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Core Ideas There is a perception that adoption of precision agriculture has been slow.Precision agriculture is not one technology but a toolkit from which farmers choose what they need.Global Navigation Satellite Systems guidance is being adopted rapidly.Variable rate technology adoption rarely exceeds 20% of farms.Use of precision agriculture technology on non‐mechanized farms is almost nonexistent. There is a perception that adoption of precision agriculture (PA) has been slow. This study reviews the public data on farm level use of PA in crop production worldwide. It examines adoption estimates for PA from completed surveys that utilized random sampling procedures, as well as estimates of adoption using other survey methods, with an objective to document the national or regional level adoption patterns of PA using existing data. The analysis indicates that Global Navigation Satellite Systems (GNSS) guidance and associated automated technologies like sprayer boom control and planter row or section shutoffs have been adopted as fast as any major agricultural technology in history. The main reason for the perception that PA adoption is slow is because PA is often associated with variable rate technology (VRT)—just one of many PA technologies, one of the first adopted by many farmers, but that now rarely exceeds 20% of farms. This level of adoption suggests that farmers like the idea of VRT, but are not convinced of its value. VRT adoption estimates for niche groups of farmers may exceed 50%. The biggest gap in PA adoption is for medium and small farms in the developing world that do not use motorized mechanization.

Pesticide application equipment (PAE) is the last part of the chain during the plant protection process. The use-phase of plant protection products (PPP) has been addressed in two EU Directives: 128/2009/EC and 127/2009/EC. This last one covers all the mandatory technical requirements to be fulfilled by new sprayers prior to their placement in the market. The objective of this research was to develop a potential decision support system (DSS) to evaluate and quantify the degree of implementation of all the required characteristics of new sprayers, including not only the mandatory requirements but also specifications widely described in the corresponding harmonized standard ISO 16119. It includes 10 independent elements of the sprayer, including a list of technical specifications listed in the applied standards ISO 16119 and ISO 16122. The relative influence of every one of the different elements has been quantified based on previous research. The algorithm enables the establishment of an objective relative classification of the sprayers to differentiate among different machines, mainly based on their quantified environmental contamination risk. The DSS can also discriminate among sprayers that should not reach the market due to their non-compliance with any of the mandatory requirements.

Automation is a new frontier in specialty agriculture equipment. Specifically, unmanned aerial vehicles (UAV), machine vision and robotics will increasingly appear in sustainable agricultural systems. The use of small UAVs retrofitted with spraying systems allows precision aerial applications on small targets. These precision applications can result in significant cost savings and reductions in risk to operators during treatments. This paper presents a novel and practical design and development of a small application system capable of being mounted on an unmanned aerial vehicle for agrochemical spraying tasks and an analysis of the quality of the application and economic costs in olive and citrus orchards compared with those of a conventional treatment. Once the equipment had been developed, field trials in super-high-density olive and citrus orchards were undertaken to evaluate the spray deposition efficiency. For comparison with a conventional hydro-pneumatic sprayer, the field tests took into account parameters such as the applied volume rate, spray drift, application time and equipment costs and depreciation. The results obtained indicate that there was a 7 €/ha difference in the application costs between the aerial vehicle and conventional equipment. It is hoped that the conclusions of this work will serve as the basis for a debate about the existing legislation governing this type of aerial work, which can be beneficial in specific cases and should be carried out in a safe and legal manner.

The canopies of high stalk crops, such as maize, intersect the rows at the later stages of growth, making conventional sprayers unable to enter the field for spraying. Air-assisted sprayers are often used to improve the deposition of droplets inside the canopy. In this study, the sprayer structure, the air-assisted system, and the spraying system were designed. The air-assisted conveyor system characteristics were numerically analyzed, and the wind-field distribution was tested. The wind-field distribution results showed that the near-ground wind speed exceeded 5 m s -1 in the sampling interval from 10 to 35 metres. The wind field covered a concentrated spatial area with a downward pressure trend, resulting in better drift resistance and penetration. Field tests for droplet distribution were conducted at three maize heights to verify the powerful air-assisted sprayer's technical performance and working quality. The test results showed that the droplet deposition and coverage decreased gradually along the range direction, and the top layer had the highest deposition and coverage across the canopy. The upper canopy of 0 to 12 metres range demonstrated a greater extent of coverage and deposition. The peak deposition area expanded from 9 to 33 metres in the lower canopy, with an average value of 3.77 μg cm -2 . The droplet coverage within the 30 to 60 metres range only amounted to 15% to 18% of the total coverage.

An orchard variable-rate sprayer applies the appropriate amount of plant protection products only where they are needed based on detection data from advanced sensors, a system that has attracted increasing attention. The latest developments in the detection unit, variable control unit, and signal-processing algorithm of the variable-rate sprayer are discussed. The detection of target position and volume is realized with an ultrasonic sensor, a laser scanning sensor, or other methods. The technology of real-time acquisition of foliage density, plant diseases and pests and their severity, as well as meteorological parameters needs further improvements. Among the three variable-flow-rate control units, pulse width modulation was the most widely used, followed by pressure-based, and variable concentration, which is preliminarily verified in the laboratory. The variable air supply control unit is tested both in the laboratory and in field experiments. The tree-row-volume model, the leaf-wall-area model, and the continuous application mode are widely used algorithms. Advanced research on a variable-rate sprayer is analyzed and future prospects are pointed out. A laser-based variable-rate intelligent sprayer equipped with pulse width modulation solenoid valves to tune spray outputs in real time based on target structures may have the potential to be successfully adopted by growers on a large scale in the foreseeable future. It will be a future research direction to develop an intelligent multi-sensor-fusion variable-rate sprayer based on target crop characteristics, plant diseases and pests and their severity, as well as meteorological conditions while achieving multi-variable control.

A technical–economic analysis was conducted on three different technological levels of spraying equipment for specialty crops, based on the results on precision spraying technologies reported in scientific literature. The application scenarios referred to general protection protocols against fungal diseases adopted in vineyards and apple orchards in Central-Southern Europe. The analysis evaluated the total costs of protection treatments (equipment + pesticide costs), comparing the use of conventional air-blast sprayers (referred to as L0), of on–off switching sprayers (L1), and of canopy-optimised distribution sprayers (L2). Pesticide savings from 10 to 35% were associated with equipment L1 and L2, as compared to L0. Within the assumptions made, on grapevines, the conventional sprayer L0 resulted in the most profitable option for vineyard areas smaller than 10 ha; from 10 ha to approximately 100 ha, L1 was the best option, while above 100 ha, the more advanced equipment L2 resulted in the best choice. On apple orchards, L0 was the best option for areas smaller than 17 ha. Above this value, L1 was more profitable, while L2 never proved advantageous. Finally, in a speculation on possible prospectives of precision spraying on specialty crops, the introduction of an autonomous robotic platform able to selectively target the pesticide on diseased areas was hypothesised. The analysis indicated that the purchase price that would make the robotic platform profitable, thanks to the assumed pesticide and labour savings over conventional sprayers, was unrealistically lower than current industrial cost. This study showed that, in current conditions, profitability cannot be the only driver for possible adoption of intelligent robotic platforms for precision spraying on specialty crops, while on–off and canopy-optimised technologies can be profitable over conventional spraying in specific conditions.

Pesticides in three-dimensional (3D) crops are usually applied sidewise, so the vertical component must be considered for adjusting the applications. For this, different approaches have been proposed. Leaf Wall Area (LWA) was selected to express the minimum dose to be used in efficacy field trials for plant protection product (PPP) authorization in northern areas of Europe, where 3D crops are grown as narrow wall-forming structures. However, southern European areas also managed 3D crops as wide walls or globular crops with non-negligible canopy width. Therefore, a Tree Row Volume (TRV) model is thought to be more appropriate for dose expression. Furthermore, efficacy evaluations for pesticide authorization are usually carried out with manual sprayers in young plantations with medium-sized trees. However, growers normally apply PPP with air-blast sprayers in plantations of different tree sizes. The objective of this study was to determine which dose expression is more suitable in citrus orchards, as well as to analyze, in turn, the influence of the sprayer. The results demonstrated that TRV was the most appropriate for dose expression. Knapsacks and air-blast sprayers distributed the spray on the canopy in different ways, and the size of the vegetation influenced the differences between them. Moreover, knapsack sprayers produced higher ground losses, and air-blast sprayers produced higher potential drift.

The uniform application (UA) of agrochemicals results in the over-application of harmful chemicals, increases crop input costs, and deteriorates the environment when compared with variable rate application (VA). A smart variable rate sprayer (SVRS) was designed, developed, and tested using deep learning (DL) for VA application of agrochemicals. Real-time testing of the SVRS took place for detecting and spraying and/or skipping lambsquarters weed and early blight infected and healthy potato plants. About 24,000 images were collected from potato fields in Prince Edward Island and New Brunswick under varying sunny, cloudy, and partly cloudy conditions and processed/trained using YOLOv3 and tiny-YOLOv3 models. Due to faster performance, the tiny-YOLOv3 was chosen to deploy in SVRS. A laboratory experiment was designed under factorial arrangements, where the two spraying techniques (UA and VA) and the three weather conditions (cloudy, partly cloudy, and sunny) were the two independent variables with spray volume consumption as a response variable. The experimental treatments had six repetitions in a 2 × 3 factorial design. Results of the two-way ANOVA showed a significant effect of spraying application techniques on volume consumption of spraying liquid (p-value < 0.05). There was no significant effect of weather conditions and interactions between the two independent variables on volume consumption during weeds and simulated diseased plant detection experiments (p-value > 0.05). The SVRS was able to save 42 and 43% spraying liquid during weeds and simulated diseased plant detection experiments, respectively. Water sensitive papers’ analysis showed the applicability of SVRS for VA with >40% savings of spraying liquid by SVRS when compared with UA. Field applications of this technique would reduce the crop input costs and the environmental risks in conditions (weed and disease) like experimental testing.

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

Air-assisted boom sprayer is proven to be one of the best pesticide application methods to achieve uniform deposition of droplets in the canopy and improve the effective utilization of pesticides. However, the air flow velocity, air flow volume and air flow direction of the orchard sprayer should match the characteristic parameters of the target canopy, equipment spraying parameters and meteorological conditions so as to improve the spraying quality and reduce environmental pollution. This paper elaborates on the research status of air-assisted field sprayers and orchard sprayers, summarizes the research methods of air-assisted sprayers in four aspects, including experimental verification, theoretical analysis, simulation and structural optimization, and clarifies the advantages and disadvantages of these methods. It also presents two future research and development trends, including the intelligent, precise dynamic regulation of air flow velocity, air flow volume and air flow direction and the instant feedback of spraying quality, hoping to provide a reference for the research of air-assisted spray technology and equipment.