Location: Application Technology Research
2023 Annual Report
Objectives
The long-term objective of this research is to advance spray applications with coordinated intelligent-decision technologies and strategies that enhance pesticide application efficiency and environmental stewardship for efficacious and affordable control of pest insects, diseases and weeds.
Objective 1: Develop intelligent precision technologies to efficiently apply pesticides and bio-products for efficacious and sustainable control of pest insects and arthropods, diseases and weeds to protect horticultural, field and greenhouse crops.
Sub-objective 1.1: Develop a reliable and user-friendly intelligent spray-decision system as a retrofit for new and existing air-assisted sprayers to deliver pesticides and bio-products accurately, economically, and environmentally for field specialty crops.
Sub-objective 1.2: Develop greenhouse intelligent spray systems for real-time control of individual nozzle outputs to improve spray deposition quality and reduce waste of water and chemicals.
Objective 2: Develop coordinated application methodologies to reduce pesticide use, reduce crop protection costs, reduce chemical contaminations to the environment, and protect workers, livestock, natural resources and sensitive ecosystems.
Sub-objective 2.1: Improve spray droplet fading process to maximize coverage area after deposition on plants through coordinating spray parameters including droplet size, formulation physical properties, plant surface morphology, and ambient air conditions.
Sub-objective 2.2: Improve spray droplet retention and reduce runoff on plants through coordinating the influences of droplet size and velocity, travel speed, spray formulation physical properties, crop leaf surface morphology, and leaf surface orientation on dynamic impact, retention, rebound and spread process of spray droplets on plants.
Approach
A versatile intelligent spray control system and mounting kits will be developed as a retrofit to different types of tractor-driven sprayers to deliver pesticides and bio-products for different specialty crops. A microprocessor controlled premixing inline injection module will be developed and integrated into the versatile spray control system. Performance of these sprayers will be tested for their accuracy to manipulate spray deposition, spray drift, off-target loss and spray volume consumption in comparison with conventional sprayers. Efficacy tests will be conducted in nurseries, apple orchards and vineyards to compare pest control, pesticide quantity used, and cost savings for the sprayers with and without intelligent functions. Spray drift models will be developed to predict movement of droplets discharged from conventional and intelligent sprayers under nursery, orchard and vineyard conditions.
Greenhouse intelligent spray systems will be developed for real-time control of individual nozzle outputs to improve spray deposition quality and reduce waste of water and chemicals. The automatic greenhouse spray system will be a retrofit attached to existing watering booms. Laboratory tests will be conducted to validate the spray control system accuracies in spray delay time, nozzle activation and spray volume using artificial objects of different regular geometric shapes and surface textures, and artificial plants of different canopy structures. Spray deposition and pest control efficacy tests in greenhouses will then be conducted to validate the intelligent spray control system.
Microscopic spray droplet spreading times and areas on leaves will be investigated to maximize and stabilize coverage area after deposition on plants. Investigation parameters include droplet size, formulation physical properties, plant surface morphology, and ambient air conditions. Droplet fading rate, absorption rate and residual pattern coverage area will be measured on the waxy, semi-waxy and hairy leaf surfaces, and hydrophilic and hydrophobic glass slide surfaces. Field experiments will be conducted in ornamental nurseries, orchards, greenhouses, vegetables, traditional crops and weeds to verify laboratory discoveries effects of the most influenced factors on droplet spreading areas.
Dynamic effects of spray parameters on the droplet impact, rebound, retention, adhesion, and spread process on plants will be determined. The parameters are droplet size and velocity, travel speed, spray formulation type, and leaf surface morphology and orientation.
Significance of coordinating these parameters to improve spray droplet retention and reduce runoff on plants will be analyzed. Dynamic impact of water-based droplets on plant leaves will also be investigated in a wind tunnel under controlled conditions.
Progress Report
In support of Objective 1, following progress was made:
An air-pinch pulse width modulation (PWM) valve was evaluated to modulate flow rates of hollow-cone nozzles to prevent malfunction. With this valve, spray mixtures only passed through a flexible tube to avoid chemicals directly contacting the moving components inside the valve chamber. The flow rate modulation was performed by pinching the tube back and forth with air-pilot PWM actions. Evaluations included the flow rate modulation capability along with droplet size distributions from three disc-core hollow-cone nozzles coupled with the PWM pinch valve and compared with a conventional electric PWM valve. Both air-pinch and conventional electric PWM valves performed comparably in the flow rate modulation accuracy and droplet size distribution for hollow-cone nozzles operated at 414 and 827 kPa pressures across the duty cycles (DUCs) ranging from 10% to 100%, except for the air-pinch valve that could not activate at 10% DUC. The consistency of droplet sizes across DUCs and accuracy of flow rate modulations demonstrated the potential advantage of using the air-pinch PWM solenoid valve as an alternative for precision variable-rate sprayers to accurately apply different chemicals.
An in-line turbidity sensor module was investigated to monitor concentrations of spray mixtures produced with a premixing in-line injection system developed for precision variable-rate orchard sprayers. A cubic polynomial regression model was established for the relationship between sensor output voltages and mixture concentrations. Sensors were mounted at three in-line locations to detect the mixture uniformity differences in the premixing in-line injection system. The module was found to have adequate precision and accuracy to measure concentrations of spray mixtures with simulated pesticides. Relative errors of the sensor were less than 4.70% and the sensor accuracy did not vary with mixture flow rates. Therefore, there would be a great potential to integrate the in-line turbidity sensor into the variable-rate and even conventional constant-rate sprayers to achieve uniform spray applications in the target field.
A real time variable rate sprayer controlled by a stereo vision system was developed to increase the accuracy of spray applications and reduce the use of crop protection products. The sprayer was designed to detect tree canopies and calculate their volume using depth images from the stereo vision system and discharge corresponding spray volumes every 200 ms through the embedded software in the graphical user interface. The sprayer was evaluated in an apple orchard at different travel speeds (3.2 to 8.0 km/h) for its performance in detecting canopy and measuring its volume. In addition, spray volume, deposition and coverage of the variable rate application of the sprayer were evaluated against a constant rate application. Test results showed that the sprayer detected visually similar tree canopies during the evaluations and travel speed did not influence spray deposition, coverage, or ground losses. The variable rate sprayer reduced the spray volume by more than 44% for the canopy volumes detected in the orchard (<2.2 m3) in comparison to the constant rate spray application. Overall spray volume reductions were 79.1%, 73.8%, 71.0%, and 69.8% when the sprayer traveled at 3.2, 4.8, 6.4, and 8.0 km/h, respectively, compared to the constant rate applications at a travel speed of 8.0 km/h. Moreover, the sprayer reduced total ground loss by 57.6%. The results suggested that stereo vision controlled sprayer could offer a cost-effective real-time variable rate spray benefits for specialty crop growers.
In collaboration with researchers in Spain, a precision sensor-guided spraying system was compared with two typical spraying systems (conventional system, optimized system following the best management practices) for the applied volume and spray drift in an apple orchard at two growth stages. Compared to the conventional system, the precision system reduced the amount of ground drift by over 60% and airborne drift by 80% while the saving of applied volume was achieved by 43%.
In collaboration with researchers at Penn State University, unmanned aerial vehicle (UAV) based imaging systems were investigated to measure apple tree canopy characteristics. A high-resolution red-green-blue camera was attached to the UAV to capture aerial images during the petal fall growth stage. However, this approach experienced overestimation and underestimation of tree characteristics due to aspects including coarser spatial resolution, elevation difference, blockage of the lower canopy and overlapping trees. In addition, a hybrid UAV and ground system was investigated for rapid detection and segment of apple tree leaves infected by diseases. The UAV-based imaging system could provide a quick method to acquire large amounts of data from the orchard; however, it could only provide fire blight infection images at the top view of canopies. In comparison, the ground-based imaging system provided enough images of fire blight infections from the side lower branches. A deep learning model was applied to develop a fire blight disease detector with combined images of top and side canopies acquired from both UAV and ground systems, and provided the identification accuracy up to 90% in complex and uncontrolled orchard environments. Moreover, an automatic system was developed and tested to control spray air volume to simultaneously match the foliage density measurements using a laser sensor under apple orchard conditions. The air flow was regulated by manipulating air inlet diameters using an iris damper. Airflow penetrations to carry spray droplets into apple trees and spray deposition quality were investigated with different tree densities and five damper opening diameters. The airflow control system had a potential to regulate the air volume with slow electro-mechanical motions in real time, thus improving intelligent sprayers with precision variable rates of both liquid and air to further reduce pesticide waste in specialty crop production.
In collaboration with researchers at Washington State University, methods of tree row volume, leaf wall area, and unit canopy row were compared for determining the optimal base spray rates for the intelligent sprayers used in two modern vineyards. Spray deposition and coverage were accessed for the comparisons. For the modified vertical shoot position grape architecture, the base spray rates estimated with the three methods were similar. However, for the high cordon trained juice grape architecture, the tree row volume method provided better spray performance than other two methods. Thus, the tree row volume method was recommended for integration with the intelligent spray system to automatically adjust base spray rates based on the canopy attributes.
In support of Objective 2, following progress was made:
A 3-Dimensional optical surface profiler and the areal roughness parameter for roughness height were used to quantify surface roughness for different leaf types ranging in wettability from very easy to very difficult and roughness from smooth to very rough. Spray solutions were composed of distilled water and various adjuvant concentrations. The adjuvants tested were a crop oil concentrate, a modified seed oil, a nonionic surfactant, an oil-nonionic silicone surfactant blend, and organo-silicone. Droplet motion and impacts were recorded with three ultrahigh-speed video cameras and analyzed using 3D motion analysis software. There was complete deposition for all adjuvant classes on smooth-easy to wet leaves at all concentrations, whereas deposition on rough-hard to wet leaves increased linearly as concentrations increased. On the rough-hard to wet leaves, approximately 70% deposition was achieved for the nonionic and silicone adjuvants at 0.75% and 0.50% concentrations, respectively. Depositions of less than 70% were achieved for the crop oil concentrate, modified seed oil, and oil-silicone adjuvants.
Droplet retention and spread behaviors with seven commercially available adjuvants were tested and compared at different concentrations. Leaf surfaces ranged in roughness and wettability, from very smooth and hydrophilic to very rough and superhydrophobic. Adjuvants were non-ionic surfactant, crop oil, seed oil, organo-silicone, hydrocolloid polymer, or combinations of these agents as functional ingredients. Droplets of approximately 340 µm diameter were emitted from a streamed mono-sized generator. Droplet impact and spread were recorded with a 3-dimensional imaging system consisting of three highspeed digital cameras. Droplets with lower surface tension were more likely to achieve high retention than those with higher surface tension. Also, droplet retention generally decreased with increasing leaf roughness-wettability. Addition of non-ionic, oil or organo-silicone based adjuvant in the spray solutions improved droplet retention on hydrophobic leaves while the organo-silicone based adjuvant achieved the highest retention on superhydrophobic leaf surfaces. Retention of droplets with the hydrocolloid polymer adjuvant were generally comparable to other six adjuvants on the hydrophilic leaves and the hydrophobic leaves with intermediate roughness and wettability but failed to achieve any retention on the superhydrophobic leaves. To improve droplet retention and adhesion, selection of adjuvants for enhancing spray solution performance must comply with leaf surface characteristics.
Accomplishments
1. Air-pinch valve to improve the regulation if hollow-cone nozzles for variable-rate sprayers. Pesticide sprayers are commonly used to achieve efficient and effective crop protection for securing high food quality and quantity. Electric pulse width modulation solenoid valves are the critical component for the sprayers to provide precision variable rate applications. However, these valves pose a potential problem that they cannot shut off completely if sprayers are not rinsed thoroughly after applying adhesive additives or physically incompatible powder pesticides. ARS researchers at Wooster, Ohio, have investigated an air-pinch valve that separated the chemical liquid from the valve chamber as an alternative to the electric valve. They discovered the air-pinch and electric valves performed equivalent accuracy in flow rate modulations for hollow-cone nozzles operated at different pressures. Similarly, droplet size distributions and classifications from the hollow-cone nozzles regulated with both valves were also comparable across the flow rate modulation ranges. Therefore, the air-pinch valve could be an alternative to conventional electric valves by isolating the valve actuation components from contacting chemicals, thus preventing the potential valve shutoff problem. The valve will be recommended to farm equipment companies for further improving the accuracy and reliability of their precision variable rate sprayers.
2. Amendment of spray solutions with adjuvants to increase pesticide application efficiency and reduce leave run-off. Effectiveness of pesticide application systems can be increased significantly by increasing the retention and spread of the impacting droplets on specifically targeted crops that are influenced by the interaction between the adhesive characteristics of the droplets and leaf surface fine structures. ARS researchers at Wooster, Ohio, have investigated the adhesive retention and spreading capabilities of spray droplets containing different types of adjuvants on leaves. The surface roughness and wettability of leaves ranged from hydrophilic to superhydrophobic characteristics. The tested adjuvants represented the non-ionic, oil, organo-silicone, blended, or hydrocolloid polymer-based additives commonly used in pesticide spray solutions. Droplets amended with adjuvants that could reduce the surface tension generally had greater retention rates than water-only droplets on hydrophilic and hydrophobic leaf surfaces. The organo-silicone adjuvant provided the best retention at the concentration of 0.75% or higher to achieve more than 90% retention on the extremely rough and superhydrophobic leaf surface. To achieve the droplet spreading area nearly three times larger than the initial droplets on these leaf surfaces, it required 0.10% adjuvant concentration in the spray solutions. The hydrocolloid polymer adjuvant improved droplet retention on the slightly hydrophobic leaves but was ineffective, providing no retention, on the superhydrophobic leaves; however, addition of this adjuvant to the spray solution retained the droplet settlement shape over time after initial spread on the hydrophilic leaves, thereby achieving similar benefits as other adjuvants to enhance adhesion and minimize run-off of spray deposits. The information from this research provided a scientific baseline for chemical formulators and growers to select or formulate optimal adjuvants to improve pesticide spray application efficiency and increase chemical retention on plants.
Review Publications
Rathnayake, A.P., Sahni, R.K., Khot, L.R., Hoheisel, G.A., Zhu, H. 2022. Intelligent sprayer spray rates optimization to efficiently apply chemicals in modern apple orchards. Journal of the ASABE. 65(6):1411-1420. https://doi.org/10.13031/ja.14654.
Jeon, H., Zhu, H. 2022. Stereo vision controlled variable rate sprayer for specialty crops: part I. Controller development. Journal of the ASABE. 65(6):1397-1410. https://doi.org/10/13031/ja.15227.
Li, X., Knight, R.M., Hocter, J.S., Zhang, B., Zhao, L., Zhu, H. 2022. Effects of electrode materials and dimensions of an electrostatic spray scrubber on water droplet charging for dust removal. Journal of Air and Waste Management Association. 72(12):1442-1453. https://doi.org/10.1080/10962247.2022.2120564.
Mahmud, M.S., He, L., Heinemann, P., Choi, D., Zhu, H. 2023. Unmanned aerial vehicle based tree canopy characteristics measurement for precision spray applications. Smart Agricultural Technology. 4:Article 100153. https://doi.org/10.1016/j.atech.2022.100153.
Knight, R.M., Hocter, J., Milliken, S., Herkins, M., Zhao, L., Zhu, H. 2023. Development and optimisation of full-scale prototype electrostatic precipitators in a laboratory for particulate matter mitigation in poultry facilities. Biosystems Engineering. 230:71-82. https://doi.org/10.1016/j.biosystemseng.2023.03.019.
Knight, R., Herkins, M., Hoctor, J., Milliken, S., Zhao, L., Zhu, H. 2023. Field evaluation of electrostatic precipitators for particulate matter mitigation in a manure-belt layer facility. Biosystems Engineering. 230:131-144. https://doi.org/10.1016/j.biosystemseng.2023.04.005.
Jeon, H., Zhu, H. 2023. Investigation of depth camera potentials for variable-rate sprayers. Journal of the ASABE. 66(1):115-126. https://doi.org/10.13031/ja.15070.
Salcedo, R., Zhu, H., Jeon, H., Ozkan, E., Wei, Z., Gil, E., Campos, J., Roman, C. 2022. Droplet size distributions from hollow-cone nozzles coupled with PWM valves. American Society of Agricultural and Biological Engineers. 65(4):695-706. https://doi.org/10.13031/ja.15064.
Womac, A., Ozkan, E., Zhu, H., Kochendorfer, J., Jeon, H. 2022. Status of spray penetration and deposition in dense field crop canopies. American Society of Agricultural and Biological Engineers. 65(5):1107-1117. https://doi.org/10.13031/ja.15091.
Knight, R.M., Li, X., Hocter, J.S., Zhang, B., Zhao, L., Zhu, H. 2022. Optimization of induction charging of water droplets to develop an electrostatic spray scrubber intended for poultry particulate matter mitigation. Journal of the ASABE. 65(4):815-824. https://doi.org/10.13031/ja.14913.
Mahmud, M., He, L., Zahid, A., Heinemann, P., Choi, D., Krawczyk, G., Zhu, H. 2023. Detection and infected area segmentation of apple fire blight using image processing and deep transfer learning for site-specific management. Computers and Electronics in Agriculture. 209. Article #107862. https://doi.org/10.1016/j.compag.2023.107862.
Salcedo, R., Sanchez, E., Zhu, H., Fabregas, X., Garcia-Ruiz, F., Gil, E. 2023. Evaluation of an electrostatic spray charge system implemented in three conventional orchard sprayers used on a commercial apple trees plantation. Crop Protection. 167: Article #106212. https://doi.org/10.1016/j.cropro.2023.106212.
Campos, J., Zhu, H., Jeon, H., Salcedo, R., Ozkan, E., Gil, E. 2023. Assessment of PWM solenoid valves to manipulate hollow-cone nozzles with different modulation frequencies. Applied Engineering in Agriculture. 39(2): 235-244. https://doi.org/10.13031/aea.15415.
Zhang, Z., Zhu, H., Jeon, H., Ozkan, E., Wei, Z., Salcedo, R. 2023. A turbidity module to measure spray mixture concentration for premixing in-line injection system. Applied Engineering in Agriculture. 39(1):13-21. https://doi.org/10.13031/aea.15245.
Mahmud, M., Zahid, A., He, L., Zhu, H., Choi, D., Krawczyk, G., Heinemann, P. 2023. Development of an automatic airflow control system for precision sprayers based on tree canopy density. Journal of the ASABE. 65(6): 1225-1240. https://doi.org/10.13031/ja.14972.
Roman, C., Jeon, H., Zhu, H., Ozkan, E. 2023. Evaluating kaolin clay as a potential substance for ISO sprayer cleaning system tests. Applied Engineering in Agriculture. 39(3):347-358. https://doi.org/10.13031/aea.15466.
