Location: Application Technology Research
2025 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
This report summarizes progress for this project, which began May 20, 2020, and terminated January 27, 2025. Research will be continued under the new project 5082-30500-002-000D, “Integration of Sensor-Vision Guided Precision Spray Systems for Sustainable Crop Production and Protection”.
Under Objective 1, significant progress was made on investigation of spray characteristics and pest control efficacy of an intelligent sprayer, developed and transferred for commercialization by ARS engineers at Wooster, Ohio, in a commercial apple orchard in Tennessee in collaboration with University of Tennessee. The precision variable-rate spray mode at an application rate lower than the default rate was tested and compared with the conventional, constant-rate spray mode. Foliage was scouted biweekly for diseases and two arthropods, and apples were scouted weekly for disease. The precision spray mode reduced the pesticide volume by 58% while maintaining pesticide coverage at or above the overspray threshold in all but one canopy location. Non-target ground applications were greatly reduced in variable-rate mode. Foliar disease measured as leaf spot incidence and leaf spot count severity was not affected by the spray mode. Fruit rot incidence, fruit rot severity, and disease index for fruit were also not affected by spray mode. Fruit disease index remained low throughout both seasons.
Effects of droplet sizes on spray penetration into lower soybean canopy positions were investigated in a wind tunnel at crosswind speeds of 0.15 to 2.4 m/s. Soybean plants grown in rectangular pots were arranged to mimic a high-density field planting condition (0.38 m row spacing). Three stationary spray nozzles, positioned 0.5 m above the canopy, released spray for 3 seconds at 275 kPa. Spray deposition was measured with water-sensitive papers at three heights inside canopy. Droplet sizes from the nozzles ranged from medium to extremely coarse classifications. Results showed all nozzles produced adequate spray coverage at the top canopy, but it was significantly reduced at the lower part of canopy. Further investigations are needed to optimize spray techniques to improve the lower-canopy penetration.
An automated air-assist system for orchard sprayers, integrated with a custom air channel, electric fans, a battery, and controllers, was developed to improve spray delivery to intended targets. The system adjusted fan speeds based on sensor inputs to optimize airflow for spray applications. Integrated into a variable-rate sprayer, it was compared to a conventional sprayer in an apple orchard. The automated system increased spray deposits by 55%, reduced spray drift by 77% while using 41.3% less spray volume and 65% less air volume than the conventional sprayer.
An inline premixing injection system was developed to minimize pesticide leftover problems associated with conventional tank mixture preparations. The system separated water and pesticide concentrates in different storage tanks and mixed them in small, on-demand batches to supply for the precision variable-rate sprayers in real time. Key components included injection and water pumps, a microcontroller, inline mixers, premixing tanks, and automatic flow control valves. Integrated into a variable-rate sprayer with a laser sensor, the system featured a new graphical user interface for seamless operation. Laboratory tests verified the accuracy of premixing concentrations, followed by field evaluations in an apple orchard to assess spray deposition, coverage, and off-target losses.
A greenhouse sprayer equipped with a laser scanning sensor was developed to apply the amount of agrochemicals based on the plant foliage volume in greenhouse production. A custom designed algorithm and control system was developed to process plant architectures including surface contours and areas detected by the laser sensor. The system, installed on a greenhouse boom sprayer, was tested for spray timing, volume, and nozzle activation accuracy in laboratory settings. Commercial greenhouse tests were conducted to optimize spray coverage for crops with varied structures, followed by comprehensive evaluations of spray volume savings.
Under Objective 2, relationships between spray additive solution properties and plant leaf morphology were investigated to maximize droplet coverage to improve spray application efficiency. Droplet evaporation, absorption, and spreading were tested across various leaf surfaces, spray additives, droplet sizes, and temperatures under controlled environmental conditions. Statistical analyses identified key factors enhancing droplet spreading on leaves. A mono-size droplet generator was used to investigate droplet impact, rebound and retention on leaves. Tests were conducted under controlled conditions to avoid interferences of uncontrollable field variables such as weather conditions. Two ultra-high-speed cameras captured 3-dimentional droplet movements at 11,700 frames per second under high-power light emitting diode illumination. Droplet behaviors on leaves were analyzed with varying cuticle characteristics, droplet sizes, velocities, additive concentrations, and impact angles. Tests were repeated with the droplet generator traveling up to 10 km/h to simulate nozzle movements in the field spray applications. Statistical correlations between droplet deposition, distribution, and coverage were established to identify critical factors for efficient and effective spray applications.
Accomplishments
1. Air-pinch valve to prevent precision sprayers from chemical clogging or sticking. Electric pulse width modulation solenoid valves are a critical component for variable rate sprayers to provide precision pesticide applications. However, these valves pose a potential problem that they can be clogged or stuck by adhesive additives or physically incompatible powder pesticides if sprayers are not rinsed thoroughly after applications. ARS engineers at Wooster Ohio investigated and identified an air-pinch valve that isolated the valve actuation components from contacting chemicals, thus preventing the valve from the potential chemical clogging/sticking problem. The valve was designed to separate the chemicals from the valve activation components while still modulating nozzle flow rates precisely. The air-pinch valve will be integrated into precision sprayers to improve reliability and application accuracy, which will help specialty crop growers achieve efficient and effective crop protection with reduced pesticide waste and safeguarded environment.
2. Improved targeted delivery of pesticide sprays using air-assisted technology. Delivering pesticides to intended crops is critical for protecting the crops from pests and diseases. In these applications, spray droplets must overcome gravity and dense canopies to reach the intended targets. Conventional mechanical fans on orchard sprayers usually generate excessive airflows to carry spray droplets, causing severe spray drift risks. No standard guideline exists for the optimal airflow rate to be used. ARS engineers at Wooster, Ohio, evaluated spray applications with electric fans in an apple orchard with airflow for the assistance ranging from 0 to 2513 m³/h. They found that moderate airflow—between 745 and 1300 m³/h—provided adequate spray delivery to target trees while minimizing drift. This insight not only enhances application precision but also lays the foundation for developing best practices that could benefit growers by reducing pesticide waste and environmental impact.
3. Intelligent sprayer technology reduced pesticide use by 58% under southeastern apple orchard conditions. Specialty crop growers in southeastern United States need application guidelines for the commercially available intelligent spray technology developed by ARS engineers at Wooster Ohio. In collaboration with researchers at University of Tennessee, spray characteristics and pest control efficacy of an intelligent sprayer were evaluated and compared with the conventional, constant-rate sprayer in a commercial apple orchard in Tennessee in two growing seasons. Apples were scouted weekly and biweekly for diseases and two arthropods. The intelligent sprayer reduced the pesticide volume by 58% while maintaining pesticide coverage at or above the overspray threshold on the plants. Also, leaf spot severity, fruit rot severity, and disease index for fruit were not affected by either the intelligent or conventional application mode. In addition, the intelligent sprayer reduced non-target ground losses by 41%, and saved annual insecticide and fungicide spendings by $114 per acre. Thus, this research provided scientific evidence and guidelines for specialty crop growers in the southeastern states to properly adopt the ARS-developed intelligent spray technology to produce high quality fruits for consumers with reduced pesticide use by more than 50% and safeguard the environment.
Review Publications
Castilho Theodoro, J., Ozkan, E., Zhu, H., Jeon, H., Campos, J., Womac, A. 2025. Wind tunnel evaluation of spray nozzle and droplet size effects on spray penetration inside soybean plants. Journal of the ASABE. 68(1): 71-79. https://doi.org/10.13031/ja.16174.
Jeon, H., Zhu, H. 2024. Development of an electric variable air assist system for apple orchard sprayers. Journal of the ASABE. 67(4):853-864. https://doi.org/10.13031/ja.15853.
Kang, C., He, L., Zhu, H. 2024. Assessment of spray patterns and efficiency of an unmanned sprayer used in planar growing systems. Precision Agriculture. 25: 2271–2291. https://doi.org/10.1007/s11119-024-10166-5.
Sahni, R., Schrader, M.J., Rathnayake, A., Khot, L., Hoheisel, G., Zhu, H. 2024. Evaluation of suitable base spray rate estimation methods for precision chemical applications in vineyards with different training systems. American Journal of Enology and Viticulture. 75(1). Article 0750009. https://doi.org/10.5344/ajev.2024.22064.
Campos, J., Zhu, H., Salcedo, R., Jeon, H., Ozkan, E., Gil, E. 2025. Droplet size distributions from PWM-controlled hollow-cone nozzles operated at high modulation frequencies and pressures. Journal of the ASABE. 68(1):51-60. https://doi.org/10.13031/ja.16094.