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Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system “perception-decision-control,” the environment perception and map construction strategy based on 3D lidar is constructed for the complex environment in orchards. At the same time, millimeter-wave radar is further selected for multi-source information fusion for the perception of obstacles. The extraction of orchard navigation lines is achieved by formulating a four-step extraction strategy according to the obtained lidar data. Finally, aiming at the control problem of plant protection machine, the ADRC control strategy is adopted to enhance the noise immunity of the system. Different working conditions are designed in the experimental section for testing the obstacle avoidance performance and navigation accuracy of the autonomous navigation sprayer. The experimental results show that the unmanned vehicle can identify the obstacle quickly and make an emergency stop and find a rather narrow feasible area when a moving person or a different thin column is used as an obstacle. Many experiments have shown a safe distance for obstacle avoidance about 0.5 m, which meets the obstacle avoidance requirements. In the navigation accuracy experiment, the average navigation error in both experiments is within 15 cm, satisfying the requirements for orchard spray operation. A set of spray test experiments are designed in the final experimental part to further verify the feasibility of the system developed by the institute, and the coverage rate of the leaves of the canopy is about 50%.

Small unmanned aerial vehicles (UAVs) have been widely used in different aspects of modern farming management, including pest and disease control in China in recent years. In this study, the spray performance of a small plant protection UAV at low volume spray was evaluated by adjusting the pesticide dosage and adding aerial spraying adjuvants. Droplet deposition, droplet density, coverage, control effect and pesticide residue from field trials were assessed. In addition, the residue and control effect of UAV spray were compared to manual knapsack at high volume spray. The results showed that, the adjuvant applying improved the efficiency of UAV spray. Also, the adjuvant applying reduced the dosage of imidacloprid by 20%. However, there was no significant difference on initial residue between UAV spray and knapsack spray. Thus, plant protection UAV spraying pesticide by adding appropriate adjuvant showed the ability of improving the pesticide effectiveness by improving the control efficiency, reducing the pesticide dosage and residue.

Furthermore, this model exhibited faster convergence rate, superior classification balance, and enhanced generalization capability compared to other methods available in literature; thus, providing a more reliable basis for decision-making regarding precise application of biological and chemical control strategies in citrus production.The dataset created by Lyu et al. consists of images capturing citrus psyllids in their natural habitats, and they proposed a lightweight detection model based on spatial channel interaction. Variable-rate automated spraying systems The variable-rate automated spraying technology for pesticides plays a vital role in achieving accurate pesticide application by gathering data on factors including pest severity, crop canopy morphology and density (Tumbo et al, 2007). In terms of positioning, the real-time position was determined through a reliable method of fusing multiple sensors for positioning, which involves transforming the RTK information into the initial position and doing a normal distribution transformation between the current frame point cloud and the scaffold reference point cloud to match the point cloud position. Additionally, the average maximum void length was measured at 0.124m while the average relative localization errors at speeds of 0.2 m/s, 0.4 m/s, and 0.6 m/s were found to be 0.026 m, 0.029 m, and 0.046 m respectively; all with standard deviations less than or equal to 0.06 m. The proposed algorithm reduced average localization error by approximately79 .9% when compared to track deduction algorithms. [...]it can be concluded that even in low-density canopy environments within greenhouses, the AF-PCP SLAM algorithm is capable of precisely mapping and localizing robots.

The intelligent pesticide application techniques in orchards have grown rapidly worldwide due to the decrease in agricultural populations and the increase in labor costs. However, whether and how intelligent pesticide application techniques are better than conventional pesticide application remains unclear. Here, we evaluated the performance of the unmanned aircraft vehicle (UAV) and unmanned ground vehicle (UGV) on pesticide application, ecological environment protection, and human’s health protection compared to conventional manual methods. We quantified characteristics from the aspects of working effectiveness, efficiency, environmental pollution, water saving and carbon dioxide reduction. The results showed that the UAV application has the advantages of a higher working efficiency and less environmental pollution and natural resource consumption compared to the UGV and conventional manual methods despite of its worse spray performance The UGV application techniques could improve spray performance at the cost of high environmental pollution. The conventional spray gun technique was unfriendly to environmental and resource protection although it showed a better spray performance. Thus, the balance of improving spray performance and controlling environmental pollution is the key to improve the performance of UAV and UGV technology in the future. The study could be useful in the development of intelligent pesticide application techniques and provide scientific support for the transition of intelligent management in orchards.

Pesticide application by unmanned agricultural aerial vehicles (UAVs) has rapidly developed in China and other Asian counties. Currently, tank-mix spray adjuvants are usually added into pesticide solutions to reduce spray drift and facilitate droplet deposition and control efficacy. The currently used tank-mix adjuvants are all derived from conventional ground sprays, and their mechanisms of action in aerial applications are still unclear. In order to clarify the spraying characteristics and control efficacy of those adjuvants in aerial sprays, the performances of various types of tank-mix adjuvants were compared by analyzing droplet spectrum, drift potential index (DIX) in a wind tunnel, field deposition and control efficacy on wheat rust and aphids. The atomization results showed that the addition of adjuvants could change the droplet spectrum of liquid, and the results suggest that droplet size is an effective indicator of spray drift potential. In the field application, the meteorological conditions are complex and uncontrollable, and the effects of adjuvants on droplet deposition and distribution were not significant. Compared with the control solution, there was no significant difference in the deposition amount of each adjuvant solution, and the CVs of deposition were higher than 30%. Adding adjuvants to the spray solution can significantly improve the control efficacy of pesticides on wheat aphids and rust and also prolong the duration of the pesticide. Our results suggest that tank-mix adjuvants should be added when UAVs are used for aerial application. This study can be used as a reference to the research and development or selection of adjuvants in aerial sprays of UAVs.

Air-assisted sprayers are widely used in orchards for pest and disease control. However, air-assisted spray deposition on the abaxial surface of leaves is often limited. In this study, a method to achieve satisfactory spray deposition on the abaxial leaf surface and an assessment of factors that affect abaxial surface deposition were investigated. The effects of leaf angle, wind speed, platform velocity, and nozzle type were assessed. Abaxial surface coverage was significantly affected by leaf angle, wind speed, and nozzle type, of which the leaf angle had the strongest impact. The leaf angle largely determines the abaxial surface area exposed to the wind field. When the abaxial surface is situated leeward, deposition of droplets on the abaxial surface is difficult. Therefore, to improve abaxial surface exposure for field application, the exposure probability of the abaxial surface at different angles between the leaf and the airflow (α) was examined. The relationship was well represented by a logistic growth curve. The exposure probability exceeded 95% when the α value was greater than 5°. The latter finding was verified by conducting a field application in which the deposition efficiency on the abaxial surface (DEAS) was calculated. Adjustment of the airflow angle based on the theoretical value achieved DEAS of 49.9% and 109.3% in the middle and upper layers of the canopy, respectively, whereas the DEAS was less than 30% if the airflow angle was not adjusted. This is caused by the difference in the exposure probability of the back of the leaf. The results provide a reference for adjustment of the wind field of air-assisted sprayers in field applications.

In recent years, unmanned aerial vehicles (UAVs) for plant protection have achieved rapid development in China. In order to test and evaluate the performances of pesticides application and development status of UAVs in China, four typical UAV models were selected to test the spraying coverage, penetrability, droplets density and the work efficiency. The results showed that the deposition and spraying liquid coverage were inconsistent both in lateral and longitudinal direction. Under the condition of the similar amount of spray volume and operation parameters, the volume median diameter (VMD) of the droplet was negatively correlated with the coverage density. The failure of the UAVs for plant protection mainly took up on the blockage of nozzle, transfusion tube and the liquid pump. The failure rate of UAVs took up 3.73%-4.36% of the total working time. The operation of UAVs during ground service took up 50% of the total working time, the preparation work took up 10%, and the route planning took up around 10%, while net operation time only took up around 30%. On the whole, the high efficiency of UAV was not fully achieved; the daily operated area was not in a satisfactory level now. The spraying performances of UAVs still need further improvement.

IntroductionWhile the integrated rice-crayfish ( Procambarus clarkii ) farming system (IRCFS) is widely developing in China, the widespread use of Unmanned Aerial Spraying Systems (UASS) to protect rice from pests has led to potential pesticide risk for the crayfish in IRCFS. Therefore, it is crucial to examine UASS’s spray deposition and drift in IRCFS.MethodIn this study, we used the oligonucleotide sequence-tracking / dot-blotting (OSTDB) method to trace pesticide spraying. We collected detailed data not only on spray loss in the paddy fields, but also on spray drift in the breeding ditches caused by upwind and downwind spray areas. Additionally, pesticide residues in the breeding ditches were measured using LC-MS/MS by collecting water samples after pesticide application.ResultsThe data analysis indicated that the spray loss in the paddy field was significantly greater than that in the breeding ditches. The spray drift in the breeding ditches, caused by the upwind spray area, was seven times higher than that originating from the downwind spray area. Furthermore, the results also revealed that the bulk flow between the paddy fields and the breeding ditches contributed a substantial amount of pesticide residue to the water body in the breeding ditches. In addition, we investigated the acute toxicities of common insecticides using in paddy fields, including thiamethoxam (THI), chlorantraniliprole (CHI), THI·CHI-Mix and THI·CHI-WG.DiscussionThe results demonstrated that the spray losses and spray drift from UASS spray applications of these pesticides in IRCFS would not cause acute toxicity or death in crayfish. These findings provide important materials for establishing pesticide application standards and guiding the field testing of droplet deposition and drift in IRCFS.

The surface texture, a major way to decrease friction and wear of the cylinder-piston ring friction pair, was conducted on cylinder-piston ring friction pair specimen using the orthogonal experimental design method to investigate the effect of different texture parameters (size, depth, shape, and surface density) of the friction and wear characteristics. Through simulation analysis, the texture parameters that affect the friction and wear characteristics are obtained. Using the evaluation method of friction coefficient and mass wear rate, the influence sequence and optimal values of texture parameters that affect friction and wear characteristics are obtained through range analysis. The results show that, after surface texture treatment under mixed lubrication conditions, the friction characteristics of the friction pair have changed and the friction coefficient and friction and wear rate have been significantly reduced. The results show that the triangular texture has a good antifriction effect, the texture depth is deepened, and the surface density and the size increases have a positive effect on the improvement of friction and wear. An ultra-depth microscope was used to observe the wear morphology of the friction and wear tests. The results show that the weakening of the third body wear by the texturing treatment and the maintenance of oil lubrication are the main reasons for reducing friction and wear.

Thrips have become some of the most challenging pests to control in mango production due to their short developmental time, hidden locations and resistance to pesticides, in the tropical regions of China. To improve pesticides efficacy, the tank-mix adjuvants Qi Gong (QG) and the thrips attractant Lv Dian (LD) were added when using an unmanned aerial vehicle (UAV) to control thrips. The surface tension, contact angle on mango leaves, droplet size, spreading rate, and drying time of the two tank-mix adjuvants were determined. The effects of the two tank-mix adjuvants using a UAV sprayer on the droplet coverage and control efficacy against thrips on mango inflorescences were tested through field trials. The results showed that both QG and LD could reduce the surface tension of the liquid and the contact angle on mango leaves and could increase the spreading performance. The droplet coverage in the upper layer of the canopy was about 2% higher than that in the lower layer, and the coverage at the top of the panicle was 5% higher than that at the bottom. QG improved the deposition coverage of mango inflorescences by about 31.5%. The addition of QG increased the efficacy by 18.24% and 8.03%, respectively, at florescence and the young fruit stage. The addition of the LD increased the efficacy by 24.56% and 14.38%, respectively, at florescence and the young fruit stage. These test results can provide a scientific basis for the control of mango thrips with UAVs.