Objects in agricultural soils will seriously affect the farming operations of agricultural machinery.At present,it still relies on human experience to judge abnormal Gounrd-penetrting Radar(GPR)signals.It is difficult...Objects in agricultural soils will seriously affect the farming operations of agricultural machinery.At present,it still relies on human experience to judge abnormal Gounrd-penetrting Radar(GPR)signals.It is difficult for traditional image processing technology to form a general positioning method for the randomness and diversity characteristics of GPR signals in soil.Although many scholars had researched a variety of image-processing techniques,most methods lack robustness.In this study,the deep learning algorithm Mask Region-based Convolutional Neural Network(Mask-RCNN)and a geometric model were combined to improve the GPR positioning accuracy.First,a soil stratification experiment was set to classify the physical parameters of the soil and study the attenuation law of electromagnetic waves.Secondly,a SOIL-GPR geometric model was proposed,which can be combined with Mask-RCNN's MASK geometric size to predict object sizes.The results proved the effectiveness and accuracy of the model for position detection and evaluation of objects in soils;then,the improved Mask RCNN method was used to compare the feature extraction accuracy of U-Net and Fully Convolutional Networks(FCN);Finally,the operating speed of agricultural machinery was simulated and designed the A-B survey line experiment.The detection accuracy was evaluated by several indicators,such as the survey line direction,soil depth false alarm rate,Mean Average Precision(mAP),and Intersection over Union(IoU).The results showed that pixel-level segmentation and positioning based on Mask RCNN can improve the accuracy of the position detection of objects in agricultural soil effectively,and the average error of depth prediction is 2.87 cm.The results showed that the detection technology proposed in this study integrates the advantage of soil environmental parameters,geometric models,and artificial intelligence algorithms to provide a high-precision and technical solution for the GPR non-destructive detection of soils.展开更多
Spray characteristics are the fundamental factors that affect droplet transportation downward,deposition,and drift.The downwash airflow field of the Unmanned Aviation Vehicle(UAV)primarily influences droplet depositio...Spray characteristics are the fundamental factors that affect droplet transportation downward,deposition,and drift.The downwash airflow field of the Unmanned Aviation Vehicle(UAV)primarily influences droplet deposition and drift by changing the spray characteristics.This study focused mainly on the effect of the downwash airflow field of the UAV and nozzle position on the droplet spatial distribution and velocity distribution,which are two factors of spray characteristics.To study the abovementioned characteristics,computational fluid dynamics based on the lattice Boltzmann method(LBM)was used to simulate the downwash airflow field of the DJI T30 six-rotor plant protection UAV at different rotor rotational speeds(1000-1800 r/min).A particle image velocimetry system(PIV)was utilized to record the spray field with the downwash airflow field at different rotational speeds of rotors(0-1800 r/min)or different nozzle positions(0,0.20 m,0.35 m,and 0.50 m from the motor).The simulation and experimental results showed that the rotor downwash airflow field exhibited the‘dispersion-shrinkage-redispersion’development rule.In the initial dispersion stage of rotor airflow,there were obvious high-vorticity and low-vorticity regions in the rotor downwash airflow field.Moreover,the low-vorticity region was primarily concentrated below the motor,and the high-vorticity region was mainly focused in the middle area of the rotors.Additionally,the Y-direction airflow velocity fluctuated at 0.4-1.2 m under the rotor.When the rotor airflow developed to 3.2 m below the rotor,the Y-direction airflow velocity showed a slight decrease.Above 3.2 m from the rotor,the Y-direction airflow velocity started to drastically decrease.Therefore,it is recommended that the DJI T30 plant protection UAV should not exceed 3.2 m in flight height during field spraying operations.The rotor downwash airflow field caused the nozzle atomization angle,droplet concentration,and spray field width to decrease while increasing the vortex scale in the spray field when the rotor system was activated.Moreover,the increase in rotor rotational speed promoted the abovementioned trend.When the nozzle was installed in various radial locations below the rotor,the droplet spatial distribution and velocity distribution were completely different.When the nozzle was installed directly below the motor,the droplet spatial distribution and velocity distribution were relatively symmetrical.When the nozzle was installed at 0.20 m and 0.35 m from the motor,the droplets clearly moved toward the right under the induction of stronger rotor vortices.This resulted in a higher droplet concentration in the right-half spray field.However,the droplet moved toward the left when the nozzle was installed in the rotor tip.For four nozzle positions,when the nozzle was installed at 0 or 0.20 m from the motor,the droplet average velocity was much higher.However,the droplet average velocity was slower when the nozzle was installed in the other two positions.Therefore,it is recommended that the nozzle is installed at 0 or 0.20 m from the motor.The research results could increase the understanding of the downwash airflow field distribution characteristics of the UAV and its influence on the droplet spatial distribution and velocity distribution characteristics.Meanwhile,the research results could provide some theoretical guidance for the choice of nozzle position below the rotor.展开更多
With the characteristic of flexible and precise,unmanned aerial vehicles(UAVs)for low volume applications are increasing substantially and quickly around the globe.However,little attention has been paid to the study o...With the characteristic of flexible and precise,unmanned aerial vehicles(UAVs)for low volume applications are increasing substantially and quickly around the globe.However,little attention has been paid to the study of wheat herbicides with UAV,especially the research on the spray volume and droplet size of the herbicide sprayed by UAVs.The objectives of this study were to compare the droplet deposition from a typical commercial UAV under four different spray volumes of 7.5 L/hm2,15.0 L/hm2,22.5 L/hm2,and 30.0 L/hm2 and three different volume median diameter(VMD)of 150μm,200μm,and 300μm during winter wheat weeding period.DepositScan software was used to analyze droplet deposition parameters including the percentage of spray coverage and the number of droplets in various sampling positions.The test results showed that the droplet deposition waseffected by each factor andtheirinteractions.When the spray volume was 7.5 L/hm2,the effect of VMD on the percentage of spray coverage was not significant.However,these variation rules were changed to smaller droplets with greater coverage when the spray volume higher than 15.0 L/hm2.In all treatments,the number of droplets increased with decreasing VMD or increasing spray volume.The maximum percentage of spray coverage and the number of droplets that were achieved under the VMD of 150μm and the spray volume of 30.0 L/hm2 were 12.8%and 40.0 droplets/cm2,respectively.The variation coefficients of the percentage of spray coverage and the number of droplets were 29.0%-73.3%and 20.2%-54.1%,respectively.The most uniform deposition was achieved under the spray volume of 15.0 L/hm2and the VMD of 150μm.The results revealed the effect of droplet size and spray volume parameters on droplet deposition,which was useful for guiding farmers on how to use UAVs for weeding in winter wheat fields.展开更多
With the gradual deterioration of the ecological environment and the increase in requirements for the quality of modern life,the use of pesticides is bound to develop towards higher pesticide utilization and less envi...With the gradual deterioration of the ecological environment and the increase in requirements for the quality of modern life,the use of pesticides is bound to develop towards higher pesticide utilization and less environmental pollution,and the low-volume spraying for agricultural aviation operation combined with the Drift Reducing Technologies(DRTs)may be a useful way to achieve this goal.Based on an analysis of the spray drift mechanism and the primary factors influencing aerial spraying,previous research on DRTs in aerial spraying were reviewed and summarized,and it was found that DRTs in aerial spraying can effectively reduce the environmental pollution caused by pesticide drift by reducing the spraying amount of pesticides and improving the control effect of pesticides,included aerial electrostatic spray technology,aerial spray adjuvant,aerial air-assisted spray technology,drift reducing nozzles and aerial variable-rate spray technology.And according to the analysis of the current research status,some suggestions and countermeasures to reduce droplet drift of agricultural aviation spraying were put forward from the aspects of strengthening the research on DRTs for plant protection Unmanned Aerial Vehicle(UAV)and adopting reasonable DRTs methods.It is hoped that provide reference and guidance for the enterprises’product improvement and users’practical operation,and play the advantages of precision agricultural aviation spraying fully.展开更多
With the development of Unmanned Aerial Vehicle(UAV)sprayers,the application of low-volume spraying of harvest-aid and other agrochemicals to cotton using UAVs is becoming a new agronomic trend worldwide.The effect of...With the development of Unmanned Aerial Vehicle(UAV)sprayers,the application of low-volume spraying of harvest-aid and other agrochemicals to cotton using UAVs is becoming a new agronomic trend worldwide.The effect of spray volume and canopy density for UAV spraying is significant but was rarely studied.In this study,five representative spray volumes were explored to examine the effect of spray volume on deposition and harvest-aid efficacy for cotton using a UAV sprayer.To explore the effect of canopy density,similar tests were carried out in a field located nearby with a lower leaf area index(LAI).A conventional trailer boom sprayer was selected for comparison.Different spray volumes had a significant effect on defoliation,but had no significant effect on boll opening and fiber quality.A higher defoliation rate was achieved in the lower LAI field.The total rate of defoliation using the UAV was inferior to the boom sprayer in the high LAI field for lower deposition and defoliation rate in the lower canopy.Considering the deposition,defoliation rate,and working efficiency,a spray volume of 15.0 L/hm^(2) with an average droplet size of 150μm is recommended for UAV application.展开更多
基金supported by the Laboratory of Lingnan Modern Agriculture Project(Grant No.NT2021009)Guangdong University Key Field(Artificial Intelligence)Special Project(No.2019KZDZX1012)and the 111 Project(D18019)+3 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515110554)China Postdoctoral Science Foundation(Grant No.2022M721201)the National Natural Science Foundation of China(Grant No.31901411)The Open Competition Program of the Top Ten Critical Priorities of Agricultural Science and Technology Innovation for the 14th Five-Year Plan of Guangdong Province(No.2022SDZG03).
文摘Objects in agricultural soils will seriously affect the farming operations of agricultural machinery.At present,it still relies on human experience to judge abnormal Gounrd-penetrting Radar(GPR)signals.It is difficult for traditional image processing technology to form a general positioning method for the randomness and diversity characteristics of GPR signals in soil.Although many scholars had researched a variety of image-processing techniques,most methods lack robustness.In this study,the deep learning algorithm Mask Region-based Convolutional Neural Network(Mask-RCNN)and a geometric model were combined to improve the GPR positioning accuracy.First,a soil stratification experiment was set to classify the physical parameters of the soil and study the attenuation law of electromagnetic waves.Secondly,a SOIL-GPR geometric model was proposed,which can be combined with Mask-RCNN's MASK geometric size to predict object sizes.The results proved the effectiveness and accuracy of the model for position detection and evaluation of objects in soils;then,the improved Mask RCNN method was used to compare the feature extraction accuracy of U-Net and Fully Convolutional Networks(FCN);Finally,the operating speed of agricultural machinery was simulated and designed the A-B survey line experiment.The detection accuracy was evaluated by several indicators,such as the survey line direction,soil depth false alarm rate,Mean Average Precision(mAP),and Intersection over Union(IoU).The results showed that pixel-level segmentation and positioning based on Mask RCNN can improve the accuracy of the position detection of objects in agricultural soil effectively,and the average error of depth prediction is 2.87 cm.The results showed that the detection technology proposed in this study integrates the advantage of soil environmental parameters,geometric models,and artificial intelligence algorithms to provide a high-precision and technical solution for the GPR non-destructive detection of soils.
基金financially supported by the 111 Project(Grant No.D18019)Laboratory of Lingnan Modern Agriculture Project(Grant No.NT2021009)+4 种基金the Leading Talents of Guangdong Province Program(Grant No.2016LJ06G689)the National Natural Science Foundation of China(Grant No.32271985)the Natural Science Foundation of Guangdong Province(Grant No.2022A 1515011008No.2022A1515011535)Liaoning Provincial Education Department Key Research Project(Grant No.LSNZD 202005).
文摘Spray characteristics are the fundamental factors that affect droplet transportation downward,deposition,and drift.The downwash airflow field of the Unmanned Aviation Vehicle(UAV)primarily influences droplet deposition and drift by changing the spray characteristics.This study focused mainly on the effect of the downwash airflow field of the UAV and nozzle position on the droplet spatial distribution and velocity distribution,which are two factors of spray characteristics.To study the abovementioned characteristics,computational fluid dynamics based on the lattice Boltzmann method(LBM)was used to simulate the downwash airflow field of the DJI T30 six-rotor plant protection UAV at different rotor rotational speeds(1000-1800 r/min).A particle image velocimetry system(PIV)was utilized to record the spray field with the downwash airflow field at different rotational speeds of rotors(0-1800 r/min)or different nozzle positions(0,0.20 m,0.35 m,and 0.50 m from the motor).The simulation and experimental results showed that the rotor downwash airflow field exhibited the‘dispersion-shrinkage-redispersion’development rule.In the initial dispersion stage of rotor airflow,there were obvious high-vorticity and low-vorticity regions in the rotor downwash airflow field.Moreover,the low-vorticity region was primarily concentrated below the motor,and the high-vorticity region was mainly focused in the middle area of the rotors.Additionally,the Y-direction airflow velocity fluctuated at 0.4-1.2 m under the rotor.When the rotor airflow developed to 3.2 m below the rotor,the Y-direction airflow velocity showed a slight decrease.Above 3.2 m from the rotor,the Y-direction airflow velocity started to drastically decrease.Therefore,it is recommended that the DJI T30 plant protection UAV should not exceed 3.2 m in flight height during field spraying operations.The rotor downwash airflow field caused the nozzle atomization angle,droplet concentration,and spray field width to decrease while increasing the vortex scale in the spray field when the rotor system was activated.Moreover,the increase in rotor rotational speed promoted the abovementioned trend.When the nozzle was installed in various radial locations below the rotor,the droplet spatial distribution and velocity distribution were completely different.When the nozzle was installed directly below the motor,the droplet spatial distribution and velocity distribution were relatively symmetrical.When the nozzle was installed at 0.20 m and 0.35 m from the motor,the droplets clearly moved toward the right under the induction of stronger rotor vortices.This resulted in a higher droplet concentration in the right-half spray field.However,the droplet moved toward the left when the nozzle was installed in the rotor tip.For four nozzle positions,when the nozzle was installed at 0 or 0.20 m from the motor,the droplet average velocity was much higher.However,the droplet average velocity was slower when the nozzle was installed in the other two positions.Therefore,it is recommended that the nozzle is installed at 0 or 0.20 m from the motor.The research results could increase the understanding of the downwash airflow field distribution characteristics of the UAV and its influence on the droplet spatial distribution and velocity distribution characteristics.Meanwhile,the research results could provide some theoretical guidance for the choice of nozzle position below the rotor.
基金The authors acknowledge that this work was financially supported by the Leading Talents of Top Talents Program for One Case One Discussion of Shandong Provincethe Development Special Funds on Science and Technology to Guide Local by the Central Government:“Research and Development on Technology and Equipment of Precision Agriculture Aviation”+4 种基金Science and Technology Development Program of Zibo(Grant No.2018kj010073)Program of Shandong Provincial Collaborative Innovation Center of Dry-farming Intelligent Agricultural EquipmentYoung Innovative Talents Project of Regular Institutions of Higher Education of Guangdong Province(Grant No.2018KQNCX020)Key Science and Technology Plan of Guangdong Province(Grant No.2017B010116003)The authors acknowledge Corteva Agroscience Technology(Shanghai)Co.,Ltd for providing corresponding materials,and also thank reviewers and editors for giving relevant revision advice to improve the paper.
文摘With the characteristic of flexible and precise,unmanned aerial vehicles(UAVs)for low volume applications are increasing substantially and quickly around the globe.However,little attention has been paid to the study of wheat herbicides with UAV,especially the research on the spray volume and droplet size of the herbicide sprayed by UAVs.The objectives of this study were to compare the droplet deposition from a typical commercial UAV under four different spray volumes of 7.5 L/hm2,15.0 L/hm2,22.5 L/hm2,and 30.0 L/hm2 and three different volume median diameter(VMD)of 150μm,200μm,and 300μm during winter wheat weeding period.DepositScan software was used to analyze droplet deposition parameters including the percentage of spray coverage and the number of droplets in various sampling positions.The test results showed that the droplet deposition waseffected by each factor andtheirinteractions.When the spray volume was 7.5 L/hm2,the effect of VMD on the percentage of spray coverage was not significant.However,these variation rules were changed to smaller droplets with greater coverage when the spray volume higher than 15.0 L/hm2.In all treatments,the number of droplets increased with decreasing VMD or increasing spray volume.The maximum percentage of spray coverage and the number of droplets that were achieved under the VMD of 150μm and the spray volume of 30.0 L/hm2 were 12.8%and 40.0 droplets/cm2,respectively.The variation coefficients of the percentage of spray coverage and the number of droplets were 29.0%-73.3%and 20.2%-54.1%,respectively.The most uniform deposition was achieved under the spray volume of 15.0 L/hm2and the VMD of 150μm.The results revealed the effect of droplet size and spray volume parameters on droplet deposition,which was useful for guiding farmers on how to use UAVs for weeding in winter wheat fields.
基金supported by the National Natural Science Foundation of China(Grant No.31901411)the Science and Technology Planning Project of Guangdong Province(Grant No.2019B020208007)+2 种基金the Young Innovative Talents Project of Regular Institutions of Higher Education of Guangdong Province(Grant No.2018KQNCX020)Science and Technology Planning Project of Guangzhou(202103000090)the Key R&D projects in Hainan Province(ZDYF2020195).
文摘With the gradual deterioration of the ecological environment and the increase in requirements for the quality of modern life,the use of pesticides is bound to develop towards higher pesticide utilization and less environmental pollution,and the low-volume spraying for agricultural aviation operation combined with the Drift Reducing Technologies(DRTs)may be a useful way to achieve this goal.Based on an analysis of the spray drift mechanism and the primary factors influencing aerial spraying,previous research on DRTs in aerial spraying were reviewed and summarized,and it was found that DRTs in aerial spraying can effectively reduce the environmental pollution caused by pesticide drift by reducing the spraying amount of pesticides and improving the control effect of pesticides,included aerial electrostatic spray technology,aerial spray adjuvant,aerial air-assisted spray technology,drift reducing nozzles and aerial variable-rate spray technology.And according to the analysis of the current research status,some suggestions and countermeasures to reduce droplet drift of agricultural aviation spraying were put forward from the aspects of strengthening the research on DRTs for plant protection Unmanned Aerial Vehicle(UAV)and adopting reasonable DRTs methods.It is hoped that provide reference and guidance for the enterprises’product improvement and users’practical operation,and play the advantages of precision agricultural aviation spraying fully.
基金funded by Shandong Province Natural Science Foundation(Grant No.ZR2021QC154)the Top Talents Program for One Case One Discussion of Shandong Province+2 种基金the Key science and technology plan of Guangdong Province(Grant No.2017B010116003)China Agriculture Research System(CARS-15-22)the National Natural Science Foundation of China(Grant No.31901411).
文摘With the development of Unmanned Aerial Vehicle(UAV)sprayers,the application of low-volume spraying of harvest-aid and other agrochemicals to cotton using UAVs is becoming a new agronomic trend worldwide.The effect of spray volume and canopy density for UAV spraying is significant but was rarely studied.In this study,five representative spray volumes were explored to examine the effect of spray volume on deposition and harvest-aid efficacy for cotton using a UAV sprayer.To explore the effect of canopy density,similar tests were carried out in a field located nearby with a lower leaf area index(LAI).A conventional trailer boom sprayer was selected for comparison.Different spray volumes had a significant effect on defoliation,but had no significant effect on boll opening and fiber quality.A higher defoliation rate was achieved in the lower LAI field.The total rate of defoliation using the UAV was inferior to the boom sprayer in the high LAI field for lower deposition and defoliation rate in the lower canopy.Considering the deposition,defoliation rate,and working efficiency,a spray volume of 15.0 L/hm^(2) with an average droplet size of 150μm is recommended for UAV application.
