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A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".

Deadline for manuscript submissions: closed (10 April 2023) | Viewed by 35103

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Prof. Dr. Jiyu Li

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College of Engineering, South China Agricultural University, Guangzhou 510642, China
Interests: UAV; rotor airflow; drone; energy and payload; UAV architecture design; airflow sensor; droplet sensor; operation route planning; control system; artificial intelligence; operation effect; operation efficiency
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Special Issue Information

Dear Colleagues,

There is a current need to improve the effect of the operation efficiency of UAVs for use in agricultural applications. This is one of the most pressing challenges for modern agricultural drones. In this view, the efficiency priority principle in UAV operations is widely recognized because it can maximize the advantage of drones. Therefore, in the current operation efficiency of UAVs it is important to learn more about how to design a UAV pattern to improve the effect of UAV operation. In the course of operation, the use of variable spray, following the arrangement of the coronal layer, suppression drift, multi-machine coordination and optimal energy consumption can guarantee the efficiency and increase the benefits of UAV operation.

The focus of this Special Issue is to develop and evaluate methods to improve the effectiveness of UAV operations. This Issue, titled “Application of UAVs in Precision Agriculture” will cover interdisciplinary research on agriculture and biology, chemistry and engineering. The research will cover UAVs for different crops, including vegetable crops, ornamental crops and large fields, and crops from other management ecosystems. Welcome various types of articles, such as original research papers and comments.

Prof. Dr. Jiyu Li
Guest Editor

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Keywords

agricultural UAVs
effects of operation
efficiency of operation
route planning
energy-consumption matching
variable spray
drift suppression
deposition of droplets

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Published Papers (11 papers)

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Editorial

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4 pages, 169 KiB

Open AccessEditorial

Application of Unmanned Aerial Vehicles in Precision Agriculture

by Zongru Liu and Jiyu Li

Agriculture 2023, 13(7), 1375; https://doi.org/10.3390/agriculture13071375 - 11 Jul 2023

Cited by 8 | Viewed by 4941

Abstract

Agriculture has long been an important part of human activities [...] Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

Research

Jump to: Editorial

15 pages, 3221 KiB

Open AccessArticle

Study on Monitoring SPAD Values for Multispatial Spatial Vertical Scales of Summer Maize Based on UAV Multispectral Remote Sensing

by Jiangtao Ji, Nana Li, Hongwei Cui, Yuchao Li, Xinbo Zhao, Haolei Zhang and Hao Ma

Agriculture 2023, 13(5), 1004; https://doi.org/10.3390/agriculture13051004 - 2 May 2023

Cited by 10 | Viewed by 2108

Abstract

Rapid acquisition of chlorophyll content in maize leaves is of great significance for timely monitoring of maize plant health and guiding field management. In order to accurately detect the relative chlorophyll content of summer maize and study the responsiveness of vegetation indices to SPAD (soil and plant analyzer development) values of summer maize at different spatial vertical scales, this paper established a prediction model for SPAD values of summer maize leaves at different spatial scales based on UAV multispectral images. The experiment collected multispectral image data from summer maize at the jointing stage and selected eight vegetation indices. By using the sparrow search optimized kernel limit learning machine (SSA-KELM), the prediction models for canopy leaf (CL) SPAD_CL and ear leaf (EL) SPAD_EL were established, and a linear fitting analysis was conducted combining the measured SPAD_CL values and SPAD_EL values on the ground. The results showed that for SPAD_CL, the R² of the linear fitting between the predicted values and measured values was 0.899, and the RMSE was 1.068. For SPAD_EL, the R² of linear fitting between the predicted values and the measured values was 0.837, and the RMSE was 0.89. Compared with the model established by the partial least squares method (PLSR), it is found that the sparrow search optimized kernel limit learning machine (SSA-KELM) has more precise prediction results with better stability and adaptability for small sample prediction. The research results can provide technical support for remote sensing monitoring of the chlorophyll content of summer maize at different spatial scales. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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19 pages, 6688 KiB

Open AccessArticle

Flight Parameter—Wind Vortex Characteristic Control Model of a Four-Multirotor Unmanned Aerial Vehicle Operating in Pesticide Spraying of Rice

by Zhijie Liu, Gangao Fan, Siyan Ye, Zhixun Zhang, Han Wu, Bo Long, Huifen Li, Hui Cheng, Longmei Wu and Jiyu Li

Agriculture 2023, 13(4), 892; https://doi.org/10.3390/agriculture13040892 - 18 Apr 2023

Cited by 5 | Viewed by 1837

Abstract

The downwash airflow generated by the rotors can enhance the penetration of pesticide droplets, allowing them to penetrate deeper into the canopy and more comprehensively control pests. Downwash air will produce a “wind vortex” in plant canopy, and the parameters of a “wind vortex” represent the effect of pesticide deposition to a certain extent. To obtain the corresponding relationship between wind vortices and flight parameters and control the effect of pesticide spraying, this paper carried out unmanned aerial vehicle (UAV) flight experiments in the field. Wind vortices were generated in rice canopy by downwash airflow, and the parameters of wind vortices were obtained by identifying wind-vortex images using the inter-frame difference method. The wind-vortex parameter control model was established, which can calculate the altitude and speed of the UAV when applying pesticide according to the target wind-vortex parameter. The deviations in the altitude were determined to be 0.67 and 0.43 m, and the deviations in the speed were 0.29 and 0.35 m/s during downwind and headwind UAV operations, respectively. The model relation functions were established, and their accuracies were found to be 97.1%, 92.3%, 69%, and 58% (downwind), and 97%, 78.4%, 62%, and 57% (upwind), respectively, indicating that downwind UAV operation leads to a clear relation between the wind-vortex parameters and the UAV-flight parameters. The model establishes the corresponding relationship between the wind-vortex parameters and flight parameters, which provides a theoretical basis for studying the precise application control method of UAV. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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13 pages, 2890 KiB

Open AccessArticle

Evaluation of Spray Drift of Plant Protection Drone Nozzles Based on Wind Tunnel Test

by Guobin Wang, Tongsheng Zhang, Cancan Song, Xiaoqing Yu, Changfeng Shan, Haozheng Gu and Yubin Lan

Agriculture 2023, 13(3), 628; https://doi.org/10.3390/agriculture13030628 - 6 Mar 2023

Cited by 8 | Viewed by 4936

Abstract

The use of drones in agriculture is expanding at a brisk pace in crop production due to the superiority in precision, efficiency, and safety of their applicators. However, their potential drift risk also raises concern for users and regulatory authorities. The method of wind tunnel research can effectively evaluate the weighted influence of each drift factor, especially the drift characteristics of the nozzle and spray solution. Based on the wind tunnel test results, centrifugal nozzles have a higher drift risk than hydraulic nozzles, even with a similar DV₅₀. The cumulative drift rate of the centrifugal nozzle at 2 m downwind was 90.1% compared to the LU12001 nozzle’s 40.6% under the wind speed of 3.5 m/s. Compared with the same coding as the flat fan hydraulic nozzle, the IDK nozzle can effectively reduce the drift rate. For the tested nozzles, DV₅₀ and wind speed had a linear relationship with drift rate, and the sampling location had an exponential or logarithmic relationship with drift rate. Spray adjuvants, especially modified vegetable oils, had a significant effect on reducing the amount of drift. The results of this experiment provide a reference for the selection of nozzles and the addition of spray adjuvants. Further clarifying the spray drift characteristics of drones until a drift prediction model is available is still the focus of research. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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15 pages, 10441 KiB

Open AccessArticle

Research on UAV Remote Sensing Method of Mold Detection Suitable for Pericarp of Citri Reticulatae ‘Chachi’ Warehouses

by Guoqi Yan, Jialei Qu, Wei Li, Dongyi Chen, Chumin Zhong, Hao Luo, Guoliang Ou and Jiasi Mo

Agriculture 2023, 13(3), 528; https://doi.org/10.3390/agriculture13030528 - 22 Feb 2023

Cited by 1 | Viewed by 1667

Abstract

Once the Pericarp of Citri Reticulata ‘Chachi’ (PCRC) develops mildew while in storage, the rapid spread of the flora after the occurrence of mold can cause huge losses. As such, inspecting whether the PCRC is moldy is important. In this paper, we propose an alternative inspection method, namely that of utilizing a small UAV with a camera to inspect the PCRC mildew in the top stacks under consideration. Specifically, we first address the light problem in the collected images with different lights via a multi-spectral method, and find that 625–740 nm of lighting has a significant effect on mildew. Second, we utilize the ultrared 1.4R-G method to extract the features of mildew with Otus binarization. We can see that the mold-free area is less than 95% in an image categorized as having mildew. The proposed mildew inspection method achieved 93.3% accuracy. Our method could send the inspection information to a control system, achieving rapid closed-loop automatic control and reducing the mildew-related loss. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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19 pages, 7460 KiB

Open AccessArticle

Optimization-Design and Atomization-Performance Study of Aerial Dual-Atomization Centrifugal Atomizer

by Zhou Yang, Jiaxiang Yu, Jieli Duan, Xing Xu and Guangsheng Huang

Agriculture 2023, 13(2), 430; https://doi.org/10.3390/agriculture13020430 - 11 Feb 2023

Cited by 4 | Viewed by 2994

Abstract

The aerial atomizer is the most essential component of the plant protection UAV (unmanned aerial vehicle). However, the structural optimization of existing aerial atomizers lacks comprehensive consideration of spray parameters and structural parameters, and there is a shortage of available atomizer spray models, resulting in the unstable effect of UAV application. In our previous work, an aerial dual-atomization centrifugal atomizer was developed. In order to obtain an aerial atomizer with good atomization effect and its atomization model, structural optimization at different rotation speeds and flow rates of the atomizer, and its atomization performance, are studied in this paper. Firstly, with the droplet volume median diameter (VMD) and spectral width (SRW) as the evaluation index, through the single-factor, Plackett–Burman and Box–Behnken tests, the influence of rotation speed, flow rate, tooth number and tooth shape were studied. The regression models of the droplet VMD and SRW were established using multiple quadratic regression fitting of the test data. Secondly, in order to achieve the lowest droplet VMD and SRW, the response surface method and post-hoc multiple comparison method were used to obtain the optimized structure of the atomizer’s rotation ring at different rotation speeds (600–7000 r/min) and flow rates (500–1000 mL/min). Lastly, with the effective swath width (ESW) of the optimized atomizer as the evaluation index, through the Box–Behnken test, the influence of rotation speed, flow rate and spray height were studied. The multiple quadratic regression model of ESW was established with the test data. The test results indicated that rotation speed, flow rate and tooth number had a significant effect on droplet VMD and SRW; tooth shape had no significant effect on the droplet VMD and SRW, however, the square tooth shape had the best atomization effect; and rotation speed, flow rate and spray height had a significant effect on ESW. The optimized structural parameters were tooth shape: square, and tooth number: 20. The determination coefficient

R^{2}

of the regression model of VMD, SRW and ESW were 0.9976, 0.9770 and 0.9974, respectively, which indicates that the model was accurate, and can evaluate and predict the spray effect. This paper provides an optimized dual-atomization centrifugal atomizer, and its regression models of VMD, SRW and ESW for UAV applications can provide a reference for efficient UAV spraying. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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18 pages, 5157 KiB

Open AccessArticle

Evaluation of Liquid Atomization and Spray Drift Reduction of Hydraulic Nozzles with Four Spray Adjuvant Solutions

by Qi Liu, Changfeng Shan, Haiyan Zhang, Cancan Song and Yubin Lan

Agriculture 2023, 13(2), 236; https://doi.org/10.3390/agriculture13020236 - 19 Jan 2023

Cited by 6 | Viewed by 2525

Abstract

The droplet size distribution following pesticide application practices can significantly impact droplet drift and non-target organisms (animals and plants). However, the relationship among liquid sheet breakup, drop formation, and droplet drift is an area that has been studied over the past 65 years but is still not fully understood. The objectives of this study were severalfold: to examine the liquid sheet breakup following the use of different adjuvants (sodium dodecyl sulfate, aerosol OT, and silicone at 1%) and their effects on the drift via three commonly used commercial spray nozzles (XR, AIXR, and TXVK). The spray sheet and initial droplet size spectrum for each spray was detected by a particle image velocimetry (PIV) system, and the drift for each treatment was measured in a wind tunnel. The nozzle type and the spray solution were found to significantly affect the liquid sheet breakup characteristics. AIXR produced large droplets, and TXVK with short liquid sheet length produced more small droplets. All adjuvants used in these experiments increased the formation of large droplets upon atomization while simultaneously reducing driftable fines (e.g., drops %<150 µm). The drift potential can be reduced by up to 66.1% when switching from a fine spray quality (TXVK) to a coarse spray quality (AIXR). The SDS adjuvant provided the most effective drift reduction for XR and TXVK nozzles showing reduced drift potential by 69.2% and 66.3%, respectively, while the silicone adjuvant showed the largest drift reduction for AIXR of 78.3%. The correlation between the liquid sheet length and D_V0.5 was positive for XR and TXVK nozzles, and there was a significant positive correlation between %<150 µm and drift potential for all nozzles. This work suggests that the drift can be reduced significantly by changing the nozzle type and adding pesticide adjuvant into spray solution, which provided data support for the drift reduction of plant protection drones. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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14 pages, 9092 KiB

Open AccessArticle

A Method to Study the Influence of the Pesticide Load on the Detailed Distribution Law of Downwash for Multi-Rotor UAV

by Fengbo Yang, Hongping Zhou, Yu Ru, Qing Chen and Lei Zhou

Agriculture 2022, 12(12), 2061; https://doi.org/10.3390/agriculture12122061 - 1 Dec 2022

Cited by 5 | Viewed by 2049

Abstract

Multi-rotor plant protection Unmanned Aerial Vehicles (UAVs) have suitable terrain adaptability and efficient ultra-low altitude spraying capacity, which is a significant development direction in efficient plant protection equipment. The interaction mechanisms of the wind field, droplet, and crop are unclear, and have become the bottleneck factor restricting the improvement of the deposition quality. This paper suggests a method to study the influence of the pesticide load on the detailed distribution law of downwash for a six-rotor UAV. Based on a hexahedral structured mesh, a 3D numerical calculation model was established. Analysis showed that the relative errors between the simulated and measured velocities in the z-axis were less than 11% when the downwash air flow was stable. Numerical simulations were carried out for downwash in hover under 0, 1, 2, 3, 4, and 5 kg loads. The effect of load on the airflow was evident, and the greater the load was, the higher the wind speed of downwash would be. Then, the influence of wing interference on the distribution of airflow would be more pronounced. Furthermore, under the rotation of the rotor and the extrusion of external atmospheric pressure, the “trumpet” phenomenon appeared in the downwash airflow area. As an extension, the phenomenon of the “shrinkage–expansion” was shown in the longitudinal section under heavy load, while the phenomenon of “shrinkage–expansion–shrinkage” was present under light load. After that, based on the detailed analysis of the downwash wind field, the spray height of this multi-rotor UAV was suggested to be 2.5 m or higher, and the nozzle was recommended to be mounted directly under the rotor and to have the same rotation direction as the rotor. The research in this paper lays a solid foundation for the proposal of the three-zone overlapping matching theory of wind field, droplet settlement, and canopy shaking. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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14 pages, 4196 KiB

Open AccessArticle

Farmland Obstacle Detection from the Perspective of UAVs Based on Non-local Deformable DETR

by Dashuai Wang, Zhuolin Li, Xiaoqiang Du, Zenghong Ma and Xiaoguang Liu

Agriculture 2022, 12(12), 1983; https://doi.org/10.3390/agriculture12121983 - 23 Nov 2022

Cited by 9 | Viewed by 2797

Abstract

In precision agriculture, unmanned aerial vehicles (UAVs) are playing an increasingly important role in farmland information acquisition and fine management. However, discrete obstacles in the farmland environment, such as trees and power lines, pose serious threats to the flight safety of UAVs. Real-time detection of the attributes of obstacles is urgently needed to ensure their flight safety. In the wake of rapid development of deep learning, object detection algorithms based on convolutional neural networks (CNN) and transformer architectures have achieved remarkable results. Detection Transformer (DETR) and Deformable DETR combine CNN and transformer to achieve end-to-end object detection. The goal of this work is to use Deformable DETR for the task of farmland obstacle detection from the perspective of UAVs. However, limited by local receptive fields and local self-attention mechanisms, Deformable DETR lacks the ability to capture long-range dependencies to some extent. Inspired by non-local neural networks, we introduce the global modeling capability to the front-end ResNet to further improve the overall performance of Deformable DETR. We refer to the improved version as Non-local Deformable DETR. We evaluate the performance of Non-local Deformable DETR for farmland obstacle detection through comparative experiments on our proposed dataset. The results show that, compared with the original Deformable DETR network, the mAP value of the Non-local Deformable DETR is increased from 71.3% to 78.0%. Additionally, Non-local Deformable DETR also presents great performance for detecting small and slender objects. We hope this work can provide a solution to the flight safety problems encountered by UAVs in unstructured farmland environments. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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19 pages, 5916 KiB

Open AccessArticle

Preliminary Evaluation of Spraying Quality of Multi-Unmanned Aerial Vehicle (UAV) Close Formation Spraying

by Pengchao Chen, Fan Ouyang, Yali Zhang and Yubin Lan

Agriculture 2022, 12(8), 1149; https://doi.org/10.3390/agriculture12081149 - 3 Aug 2022

Cited by 15 | Viewed by 3503

Abstract

Chemical application using unmanned aerial vehicles (UAVs) has received significant attention from researchers and the market in recent years. The concept of using drones for collaborative spraying was proposed by manufacturers for improving intelligence and work efficiency. However, chemical spraying is a professional technology in which spraying quality is the main concern. Using drones to achieve multi-unmanned aerial vehicle formation spraying and evaluating the spraying effect has not yet been reported. In this study, an indoor test platform and two UAVs for field experiments were built. Indoor and outdoor trials of close formation spraying were carried out in Guangzhou and Changji, China from the end of 2018 to 2019, respectively. The droplet density and distribution uniformity of droplets were evaluated from multiple spray overlap areas. It can be seen that simultaneous spraying was better than sequential spraying with the indoor spraying results in the outer fuselage overlap area (S1), and spraying in a short-interval mode can improve the droplet deposition distribution in the overlapping spraying area. Additionally, the droplet distribution result of sequential spraying was better than that of simultaneous spraying in the route center overlap area (S2). Also, the droplet distribution result of the long-interval mode was better than that of the short-interval mode. The uniformity of the droplets’ distribution in two spray width areas (S3) did not change significantly among the treatments. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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22 pages, 4062 KiB

Open AccessArticle

Single-Neuron PID UAV Variable Fertilizer Application Control System Based on a Weighted Coefficient Learning Correction

by Dongxu Su, Weixiang Yao, Fenghua Yu, Yihan Liu, Ziyue Zheng, Yulong Wang, Tongyu Xu and Chunling Chen

Agriculture 2022, 12(7), 1019; https://doi.org/10.3390/agriculture12071019 - 13 Jul 2022

Cited by 16 | Viewed by 3259

Abstract

Agricultural unmanned aerial vehicles (UAVs), which are a new type of fertilizer application technology, have been rapidly developed internationally. This study combines the agronomic characteristics of rice fertilization with weighted coefficient learning-modified single-neuron adaptive proportional–integral–differential (PID) control technology to study and design an aerial real-time variable fertilizer application control system that is suitable for rice field operations in northern China. The nitrogen deficiency at the target plot is obtained from a map based on a fertilizer prescription map, and the amount of fertilizer is calculated by a variable fertilizer application algorithm. The advantages and disadvantages of the two control algorithms are analyzed by a MATLAB simulation in an indoor test, which is integrated into the spreading system to test the effect of actual spreading. A three-factor, three-level orthogonal test of fertilizer-spreading performance is designed for an outdoor test, and the coefficient of variation of particle distribution Cv (a) as well as the relative error of fertilizer application λ (b) are the evaluation indices. The spreading performance of the spreading system is the best and can effectively achieve accurate variable fertilizer application when the baffle opening is 4%, spreading disc speed is 600 r/min, and flight height is 2 m, with a and b of evaluation indexes of 11.98% and 7.02%, respectively. The control error of the spreading volume is 7.30%, and the monitoring error of the speed measurement module is less than 30 r/min. The results show that the centrifugal variable fertilizer spreader improves the uniformity of fertilizer spreading and the accuracy of fertilizer application, which enhances the spreading performance of the centrifugal variable fertilizer spreader. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

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