS with automatic section control (RTK), and weather stations [107]. Although sensors provide powerful functionalities, factors such as high cost, large payload demands, and complex operating systems have limited their application in the field [99,108]. The close distance field-based camera uses multispectral and hyperspectral spectrometric sensors of the RGB sensor [109]. Optical sensors are used for in situ detection of insect-stressed plants [110], which have benefitted from detection software based on digital image analysis technology. Although their performance is comparatively high, field scouting is required to verify the measurements recorded by these devices [111,112]. The use of multiple sensors in UAVs has increased the control of many flight parameters encountered in complex scenarios, resulting in an optimum strategy [26,113]. Moreover, sensors are used for obstacle detection and identification, making it possible to perform tasks such as crop health assessment, fertilization, irrigation modeling, pest and disease surveys, and field management [99,108]. Sound emissions can be monitored through acoustic sensors as a non-invasive tool for monitoring insect pests’ activity like larvae and borers. UAV-based sensing techniques exploit machine learning algorithms and hyperspectral sensors to strengthen pest and disease detection by acquiring reflectance factor data [114]. The measurements of land surface temperature and object distances are key information for comprehensive agricultural monitoring, and thereby thermal and LiDAR sensors can deliver these crucial data [29,104]. These sensors enable precision in the detection of the soil-to-crop temperature, and overall evaluation [115,116]. The application of sensing technology via ground-based and aerial platforms allows assessment for a broad array of applications in precision agriculture including crop density, canopy size 3D models, site evaluations, and farm planning [29,114]. Drainage management through technological tomography-assisted mapping systems ranges from GIS to app-supported grid-based soil tests down to current sensor-guided measures like the use of UAVs and cameras during remote image analysis [117,118,119,120,121]. The future of sensor technology in plant protection appears to offer far more accurate and efficient performance due to enhanced data analytics and real-time monitoring. Combining IoT and AI will allow predictive maintenance and earlier detection of pests or diseases. The improvement will stimulate sustainable practices of cultivation and increase crop yield.

6. Software and Surveillance Systems

In China and other countries, precision agricultural software has created precise renderings of field-based data from soil sensors and UAVs, enabling tailored interventions to reduce chemical use. Software and surveillance systems combined have transformed farming techniques globally in the field of plant protection, providing growers with cutting-edge features for monitoring plant health and managing pests. European countries like Germany and the Netherlands are utilizing advanced monitoring systems equipped with AI and ML to predict pest outbreaks. Innovative software platforms have been developed by China for analyzing data from UAVs and remote sensing to enhance real-time data. Sophisticated surveillance systems integrated with UAVs have been used by Japan and South Korea to determine the data with IoT sensors, providing real-time crop status and pest activity. Several Asian countries are developing and using mobile applications and cloud-based platforms in collaboration with government and industry. Australia’s vast agricultural operations benefit from integrated software systems that offer remote monitoring and automated pest detection, particularly in remote areas. Brazil and Argentina are implementing advanced surveillance technologies to manage their extensive agricultural landscapes, improving pest control and yield optimization. These global and regional advancements in software and surveillance systems are driving a new era of precision agriculture, enhancing the sustainability and resilience of agricultural practices worldwide. High levels of innovation in UAV technology have made it possible to acquire data for use in data-driven applications and other systems, greatly improving how farmers manage their problems through monitoring, analysis, and response-based solutions as discussed previously. These applications allow UAVs to rapidly, extensively, and efficiently collect data from farmland. By leveraging deep learning methods on extensive agricultural data, they provide valuable insights that facilitate effective decision-making and enhance operational performance. UAVs with data analytics, machine learning, and artificial intelligence algorithms will have these features, allowing automated data processing, pattern recognition, and predictive modeling. By using different sensors and imaging technologies including multispectral and hyperspectral sensors, UAVs can capture high-resolution imagery/videography in the field, monitoring environmental parameters and detecting crop health in real-time by analyzing how specific spectral signatures behave across an array of light wavelengths. Machine learning algorithms are used to make sense of UAV-derived and existing field data, identifying patterns, outliers, and correlations that inform targeted spraying for disease control as well as pest tracking. Additional operational efficiency from software applications such as flight planning, data processing, and analytics help farmers optimize their farm practices and add value to the agriculture industry, indicating substantial advancement in the software development sector [94,105,112]. Key industry participants involved in the development of such software are AGRAS APP, DJI Terra, and DJI, Smart Farm (Guangdong, China), Skyworks Aerial System (USA), SkyWards (USA), RedBird (France) PIX4D (Switzerland), MapBox (USA) DroneDeploy, Dedrone GmbH, and Airware Company USA. Several web- or cloud-based applications have been developed that can evaluate the availability of UAV-captured data to generate smart agricultural solutions and deliver maps representing field information. Tools such as Agroview, Aerobotics, and DroneDeploy (United States), allow for yield estimation, identifications of plant stress, and the production of precision applications. Agroview is a cloud-based application specifically designed to use artificial intelligence (AI) to interpret and demonstrate data obtained from UAVs [114,115]. UAV data-centric applications unify remote sensing, weather forecasts, and soil analysis to optimize spraying operations. Variable rate technology (VRT) varies the application of spraying by considering parameters like the density of the crop, level of infestation from pests, and other environmental factors subjectively to avoid unnecessary environmental damage and input costs (Figure 4). VRT enables proactive pest and disease management by providing early warning facilities and predictive modeling features, along with UAVs monitoring crop health indicators 24/7 to assist farmers in implementing preventive measures to address the spread of diseases as quickly and effectively as possible. Data-driven applications in UAVs provide farmers with critical insights, decision support, and precision management strategies, improving spraying, tracking crop health, and mitigating pests, thus modernizing cultivation and making it sustainable.

7. Artificial Intelligence (AI) and Internet of Things (IoT)

In China and the United States, the convergence of AI and IoT is revolutionizing crop protection and changing agricultural practices worldwide. AI platforms are using data from IoT devices and UAVs to make real-time predictions that allow farmers to optimize pest control and crop management with unprecedented accuracy. European countries such as Germany and the Netherlands are pioneering the adoption of smart sensors and automated precision farming systems that predict pest outbreaks and monitor crop health to improve efficiency and sustainability. Japan and South Korea are pioneering the integration of artificial intelligence and the Internet of Things for comprehensive crop monitoring, combining drone data with ground-based sensors to control pests more efficiently and sustainably. Driven by innovative government and private sector initiatives, some Asian countries are experiencing a proliferation of artificial intelligence mobile applications and cloud-based platforms that are revolutionizing pest control and crop monitoring. Australia’s vast agricultural areas are benefiting from AI and IoT technologies that enable remote monitoring and automatic pest detection, especially in difficult, remote areas. In Brazil and Argentina, the integration of AI and IoT is transforming the management of large acreages, improving yield optimization and pest control. These advances in AI and IoT are ushering in a new era of precision agriculture worldwide, promoting sustainability, resilience, and innovation in farming. The combined application of AI and IoT represents a comprehensive shift from traditional chemically based plant protection to device interaction and data analysis, and the decision-making processes are overhauled through these cutting-edge technologies (Figure 4) [32]. The combination of AI and IoT is a powerful partnership that provides several opportunities for new possibilities for data-driven automation, predictive analytics, and smart decision-making that allow for simplified communication, information exchange, and remote control. In an agricultural context, IoT sensors collect on-field environmental parameter data such as soil moisture levels and pest activity through integration into farming equipment. To detect irregularities, monitor for signs of pest outbreaks, and evaluate crop health, AI-driven analytics pore over these data at scale with speeds that provide early alerts, enabling interventions to be carried out promptly. IoT enables precision agriculture systems that leverage data received from different sources like soil sensors, weather stations, or crop monitoring tools to control the way pesticides are applied. These data are then consumed by AI algorithms that compute accurate application maps, change prices, and suggest control strategies. In addition, precision and variable rate application technology have been key focus areas of innovation for plant protection in the most recent years. These plants are equipped with sensors that measure nutrients as needed in real-time (Figure 4). IoT sensors on UAVs along with AI-based imaging enable capturing aerial imagery of agricultural fields to analyze everything from crop health and vegetation indices to pest dispersion. The collected data are analyzed using AI algorithms, which are informal surveillance and direct interventions. Telli et al. [32] reported that leading research of AI applications in UAVs uses algorithms such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for activities like object detection, path planning, autonomous navigation, swarm intelligence, and image analysis for surveillance purposes. The advancement of AI technology for flying task autonomies, including deep reinforcement learning and vision-based autonomous landing, can be useful in a wide range of areas. While these developments represent substantial progress, issues in this conglomeration include security, privacy, and the efficiency of data processing solutions. The affordable and effective integration of IoT data with AI is necessary for plant protection. Such systems must be low-cost, democratized, standardized, and interoperable solutions that are easy to adopt for users. Farmers should transform the adoption of these rather than having to upskill in IT or rely on nonprofit organizations. Deploying AI and IoT for plant protection has the potential to increase agriculture productivity, sustainability, and resilience greatly. Through integration with real-time and advanced analytics, these technologies can play a crucial role in addressing global food security challenges.

8. Technological Development and Limitations

8.1. Technical, Physical, and Environmental Limitations

Since the beginning of history, farmers have been fighting pests and diseases in order to grow their crops. A precise and more efficient way to apply pesticides, fertilizers, and other phytosanitary products to agricultural fields or orchards is presented through UAVs. This efficacy is related to several meteorological, technical, and physical aspects, notably concerning droplet disappearance that may have undesirable effects in surrounding areas [122,123]. Spray drift is a multifaceted, complex phenomenon that involves an interaction of various factors that are both within and outside the control of UAV operators. Droplet size, nozzle type, and spray pressure are critical factors that significantly affect UAV spraying. These factors influence various aspects such as spray path, volume flow rate, altitude, velocity, temperature, humidity, wind direction, volatility, solution viscosity, turbulence, and surface tension, as well as operator skill, competency, and positioning expertise [124,125]. Temperature, humidity, and wind speed are the essential environmental factors that impact the performance of UAVs a great deal. However, since UAV operators have little control over these conditions, they should be evaluated well before any operations. Higher temperatures can significantly speed up droplet evaporation and decrease droplet size. Temperature can impact pest activity and behavior and also affects the evaporation and distribution of spray solutions.

Increased viscosity may alter the atomization process and flow, potentially resulting in coarser droplets suspended in the atmosphere. This reduced moisture diffusivity can cause small water droplets in the air to shrink. Conversely, raised humidity levels can significantly heighten droplet size, coverage, and deposition volume. Compared with open fields, greenhouses are more easily controlled in their weather patterns. Temperature and humidity conditions should be considered when applying different formulations. According to [126], the deposition pattern of droplets remains relatively constant between 28 and 29 °C. Franz et al. [127] examined the influence of relative humidity on canopy deposition from aerial application to cotton and cantaloupe leaves. Nuyttens et al. [128] also developed a model to quantify spray drift and presented an equation for predicting the intensity of drift deposition. Tian et al. [129] also determined an unreliable factor in droplet deposition during UAV operations at night. According to Hu et al. [25], spraying should be carried out when the RH ≥ 70%, which is ideal for pesticide drift reduction for both ground-based as well as UAV operations, and the concept of an optimal ratio of sprayed mass per unit of water mass (correctly assessable considering weather conditions) can be applied in each case [130].

8.2. Variable Rate Applications (VRAs) and Precision Detection in Modern Spraying Technology

Smart atomization technologies incorporated into UAVs for plant protection purposes optimize crop pests, diseases, and weed management, improve yields, and minimize environmental impact through the precise delivery of pesticides, fertilizers, and other agrochemicals. The utilization of artificial intelligence (AI) and machine learning algorithms within UAV systems is leading to a transformation in the application of agrochemicals, ensuring efficient resource utilization, preventing overapplication, and decreasing expenses and environmental contamination by adjusting application rates and patterns [131]. Enhanced nozzle and spraying technologies are elevating the accuracy and consistency of atomization processes, thereby decreasing waste, and achieving uniform coverage that surpasses conventional methods. These advancements empower UAVs to direct agrochemicals precisely to targeted zones with minimal dispersion. Intelligent spraying mechanisms in UAVs refine deposition and effectiveness by modifying pressures and droplet sizes based on the speed and altitude of the aircraft, resulting in the production of fine droplets that optimize performance [132,133]. Liu et al. [134] reported that using a smart atomization system revealed that droplet size is influenced by pressure, with sizes ranging from 85.95 to 124.46 µm. Smart atomization technologies are reshaping UAVs, fostering sustainable agriculture, and diminishing the dependence on synthetic chemicals. They facilitate the precise application of biopesticides, pheromones, and organic inputs, supporting integrated pest management (IPM) practices and biodiversity. These technologies serve as robust instruments for crop management, enhancing productivity, and promoting environmental sustainability. The application of precise detection and spraying technology in integrated pest management results in a new generation of precision application platforms for the plant protection industry, which marks an important step towards perfecting pesticide safety with efficiency. The fact that spray volume can be customized to the crop and orchard canopy size/density can also increase efficiency, reduce waste, and minimize environmental repercussions. Commercially available novel machine vision, controlled-system technologies can cover the foliage well at smaller spray volumes per hectare than would be applied by constant rate applications. Comparatively limited research is available on variable rate versus constant rate spraying applications and still, crop attributes vary stage by stage based on agroclimatic conditions and management practices throughout the growing season. In this review, the focus is on UAV sprays and surveillance systems, with their environmental condition-adjusted regulation of various sprayer parameters to mitigate pesticide wastage.

Many researchers have worked on the combination of UAV swarms and image processing to enhance the performance of spraying. Application (sprayer% reduction relative to ~20% for walking design [37,135] methods employed by [136] had the advantage of analyzing various spraying parameters, such as the shift in spray rate and flow along with other factors at a precision level while being rapid in setting up UAVs. Khan et al. [137] tackled the problem of spraying coriander plant spots; this approach uses a deep learning mechanism. Hunter et al. [138] used UAVs to detect and manage weed locations, thereby reducing the use of pesticides. Wen et al., based on the ArcMap program (2018), developed an adjustable spray system using a PID-PWM model that directed varying spray qualities to adhere to the recommendation map. Using the Lucy–Richardson filtering, the open-space and vegetation regions were identified to guide the system on when to stop spraying [139]. Faiçal et al. [140] developed a particle swarm optimization-based method for control rule adjustment in crop spraying for pesticide application using UAV-enabled object detection based on deep learning algorithms. Deep learning AI algorithms allow UAVs to detect objects, thereby increasing the accuracy of crop threat identification. Coupled with UAV spraying technologies, this collaboration provides a means to target zones of application even more precisely down to the millimeter. Farmers can leverage these advancements to deploy more effective and precise plant protection strategies, decreasing the environmental load while increasing crop yield (Figure 4). Meanwhile, Ivić et al. [141] generally proposed an operational approach to the heat equation-driven area coverage for autonomous UAV swarm spraying, originating from the multi-agent area coverage technique. By integrating a system in the rice field to coordinate the precise UAV location, Hong et al. [95] used the Ex-green and Ex-red methods in the rice canopy, resulting in a faster response time of 15.765 milliseconds. This outline shows which areas should receive treatment and is generated using a normalized differential vegetation index and a unique algorithm that establishes the location [142,143,144]. They can detect field vegetation using UAVs and generate prescription maps with higher precision that help minimize chemical application. Thus, an intelligent spray requires a very smart algorithm and different sensors to sense the environmental conditions in order to reduce the number of pesticides.

8.3. UAV Flight Speeds, Altitudes, and Droplet Depositions

Flight speed significantly influences the operational duration of UAVs over crops or orchard canopies, directly impacting pesticide application effectiveness. Maintaining droplet deposition integrity while optimizing UAV speed is crucial for efficient pesticide application. Dynamic Speed Spraying Technology represents a breakthrough in agricultural plant protection, offering adaptive and responsive spraying to enhance chemical application efficiency. UAV technology adjusts flight parameters in real-time to ensure optimal droplet distribution, thereby maximizing coverage and minimizing wastage. Several studies have demonstrated the profound impact of flight speed and altitude on pesticide deposition. Zhang et al. [145] utilized thermal infrared imaging and identified 1.5 m as the ideal UAV flight velocity to achieve uniform droplet deposition. Their study underscores the importance of fine-tuning flight speed to balance operational efficiency and pesticide effectiveness. Similarly, Pan et al. [146] observed in 2021 that the increased flight speed of diesel-powered UAVs led to a significant reduction in droplet deposition efficiency. At a flight speed of approximately 1 m, the droplet density was only 41.4%, with coverage dropping to 3.9%. These findings highlight the delicate interplay between flight speed and deposition efficacy, necessitating precise control over UAV flight parameters. Lou et al. [147] reported that maintaining a UAV flight height of 2 m ensures uniform droplet deposition across canopies, regardless of cloud volumes. However, reducing the flight height below 2 m significantly decreased deposition on cotton fields, indicating that optimal altitude is crucial for effective pesticide application. Wang et al. [148] recommended a flight height of 2.5 m for pineapples, optimizing deposition and minimizing drift. Similarly, Shengde et al. [149] suggested a flight speed of 1 m for citrus trees, aligning with the specific requirements of different crops. Flight speeds of 2 m displayed superior uniformity, enhancing droplet deposition. Optimal effects were observed at speeds of 4 and 6 m/s, indicating that higher speeds, within certain limits, can improve deposition efficiency. Hu et al. [150] recommended a flight height of 1.5 m and a volume application rate of 22.5 L/ha for effective aphid control in cotton plants, demonstrating the need for tailored UAV flight parameters based on specific pest control requirements. UAVs typically operate effectively at heights between 1.0 and 2.5 m, similar to step residue depth and dense vegetation, which can hinder UAV performance during area surveying. It is concluded that droplet drift is more influenced by crosswind velocity than spray height. Therefore, a deposition model considering wind speed as a function of altitude should be employed to estimate deposition accurately. This approach allows for better prediction and control of droplet drift, enhancing overall application efficiency. Hunter et al. [151] showed that using air-sensing flat or 75° flat nozzles at a speed of 3 m/s effectively decreased spray drift. This finding underscores the importance of nozzle selection and flight speed in controlling drift. Zhou et al. [152] indicated that droplet deposition is affected by flight speed, height, and droplet size, necessitating the optimization of these parameters for maximum deposition. Additionally, low temperature, humidity, and wind velocity influence droplet deposition [153,154,155,156]. Higher wind speeds and flight heights can cause droplet drift, with deposition and evaporation times of spray droplets varying with flight height due to aerodynamic drag, thereby modifying drift distance. Optimizing these parameters under realistic UAV operating conditions can enhance deposition efficiency. Dynamic Speed Spraying, an adaptive pesticide application technology, has the potential to offer tailored chemical applications within fields. By dynamically adjusting flight speed, height, and nozzle settings, this technology ensures optimal droplet deposition, reduces environmental impact, and enhances pest control efficacy. As UAV technology continues to evolve, further research and development in dynamic spraying techniques will be essential to fully realize the potential of this innovative approach in precision agriculture.

8.4. Autonomous Navigational Flights and Obstacle Avoidance Technologies

Advanced technologies, such as fully autonomous aerial navigation and obstacle avoidance systems have resulted in a substantial transformation of the agricultural sector. This assists in improved efficiency, accuracy, and green technology. In the current era, UAVs are integrated with GPS and sensors/cameras for field navigation, bringing a high level of autonomy to ensure that errors are minimized in operations where precision is key such as pesticide application, fertilization, and crop health monitoring. In addition, obstacle avoidance tools implement LiDAR and ultrasonic sensors that help UAVs recognize and avoid obstacles in real time to protect equipment and crops. However, the commercial use of UAVs in farming depends on regulations such as licensing for pilots, operation limits, and airspace borders. While the implementation costs associated with these technologies can be high, the resultant long-term benefits of this technology, such as improved crop yields and early detection of crop-related issues, make them worthwhile investments. The way UAVs are currently used has advanced through machine learning optimizations and the future is bright with additional improvements in this technology. According to Hu et al. [157], the results of their study showed a 50% decrease in droplet drift, attributed to the modification of flight routes according to wind conditions when using DQN and PSO algorithms, as well as enhanced droplet accumulation (Figure 4). Nonetheless, the fact that faster wind changes can thus affect efficiency means that additional studies are needed to improve the efficiency. In an attempt to reduce the chances of vehicles harming themselves and other obstacles, actual aircraft radian obstacle avoidance has been secured by way of several avoidance systems. Wind-induced spray drift is still a major problem for applicators. This effect can be countered by changing the operating tracks of UAVs. Winds have a high impact on droplet drift and resultant pest populations; however, the appropriate wind direction and nozzle size can be selected to minimize drift. Chen et al. [158] tested four different types of UAVs and suggested that the 200 µm droplets are capable of drifting in crosswinds of at least 5 km/h, and the degree of downwind travel was unrelated to wind speed. Moreover, the operation was inappropriate with crosswind speeds higher than 3 m/s. Fengbo et al. [159] determined that a wind speed below 5 m/s and an operating height within 2.5 m during UAV spray deposition are two key factors for pineapples [160]. In addition, droplet drift occurs downwind if the UAV is operated at 1.5–3 m flying height and 2.4–5 m/s speed, and its main factor is a spraying height of 7 m [161]. Such precision farming methods, which are both sustainable and data-driven, further reduce the carbon footprint of agriculture while boosting yields and reducing food losses. Moreover, limitations of these methods include regulations, technical challenges to their development, and EO/IR sensors that support decision-making processes (e.g., surveillance). In addition, ongoing research is needed on the adaptability and intelligence of UAVs.

8.5. Droplet Spectrum and Distribution

Achieving uniformity in the precise and consistent distribution of pesticide droplets from UAVs is crucial for ensuring effective operations; however, these tasks face several challenges. A consistent droplet size distribution is vital for adequate coverage and canopy penetration, despite the challenges in dynamic flight altitude and velocities. Wind significantly alters droplet trajectory, potentially reducing efficacy and contributing to off-target spray drift. The control of droplet evaporation significantly impacts spray coverage effectiveness and flight efficiency. Proper calibration is vital for accurate application rates and coverage, ensuring the right droplet retention and adhesion to plant surfaces for ingredients to be effectively taken up by plants. Several authors have researched the substantial effect that these variables have on droplet deposition, considering various factors including nozzle efficiency, spray volume, and droplet size to impact the outcome of deposition. Cerruto et al. [162] determined that all of these variables affect droplet distribution, deposition, and droplet size. Xue et al. [73] assessed droplet spray drift using an N-3 UAV. The results of their study indicated that the ratio of droplet deposition and pest control of brown plant hoppers varied with flight velocity and altitude. Many studies emphasize the importance of dependable nozzle engineering for steady coverage and penetration ability. Qin et al. [68] conducted a test in rice fields to assess developments in nozzle design (electrostatic and ultrasonic) in terms of improving spray visibility for better pattern visibility, coverage improvement, drift reduction, smaller water droplet generation, and synergizing agricultural practices sustainability. For best performance, it was recommended to have a nozzle deposition diameter within the range of 100–300 mm. The relationship between droplet size and droplet density was found to be negative [163]. Smaller droplets are easily predisposed to drift, but even larger droplets are better for pest control in wheat fields [164,165]. Several research studies have shown that nozzles incorporating innovative technologies can reliably and effectively disperse chemicals by tailoring droplets to the canopy, thus reducing wastage. Wang et al. [166] reported that these factors possess a notable influence on droplet deposition. Derksen et al. [167] evaluated the performance of nozzles and droplet volumes in the application of agrochemicals in soybeans. Fritz et al. [168] investigated the impacts of spray rate and droplet size on droplet deposition and determined the effects caused by three different types of nozzles. Nozzles present a complex balancing act between regularity, infiltration, and dependability, with the latter being of supreme importance. The productivity and consistent acceleration of UAV applications, coupled with alterations to nozzle or outlet placement, can help mitigate drift impacts [169,170,171]. Tang et al. [2] proposed that modern nozzles outfitted with progressive technologies strive to maximize spraying results by achieving broader coverage, decreasing drift, and creating smaller droplets in an environmentally sustainable manner. Considering the effect of flight elevation and velocity on droplet deposition suggests that efficacy requires careful planning. Effective coverage can only be achieved by performing monitoring of pest populations and adapting and changing with the winds in real time. Uniform droplet distribution and coverage across a large area is ideal but must be achieved in such a way that payload capacity, application rate, and flight duration adhere to aerodynamic constraints. If carried out strictly according to regulatory guidelines and incorporating environmentally friendly techniques, the operation will be safe and effective [34].

8.6. Biodegradable Materials

Biodegradable spray covers quickly and degrades into harmless substances, minimizing the risk of contaminating soil and water sources while supporting environmental sustainability and ecosystem health. The use of biodegradable sprays reduces residues on crops, soil, and water, resulting in less pesticide build-up in the food chain and decreased human and animal exposure to toxins. Ongoing research is focusing on surfactants, adjuvants, and polymers to fine-tune spray solutions for different crops and environmental conditions. The main goals are achieving the greatest effectiveness and minimizing the environmental load [172]. Different additives developed using nanotechnology enhance the effectiveness of spray solutions by improving stability, dispersion, and target precision. Additionally, these additives include smart compounds that can react to environmental cues.

Ongoing assessments are being carried out to evaluate the influence of these novel substances on ecosystems, non-target organisms, and human health. Several types of adjuvants are available nowadays in the markets (see

Table 1. Types and characteristics of different tank-mix additives commonly used in UAV operations.

S.NO	Name	Type	Characteristics	Source
1	Beidatong	Vegetable oils	Anti-evaporation, anti-drift	Hebei Mingshun Agricultural Technology Co., Ltd., Hebei, China
2	Maifei (MF)		Increases wetting and spreading of droplets on the leaf	Beijing Grand Agrochem Co., Ltd., Beijing China
3	Atplus Mso-Hs 500		Anti-evaporation, anti-drift	Britain Croda, Co., Ltd., United Kingdom
4	Y-20079	Organosilicon	Increases wetting and spreading, anti-drift, improved efficacy	American Masan High-tech Materials, Co., Ltd., United Kingdom
5	Surfom ADJ8860		Reduces droplet surface tension, contact angle, and wetting time, inhibits droplet rebound	Brazil Oxiteno, Co., Ltd., São Paulo, Brazil.
6	Lieying		Reduces droplet surface tension, increases adhesion	Anyang Quanfeng Aviation Plant Protection Technology Co., Ltd., China
7	Starguar4A	Polymers	Anti-drift, anti-evaporation, increases adhesion on leaf, anti-bounce	Belgium Solvay, Co., Ltd., Brussels, Belgium
8	Starguar4		Anti-drift, anti-evaporation, increases adhesion on leaf, anti-bounce
9	Ultimate		Reduces droplet ST and contact angle, increases wetting and spreading, anti-drift
10	Silwet DRS-60		Anti-drift, increases wetting, adhesion, and cuticle penetration	American Masan High-tech Materials, Co., Ltd., United Kingdom
11	G2801		Increases droplet deposition and adhesion	Shantou Daqian Research Center of Advanced Science & Technology Co., Ltd., China
12	DS10870		Reduces droplet surface tension, increases viscosity, anti-evaporation, anti-drift	Huntsman Chemical Trading, Shanghai, Co., Ltd., China
13	InterLock™	Anti-Drift	Increases droplet size and weight to reduce drift enhances deposition	Winfield United, Arden Hills, MN 55126, Co., Ltd., United States
14	Drift-X™		Modifies droplet size and velocity to minimize drift, improves droplet adhesion	BASF, Co., Ltd., Germany
15	Leverage® GT		Reduces fine droplet formation to minimize drift	Corteva Agriscience, Co., Ltd., American
16	Drift-Not®		Adjusts droplet size and velocity to reduce off-target movement	Bayer Crop Science, Co., Ltd., Rhein, Germany
17	IPP-4		Anti-drift, increases wetting, adhesion, and cuticle penetration	Institute of Plant Protection-GSCAAS, Beijing, China

). Environmental issues are playing a significant role in driving demand for green biodegradable spray chemicals for UAV-based applications. Integration of additives with pesticides and herbicides aims to improve their effectiveness by increasing adhesion or penetration through better spreading and wetting characteristics or reducing drift. The use of UAV spraying can lead to sustainable agriculture as farmers will increasingly choose lighter, biodegradable spray materials rather than heavy synthetic chemicals, thereby helping with sustainable long-term agricultural viability. Spray formulations using biodegradable polymeric materials can decrease environmental persistence by degrading into non-toxic materials. Most anti-drift tank-mix products are based on organophosphorus, polymer, or oil-based compounds that require laboratory and field tests [173]. Therefore, factors such as UAV, formulation, concentrations, and nozzle type must be carefully considered when selecting these additives [42,99]. These adjuvants can increase the efficiency of spray droplets, manage droplet distribution, and reduce the spray volume and number. However, the selection process depends on the application type [174,175]. UAVs can increase droplet retention and improve coverage [176]. Factors such as nozzle types, application rates, flight altitude, and speed, and weather conditions (temperature and wind) play crucial roles in improving spraying efficiency and must be considered before applications. Guidelines for each type of adjuvant and application must be established to promote sustainability.

8.7. Droplet Deposition Detection Technologies: Spectral Solutions

The flight characteristics of UAVs provide performance opportunities, cost-effective operations, reduced labor requirements, and precise spraying applications (see

Table 2. Evaluation of different droplet drift-control technologies.

Technologies	Detailed Description	Key Features	Advantages	Disadvantages
Anti-drift adjuvant	Amends physical parameters and reduces drift.	Enhances droplet cohesiveness, minimizing wind drift.	Increases efficacy, and reduces the dosage.	Potential for chemical incompatibility with certain pesticides.
Anti-drift nozzle	Design with precise delivery of amounts.	Reduces the number of fine droplets, lowering drift potential.	Easy to retrofit on existing equipment.	Coverage at lower application rates.
Flight parameters	Adjustments in application, UAVs to optimize spray deposition and minimize drift.	Includes adjustments to height, speed, and spray angle.	Optimizes application under varying operational conditions.	Requires precise control and monitoring, which can be challenging in rough terrain.
Drift model	Computational or physical models are used to predict the path and deposition of spray droplets under various conditions.	Assists in developing guidelines and regulations for spray applications.	Helps in planning and regulatory compliance; can be tailored to local conditions.	Relies on accurate input data; may not capture all environmental variables.
Electrostatic spraying	Spraying method that charges droplets to attract them to the target, enhancing deposition and reducing drift.	Increases spray efficiency and coverage on target surfaces.	Improves target specificity, reducing waste and environmental impact.	Equipment costs and maintenance are high; and not suitable for all types of chemicals.
Smart atomizers	Technology-driven sprayers that adjust droplet size and spray parameters in real-time based on environmental sensors.	Optimizes spray applications, dynamically responding to wind and movement.	High precision in application; reduces chemical use and environmental impact.	Complex systems that require significant investment and maintenance.
Hyperspectral sensors	Sensors that capture and process information from across the electromagnetic spectrum.	Allows detailed detection of crop health and characteristics for precision application of inputs.	Enables highly detailed imaging for precise agronomic decisions.	Typically, more expensive and data-intensive compared to other sensor types.
Multispectral sensors	Sensors that measure specific wavelengths of light to assess plant health and other environmental conditions.	Commonly used in agriculture for assessing plant health and soil properties.	More affordable and easier to deploy than hyperspectral sensors, good for large-scale use.	Provides less detailed data than hyperspectral sensors.
Ultrasonic sensors	Sensors that use sound waves to measure distances or detect object characteristics.	Useful for determining plant canopy density and ground topography. Can operate in various weather conditions, reliable for real-time adjustments.	Limited in data complexity, affected by air temperature and humidity.

). The deposition method should be efficient to achieve maximum efficacy and minimal environmental effects. Using advanced sensors as a substitute for spraying machines and capturing high-resolution images, data processing algorithms are used to analyze droplet deposition patterns, coverage of uniformity levels, and spraying drift rates. Various detection methods are required to monitor hydrophobic pesticides on sprayed crops. Typically, these methods entail water-soluble tracers such as fluorescent substances, visible dyes, or metal salts. Allura Red, a safe water-soluble food dye, and copper are mainly used as tracers and showed excellent characteristics when field-tested. In addition, LiDAR technology and remote sensing greatly assist in accurately mapping fields. They can be used to judge how the pesticide spray is dispersed and also for optimization, ultimately generating three-dimensional maps of field detail. Combining UAVs with hyperspectral imaging systems allows real-time monitoring of droplet depositions and chemical residues on the plant surface or canopy. Hence, workers can adjust their spraying parameters dynamically to achieve maximum effect and reduce off-target drift. Leveraging machine learning algorithms or computer vision methods added to traditional spectrographic methods will enable maximum (99.9%) deposition detection during UAV-based pesticide spraying operations. These methods predict the best flight paths and reduce environmental contamination by training models on large aerial imagery datasets. Thus, the in situ detection of droplet deposition could be performed by an all-around UAV using LiDAR (Light Detection and Ranging) technology, integrating hyperspectral and thermal imaging techniques, fluorescence spectroscopy with real-time feedback, or adaptive control. Next-generation cloud-based data analytics platforms are critical to the speedy utilization of UAV-collected data on pesticide spraying, thereby influencing the optimization and innovation in UAV pesticide application practices. Lan et al. [177] assessed the application of machine learning methods for quantitatively assessing the distribution of UAV spray nozzle deposition. Shi et al. [178] conducted numerical simulations, Yongjun et al. [81] utilized LIDARs, and Lv et al. [179] studied the heat equation-driven area coverage proposed as an operational strategy for autonomous UAV swarm spraying based on the multi-agent area coverage method. Spraying may typically reduce overspray by 3–8% compared to traditional path design. Zhu et al. [153] conducted CFD simulations and developed a method using computational fluid dynamics to calculate droplet distribution. Wen et al. [180] employed PWM precision spraying controllers. Gonzalez et al. [181] also introduced a portable visual sensor system that utilized MobileNet SSD and deep learning for droplet deposition detection [162].

Wang et al. [172] proposed an intelligent vision-based sensing approach for detecting droplet deposition during spraying. To ensure safety, operators must diligently check spray direction and dispersion while also establishing sensitive buffer zones around the target area. With care and caution, technological progress can be harmonized with environmental protection. Comprehensive record-keeping of past projects will not only support continued enhancement but also provide a benchmark for evaluation and collaboration. Future development requires maintaining such documentation to carefully assess performance, streamline processes over time, and engage stakeholders. Investigating techniques to refine drift classification through aerial detection technology utilizing precise machines of the skies promises to advance crop safeguarding. The merging of UAV spraying with laser scanning, detectors, and imaging that sees all wavelengths of light, and the ability of computers to learn from data are transforming methods, smoothing the path toward more effective yet considerate protection of yields. The examples provided in this study highlight the substantial improvements achievable through these advancements.

9. UAV Adoption and Complex Barriers

The use of UAVs in plant protection faces complex obstacles, but innovative solutions and principles are emerging to overcome these challenges in the United States, Germany, France, China, Japan, Korea, Australia, Brazil, Argentina, India, Pakistan, and other countries. Regulatory compliance is a major hurdle, and advanced encryption technologies and clear guidelines ensure security (Figure 8). Technical limitations such as short flight times and limited payload capacity can be overcome by developing efficient batteries and lightweight materials and adhering to efficiency principles. Interoperability between different UAVs could be improved through standardized communication protocols, leading to greater coordination and efficiency. Investments in artificial intelligence and machine learning enable automation and make technology more accessible and usable. Infrastructural constraints, especially in remote areas, are addressed through the use of mobile ground stations that integrate drone data with existing agricultural systems according to integration principles. With a focus on safety, efficiency, standardization, ease of use, and integration, these solutions break down barriers and accelerate the adoption of UAVs in crop protection, making the future of agriculture more sustainable and resilient. Regulatory bodies in developing nations impose limitations on UAV flight altitudes, operational zones, and payload capacities to ensure adherence to safety, privacy, and aviation regulations [103,182]. Authorized farmers and UAV operators are legally responsible for operating UAVs for agricultural purposes. Countries like China, Norway, and Sweden have more relaxed regulations, with China establishing 81 specific standards [134]. Regulatory frameworks for plant protection UAVs differ by country and region. In the United States, the FAA and EPA regulate the operation and the use of pesticides, respectively. In the EU, the European Aviation Safety Agency (EASA) and the European Food Safety Authority (EFSA) enforce strict guidelines on drone certification, safety, and pesticide use. In Japan, the Ministry of Agriculture, Forestry, and Fisheries focuses on registration, business licenses, and sustainable agricultural practices. Australia’s CASA and APVMA handle UAV regulations and ensure the safe use of pesticides. The Brazilian associations ANAC and MAPA focus on safety and environmental protection when using UAVs. China stands out for its large-scale adoption and innovation of drone technology, driven by policy support. Most countries require certification and compliance with operational guidelines, with regulations varying in stringency based on national priorities and technological advancements. The significant barrier to adopting advanced UAVs equipped with sensing technologies is their exorbitant cost. In China, procuring and maintaining agricultural UAVs ranges from CNY 20,000 to CNY 80,000 depending on the model, features, and intended uses [32]. This financial burden renders the technology inaccessible to small-scale and low-income farmers, significantly limiting widespread adoption. Advancements in computer vision and sensors have enabled UAVs to autonomously navigate obstacles like trees, power lines, buildings, and other moving objects, minimizing collision risks [179,180]. Certain traditional farmers in rural communities remain sentimentally attached to heritage farming practices, demonstrating initial resistance to new technologies [94,183]. However, technology shows promise for boosting yields and preserving traditional methodologies if accessibility issues are addressed through training programs and financing options for smallholders [184]. While current UAV costs are substantial, prices are expected to decrease over time as the industry expands and matures [32,113,120]. Emerging companies now offer affordable UAV sensing and data analysis services that integrate with other agricultural management systems for efficient record-keeping [185,186].

Vigilant battery maintenance and payload calibration are crucial considering various flight durations and weather conditions discussed in Section 5 and Section 6, (Figure 7) [187]. As agricultural drone technology advances, enhanced infrastructure and support networks are still needed. Notwithstanding present challenges, expected technology improvements and declining costs may propel future growth and broader acceptance of UAVs within agriculture.

10. Research and Development Role in Plant Protection Paradigms

Research collaborations are driving innovative breakthroughs in the integration of UAV systems for plant protection. These partnerships foster cooperation between scholarly institutions, industrial allies, and government (Figure 9). In May 2016, Chinese companies united to establish an investigation coalition aimed at addressing technological obstacles in the aviation sector. This alliance operates jointly in conjunction with universities, research institutes, and promotional divisions. The scholarly alliance actively engages with regulatory bodies and policymakers to tackle legal, ethical, and safety issues associated with UAVs used for plant protection. The primary goals include developing efficient and intelligent systems, promoting technology assimilation and novelty, and decreasing pesticide utilization while boosting operational proficiency, standards, directions, and knowledge swap initiatives. Moreover, it facilitates the dissemination of knowledge, networking, and collaborative efforts in UAV research for plant safety, fostering innovation and capacity development within the agricultural industry, and accelerating progress toward sustainable solutions. China has demonstrated significant commitment and interest in policies and technological advances related to UAV technologies over the past decade. At the same time, the Chinese government is actively advocating for the utilization of UAV systems in plant protection by providing subsidies, implementing policies, and funding research ventures. In 2016, the Ministry of Agriculture initiated a CNY 96 million research and development program focusing on advancing technology and intelligent equipment systems for UAV applications. Several research projects were carried out by teams across China, specifically in Hunan, Xinjiang, Henan, and Yunnan provinces, focusing on crops like rice, citrus fruits, cotton, and wheat. These varied investigations emphasized protecting plants from pests and diseases, weed control, developing UAVs, smart machinery, operating, spraying, performance, tools, low-altitude tasks, and low-volume spray technologies. The overarching ambition of these efforts was to combat the overuse of pesticides, outdated plant protection methods, and scarcity of independent research and development abilities.

In 2015 and 2016, Centra Documents underscored the importance of innovative intelligent technologies and the rapid evolution of plant protection aviation applications. This project was one of the initial national crucial research and development initiatives in 2016, concentrating on “Air-Ground High-Efficiency Technology and Intelligent Equipment”. In 2017, the Ministry of Science and Technology expanded support for critical technology and equipment research and development for agricultural aviation operations. Simultaneously, the Civil Aviation Administration of China, the Ministry of Agriculture and Rural Affairs, and the Ministry of Finance launched pilot programs offering subsidies for purchasing farm machinery, like standard UAV operations (Figure 5 and Figure 9). The 2018 Pilot Program of Subsidies for Agricultural Machinery aimed to boost technological innovations, investigation, and manufacturing of agricultural items, expediting product testing, identification, and marketing. In 2018, the National Natural Science Foundation of China allocated substantial funds towards a highly ambitious project focused on effectively utilizing drone-based pesticide dispersal for agricultural protection purposes. Furthermore, local governments accelerated modernization efforts in farming through the acquisition of UAVs for comprehensive prevention services, which led to a notably large market expansion of 41.5%. Back in 2016, the alliance established seven companies and four research institutes for the monitoring of the extensive 20 million mu stretches of wheat, rice, and corn fields using their fleet of 5540 UAVs for innovative study and technological advancement initiatives. The coalition, comprising over 130 enterprises and 40 scientific institutions, intends to deploy more than 100,000 UAVs across a region of one billion mu by the year 2020 [1]. This collaborative effort has significantly encouraged farmers and agricultural companies to embrace UAV technology through notable advancement [8,9,188]. The implementation of China’s 13th Five-Year Plan in 2015 notably bolstered governmental support for the UAV sector. Subsidies for UAVs are widely recognized as a valuable resource and are outlined in the “List of Subsidies for Machine Purchase.” Farmers benefit from subsidies ranging from 30% to 50% for UAVs, with continuing improvements in procedures and subsidies. The goal is to foster technological progress, address technical hurdles in agricultural aviation, and propel China’s modernization of plant protection while aiming for zero growth in chemical pesticide use.

11. Transforming Plant Protection into an Economic Imperative

UAVs have revolutionized traditional spraying techniques by streamlining processes, enhancing pest monitoring capabilities, and facilitating the deployment of natural predators. Their stability, extensive spraying range, and precise maneuverability bolster operational efficiency while satisfying modern plant protection requirements. By providing a cost-effective solution, UAVs effectively reduce operational expenses, fuel consumption, and maintenance costs. Technological advancements have made UAVs accessible to farmers, eliminating pilot wages and minimizing fuel usage. Moreover, UAVs increase productivity and decrease labor expenses. The meticulous compilation of data on diseases, pests, and crop health through sensors and cameras aids informed decision-making for superior farm administration and sustainability. Utilizing UAVs promises a guaranteed return on investment due to their pinpoint accuracy, economic benefits, and augmented yields. UAVs optimize resource allocation, guide strategic decision-making, and elevate operational effectiveness, thereby cultivating a positive trajectory for return on investment over time. UAVs are increasingly being integrated into plant protection frameworks, providing immediate economic dividends, and supporting broader sustainability goals [165,166]. By mitigating environmental degradation, limiting chemical runoff, and boosting ecosystem vitality through decreased pesticide use and timely hazard identification, UAVs are at the forefront of modern agricultural practices. Their growing prevalence in the agricultural landscape is attributable to their cost efficiency, return on investment potential, and sustainability merits. UAVs optimize crop management methodologies, culminating in augmented effectiveness, profitability, and ecological stewardship [183,189].

11.1. Sustainable Technologies for Pest and Disease Surveillance

Innovative UAV applications play a pivotal role in identifying and managing threats, leveraging cutting-edge sensors to streamline monitoring and early recognition of issues. These technologies are at the forefront of transforming sustainability by allowing accurate and prompt pinpointing of risks. A notable study utilized UAVs to track Drosophila suzukii pests in Europe, highlighting their potential in automating detection and quantification. Sophisticated payloads integrated into UAVs facilitate sustainable detection within farms. High-resolution cameras, multispectral instruments, and thermal imaging allow for variations in crop health to be spotted, enabling swift identification and targeted solutions as (Figure 7) details [139,190]. An imaginative UAV-based approach identified 13–16 mm long, red, fluorescent powder-coated brown marmorated stink bugs in the grass, providing a speedy, effective, and cost-efficient replacement to manual marking and capturing while extending collection duration [119]. Integrating machine learning and artificial intelligence enhances UAV-driven detection, allowing timely responses, reduced losses, and sustainable practices by finding occurrences and symptoms as Section 9 (Figure 4) discusses. Lan et al. [78] obtained hyperspectral images of citrus orchards by UAV and established a discriminant model to identify HLB in the test orchards. Furthermore, UAVs outfitted with transponders could monitor locust and airborne insect populations [190]. Cooperative research evaluates the performance of UAVs, such as in the detection of Asian long-horned beetles, for overseeing air quality and detection [191,192]. UAVs are revolutionizing precision agriculture by facilitating sustainable detection through advanced sensing and real-time surveillance. As technology progresses, integration into farming will greatly boost productivity [193]. Moving forward, further exploration of UAV integration holds promising prospects for enhancing the efficiency and effectiveness of management strategies. Incorporating emerging enhancements, like improved sensors and analysis capabilities, positions UAVs as indispensable precision farming tools [194,195]. Additionally, refining and applying artificial intelligence and machine learning will continue refining accuracy and speed using UAVs, enabling quicker responses and solutions. This evolution towards increasingly sophisticated applications anticipates the seamless integration of health monitoring and identification into precision operations, ultimately optimizing yields and reducing environmental impact.

11.2. Real-Time Prediction Systems

Real-time data, early detection of outbreaks, and precise application of treatments are indispensable for achieving sustainable pest management by preventing pests from taking hold and inflicting agricultural losses. Isolating field infestations of pests and diseases is laborious and unpredictable work due to the lack of reliable or cost-effective sampling approaches. UAVs play a pivotal role in swift pest detection by leveraging high-resolution cameras and sophisticated sensors, empowering farmers to act upon initial signs of infestation, thereby minimizing crop damage and reducing reliance on reactive measures (Figure 4). UAVs enable farmers to monitor pest populations in real-time via regular surveillance flights, generating precise pest distribution maps, and pinpointing pest activity dependent on crop health and temperature, allowing for proactive pest management strategies to be implemented. By offering real-time data, UAVs help farmers anticipate pest pressures and tailor their agricultural practices accordingly. They amalgamate weather predictions and pest modeling algorithms, thereby strengthening farm resilience and controlling pest-induced losses in crop yields. UAVs are instrumental in integrated pest management (IPM) efforts, cultivating environmental equilibrium and minimizing dependence on chemical pesticides. By integrating pest data with agronomic practices, farmers can develop customized plans, oversee natural pest predators, and assess the effectiveness of their methods. UAVs outfitted with sensing and control capabilities may assist in managing pest outbreaks by enabling plants to adapt to biotic stressors through modifications in leaf light reflectance. Cutting-edge techniques can be deployed to detect these alterations (Figure 4), as demonstrated across various arthropod-based pests like spider mites, aphids, and lepidopteran larvae [196,197]. The precise application of abiotic stress alleviation measures, like water and fertilizer, proves to be an effective strategy in mitigating the risk of arthropod pest infestations [198]. There is a shifting focus in pest management from a reactive approach involving insecticides towards a prevention-oriented strategy that emphasizes crop health [199]. The utilization of UAVs outfitted with actuators and sensors to monitor plant stress levels and pre-apply fertilizers and water could facilitate this transition. The maneuverability and small-area treatment capabilities of UAVs offer diverse applications in pest management and outbreak control, thereby enhancing real-time monitoring and prediction systems.

11.3. Farm and Field Surveillance Systems

Traditionally, farm surveillance has relied heavily on labor-intensive manual processes that require farmers to inspect their vast tracts of land intensively. However, emerging UAV technologies have streamlined surveillance, vastly improving productivity. High-resolution sensors and aerial photography now allow farmers to thoroughly evaluate crop health, identify infestations, and prioritize areas that require immediate attention (Figure 4 and Figure 7). This information empowers strategic optimization of applications, customized irrigation, and tailored management to maximize yields while minimizing waste. Farmers can now judiciously use chemicals to enhance their impact and apply targeted treatments that minimize environmental impact and the risk of resistance, as well as preserve beneficial organisms and promote biodiversity. Additionally, UAVs with autonomous navigation and evasion in challenging conditions can precisely and promptly apply inputs. In developing nations where smallholders combine farming and fish-rearing, integrating production across pond barriers shows promise for a unified system. UAVs play an essential role in monitoring offshore aquaculture due to mobility and affordability, enhancing access to remote sites. By leveraging UAVs, sensors, artificial intelligence, and the Internet of Things, farmers can efficiently gather insights and interconnect operations, propelling automation and mechanization [200]. The integration of sophisticated real-time observation and prediction fundamentally reshapes practices, profoundly empowering farmers with unmatched understanding, productivity, and sustainability. UAVs bearing hyperspectral, multispectral, and color cameras supply comprehensive canopy images, further refining precision techniques.

11.4. Role of UAVs in Rescue Missions

In plant protection settings, unforeseen occurrences like pest epidemics, disease outbreaks, and adverse weather events can endanger crop health and livelihoods. Additionally, disasters such as floods, storms, and wildfires can have devastating effects. Swift action is critical to reduce losses and recover crop yield. Remote sensing and imaging technologies play a crucial role in identifying and evaluating crop damage during intervention efforts and collecting comprehensive information and spatial patterns. Integrated pest management (IPM) practices effectively shield fields by combining control approaches. Therefore, UAV systems can aid in monitoring losses, as well as navigating challenging terrains or severe weather conditions. UAVs can deliver life-saving medical supplies before medical personnel or ambulances arrive on-site. In rural and remote regions, vast fields are interspersed with dense trees and orchards, while urban environments are characterized by towering structures and crowded pathways. Common causes of power line malfunctions involve extreme weather, wildfires, tree collapses, large billboards, and occasionally solar panels [104]. Scholars are investigating UAV-led power lines/tree maintenance, including removing snow and other fault inspection methodologies to boost electricity reliability and quality by pinpointing and preventing faults and mitigating the constraints of conventional approaches. Operational tasks like inspection can be undertaken by UAVs by utilizing a mounted digital camera to capture power line images and other related accessories to perform operations [201]. Multi-rotor UAV systems are favored due to their exceptional 3D maneuverability and ability to observe aerial information at a close range by hovering [183,202,203]. The integration of smart control technology and optimized route-planning algorithms can enhance UAV-system performance in safeguarding agricultural fields, tackling climate change, and addressing the needs stemming from population growth. Community involvement and partnerships among stakeholders are pivotal for the success of intervention efforts, engaging farmers, extension services, researchers, and governmental bodies to pool resources and synchronize response initiatives. Intervention activities that encompass plant protection strategies, UAV utilization, remote sensing, IPM approaches, localized treatments, and stakeholder partnerships are essential to alleviate crop losses and revive agricultural productivity in light of pest and disease outbreaks, as well as severe weather incidents.

11.5. Role of UAVs Releasing Natural Enemies and Pollinations

UAVs possess great promise to revolutionize agricultural practices by enabling the distribution of natural enemies for pest management and boosting pollination efforts. Through different technologies, such as AI and sensing, UAVs are capable of releasing beneficial insects and other natural adversaries to counteract biological pests across farmland. This approach serves to cut production costs, improve the effectiveness of biological control, promote environmentally friendly practices, and reduce chemical pesticide usage. By assisting with pollination in agricultural settings and supplementing wild pollinators, UAVs have the potential to enhance pollination services. They are adept at monitoring flower densities, transporting pollen or helpful insects, and refining pollination strategies, all contributing to increased crop yields and agricultural productivity. These devices incorporate deep learning algorithms, image analysis, pollen dispensers, and data collection onboard to identify plants, map flight paths, and approximate blossom locations. Moreover, UAVs excel at adhering to pre-defined flight routes, distributing pollination agents onto pistils, and navigating obstacles to ensure safe and effective pollination processes. Advances in UAV technology present hopeful solutions for boosting agricultural output through using artificial pollination techniques and introducing natural enemies [113,204]. Additionally, UAVs provide scalability and adaptability in artificial pollination endeavors, allowing farmers to pollinate large fields or orchards quickly and economically. Furthermore, UAVs can be programmed automatically, thereby decreasing the need for human intervention, and enabling continuous pollination services. Jiyu et al. [205] found that the high-speed air generated by UAVs had an uneven impact on pollen distribution. UAVs excel at optimizing performance in targeted areas of the field by facilitating efficient aerial delivery of natural enemies, such as parasites, predators, nematodes, fungi, bacteria, and viruses [206]. For prompt augmentative biological pest management, UAVs can prove to be a valuable resource. Moreover, UAVs can precisely dispense natural enemies to designated locations as needed [207,208]. Multiple companies and research institutions worldwide have developed effective and user-friendly Trichogramma UAV applications aimed at controlling the widespread pest of the two-spotted spider mite [209,210]. Various entities are offering services to distribute predatory mites through UAVs on crops like strawberries and corn to battle the two-spotted spider mite [211]. Specially designed dispensing mechanisms have been created for ladybirds and other aphid adversaries using UAVs [98,212,213,214,215]. While UAVs exhibit potential for deploying natural enemies and enhancing pollination processes, interdisciplinary collaboration is essential to address challenges such as regulatory barriers, technological constraints, and socio-economic considerations [216,217,218,219,220,221,222]. UAVs can strengthen agriculture by facilitating natural enemy distribution and boosting pollination services. They can decrease reliance on chemical pesticides, refine pest control methodologies, and foster sustainable crop protection and production.

12. Future Prospects

The rapid development of UAV technology in plant protection has greatly improved traditional methods by adopting advanced technologies. Excellent spraying capabilities, higher productivity, ease of use, and precise intelligent control systems are driving explosive growth in the adoption of UAVs. The future of agricultural UAVs will rely on innovations to continuously update their functionality, productivity, and autonomy. As a result, UAVs will become increasingly versatile and adaptable to diverse applications. Although using UAVs for pest monitoring and control has a promising prospect and broad development space, there are limited research opportunities, complex regulations, as well as high costs that currently hinder their widespread use in many countries. Droplet drift, challenges from crop canopies, and layout limitations can also affect their efficiency. Future research should focus on new ingredients, additives, and nanotechnology to develop non-toxic formulations that address these barriers. UAVs are effective in controlling pests; however, effective management of migratory pests by UAVs requires further research on real-time pest control solutions. Furthermore, effective delivery of beneficial organisms via UAVs deserves extensive research. It is critical to increase UAV technology, expand standards, and adopt affordable sensors while strengthening capacity and extending flight time. There is considerable potential for integrating UAVs into other agricultural areas such as crop pollination. Power management, hybrid battery technology, and intelligent spray systems need to be prioritized through research. Future work should also focus on improving sensing technology, positioning methods, and algorithms to enhance the mapping of pests, diseases, and weeds. Further investigation is needed to pattern the monitoring of UAVs, especially in terms of microclimate and weather recovery capabilities. The key to effectiveness is to enhance artificial intelligence to improve decision-making and pest management strategies. The foundation of efficiency is to ensure strong power supply regulation. In addition to new regulations and software optimization, additional research is needed on UAV applications to benefit small farms and public safety. Developing interoperable standards is essential for technological innovation. Subsidized purchase programs for agricultural equipment emphasize the growing demand for research into UAV technology. Certification of UAVs for rescue operations is vital while safeguarding regulatory compliance. This addition will enable farmers to address developing challenges and prospects in the supply chain. These limitations can be addressed by research and development support, training, workshops, and financial incentives. Up-to-date knowledge of new technologies will enhance UAV operations and serve as a benchmark for global advancement. The continuous improvement in theoretical systems and technologies will further promote the development of plant protection in China and other regions, leading to enhanced efficiency, environmental sustainability, and adherence to safety regulations.