Location: Application Technology Research2020 Annual Report
Objective 1: Establish comprehensive ground-based strategies to increase foliar retention of pesticide spray for traditional and specialty crops produced in greenhouses and the field. Sub-objective 1.1: Determine the influence of spray parameters including droplet size, formulation physical properties, ambient air conditions, and plant surface morphology on the droplet behavior, evaporation, absorption, and residual pattern on plant surfaces. Sub-objective 1.2: Determine the influence of droplet size and velocity, travel speed, spray formulation physical properties, crop characteristics, leaf surface morphology, and leaf surface orientation on spray droplet dynamic impact, retention, rebound and coverage. Objective 2: Develop intelligent-decision spraying systems to increase spray application efficiency and reduce off-target losses. Sub-objective 2.1: Develop advanced sensor-based intelligent decision systems that can be adapted for different types of sprayers. Sub-objective 2.2: Investigate spray deposition uniformity, off-target losses and pesticide savings with intelligent-decision controlled sprayers. Sub-objective 2.3: Develop drift reduction technologies (DRT) with intelligent decision systems to aid in reducing off-target losses and enabling development of sustainable production programs. Objective 3: Develop ground-based methods for improving delivery of weed management materials to nursery containerized production systems. Sub-objective 3.1: Optimize application factors such as droplet size, spray volume and irrigation volume to improve delivery efficiency of herbicides through a nursery crop canopy to the substrate surface. Sub-objective 3.2: Determine the influence of delivery and plant parameters such as air-assistance, travel speed, irrigation volume, and canopy structure on deposition of granular materials on container substrates. Objective 4: Develop alternative delivery methods for agrochemicals and bioproducts. Sub-objective 4.1: Develop mechanical delivery devices to apply entomopathogenic nematodes. Sub-objective 4.2: Develop methods and strategies for efficiently applying pheromones.
This project envisions that research on intelligent spray technologies, efficient applications of bio-products as alternative pesticides, and coordinated strategies can enhance pesticide application efficiency for efficacious and affordable control of insects, diseases and weeds. The research will focus on delivery systems in conjunction with spray droplet transport, fate of spray droplets upon target impact, epidemiology of pests and pathogens, pesticide formulation, and microclimatic conditions. Selective approaches to achieve the objectives will be to: (1) establish comprehensive ground-based strategies to increase pesticide retention on specialty and traditional crops in greenhouse and field environments; determine the influence of spray parameters such as droplet size, formulation physical properties, ambient air conditions, and plant surface morphology on the droplet impaction, rebound, retention, spread, evaporation, absorption, and residual pattern on plant surfaces under the conditions that individual parameters can be controlled separately; (2) innovate advanced intelligent-decision spraying systems to increase spray application efficiency; investigate spray deposition uniformity, spray drift, offtarget losses and pesticide savings for ornamental nurseries, orchards and other specialty crops with intelligent-decision controlled sprayers; develop drift reduction technologies with intelligent decision systems to aid in enabling development of sustainable production programs; (3) develop methodologies to improve herbicide applications for containerized nursery production systems; optimize application factors such as droplet size, spray volume and irrigation volume to improve delivery efficiency of herbicides through a nursery crop canopy to the substrate surface; determine the influence of delivery and plant parameters such as air-assistance, travel speed, irrigation volume, and canopy structure on deposition of granular herbicides on container substrates; (4) develop mechanical delivery devices to apply new agrochemicals and bio-products for pest control; discover innovative techniques for accurate delivery of entomopathogenic nematode infected insect larvae to effectively control soil pests; develop methods and strategies for efficiently applying pheromones by designing new dispensers with controlled evaporation rates.
This report summarizes progress for the project which began October 23, 2018 and terminated January 31, 2020. It is a bridging project for the previous project 5082-21620-009-00D “Improved Pest Control Application Technologies for Sustainable Crop Protection” and the new project 5082-21620-001-00D “Coordinated Precision Application Technologies for Sustainable Pest Management and Crop Protection”. A universal intelligent spray control system was developed as a retrofit kit mounted on different types of conventional air-assisted sprayers and transferred to a commercial partner for further development. An experimental automatic premixing in-line injection system was improved as a retrofit unit for variable-rate orchard sprayers to eliminate tank mixture leftovers. The primary components of the system consisted of a chemical metering pump, a water pump, a two-stage static mixer, a premixing tank, a buffer tank, an electric motor operated shut-off valve, a chemical container assembly, electronic control boards, a graphic user interface, and an embedded computer with a touch screen unit. Liquid level sensors were mounted in all tanks and the chemical container to control the fluid discharge process and prevent overflows. The graphical user interface with visual operation functions was designed for operators to communicate with the system and monitor the system operation status. During spray applications, the system performed with loops in dispensing, mixing, and transferring desired amounts of water and chemical concentrates automatically to maintain spray mixture with a constant concentration for variable-rate nozzles to discharge. The system was rinsed automatically when the spray application task was completed. In addition, the user interface was designed for operators to manage the system operation and view the operation status shown on the touch screen. Chemical concentration accuracy and spray mixture uniformity produced from the premixing system was investigated with various viscosities of simulated pesticides and duty cycles of pulse-width-modulated nozzles at different positions on the sprayer. Field tests in a two-year old apple orchard were conducted to evaluate spray deposition quality of three pulse width modulation (PWM) systems attached to an air-blast orchard sprayer: 1) a manually-PWM-controlled spray system producing a constant-rate application (Manual-PWM), 2) a laser-guided PWM-controlled intelligent spray system producing a variable-rate application (Laser-PWM), and 3) the same laser-guided spray system with disabled PWM control producing a constant-rate application (Disabled-PWM). Spray deposition distributions on multiple-row trees were quantitatively evaluated for the three spray systems. Water droplet impact and adhesion on leaves were investigated with various levels of leaf surface roughness or leaf wettability. An optical profiler and three industry standard roughness parameters: height, skewness, and kurtosis, were used to quantify the surface roughness for different leaf types ranging in wettability from very easy to very difficult. These parameters were then compared and related to the adhesion and spreading of impacting water droplets at different surfactant concentrations and impact velocities. Droplet size and impact velocity were controlled by a streamed mono-sized droplet generator mounted on a horizontal motion track. Droplet motion and impacts were recorded with three ultrahigh-speed video cameras and analyzed using 3-dimensional motion analysis software. A 3D ultrahigh-speed video surveillance system was used to monitor the effects of hairy trichomes on the adhesion, spread, and rebound of impacting water droplets on plant leaves. The effects were determined by comparing the droplet impact behavior for different surfactant concentrations on maize, soy, and squash leaves when their trichomes were present and then removed. Trichomes were removed mechanically with an electric razor. Potential changes to the surface characteristics of the leaves due to trichome removal were monitored by measuring the wax load, surface roughness, wettability and scanning electron microscopy micrographs before and after trichome removal. An electronic nose (E-nose) system equipped with a set of sensitive sensor array was investigated for a fast diagnosis of aphid infestation at early stages of tomato plants. The system was preliminarily tested for its capability to distinguish volatile organic compounds released from heathy plants and from aphids-stressed tomato plants at the beginning of infestation under greenhouse conditions. A gas chromatography–mass spectrometry instrument was used to verify the analyses of volatile compounds identified with the E-nose. Preliminary results illustrated that tomato plants infested by aphids released new volatile compounds for combating aphid attacks. These new compounds could be used as the biomarkers for the E-nose to identify infested plants. However, further investigations are needed to quantify the new volatile compounds released from different varieties under different growth conditions to validate the E-nose sensitivity and reliability. Droplet size distributions of rotary micro sprinkler nozzles with five different orifice diameters were investigated for pesticide applications to minimize spray drift in orchard systems. A particle-droplet laser image analysis system was used to measure droplet spectrum at two pressures and two radial distances from the nozzle center. Nozzle orifice sizes, rotation speeds and flow rates were also measured. Droplet sizes varied with the nozzle tip orifice size, operating pressure and sampling location. Spiral-shaped spray patterns formed due to the spinning discharge port, within which droplet densities varied with location, nozzle diameter and operating pressure. A multiple variable regression model was developed to predict volume median diameters of droplets discharged from the sprinkler spinning nozzles. An experimental laser-guided spray system was developed and implemented into a water-boom system in a commercial greenhouse for discharging variable-rate sprays to save pesticides, water, and nutrients. Accuracy of an inexpensive indoor-use radial laser sensor and a sophisticated algorithm were evaluated in detecting surface edge profiles of plants before their integration into the intelligent spray system development for greenhouse applications. Evaluations included four objects of different regular geometrical shapes and surface textures, and two artificial plants of different canopy structures. Three-dimensional images for the object surfaces were reconstructed with the data acquired from the laser sensor at four different detection heights above each object, five sensor travel speeds, and 15 horizontal distances to the sensor. Edge profiles of the six objects detected with the laser sensor were compared with images taken with a digital camera. The edge similarity score was used to define the differences in surface edge profiles between images obtained from the laser sensor and the camera. Consequentially, a preliminary intelligent spray system was designed for real-time control of individual nozzle outputs for greenhouse applications. The system mainly consisted of the laser scanning sensor, 12 individual variable-rate nozzles, an embedded computer, a spray control unit, and a 3.6 m long mobile spray boom. Each nozzle was coupled with a pulse width modulated solenoid valve to discharge variable rates based on object presence and plant canopy structures. Laboratory tests were conducted to evaluate the intelligent spray control system accuracy in terms of the spray delay time, nozzle activation, and spray volume using the four different regular-shaped objects and two artificial plants. Other experimental variables included three laser detection heights from 0.5 to 1.0 m and five constant travel speeds from 1.6 to 4.8 km/h. A high-speed video camera was used to determine delay time and nozzle activation in discharging sprays on target objects.
1. Universal intelligent spray control system as a retrofit for conventional sprayers was commercialized. The intelligent spray technology developed by ARS researchers in Wooster, Ohio, effectively controls pest insects and diseases with significant reductions in pesticide waste to the environment; however, to ensure growers to use this technology economically, it must be adaptable to conventional sprayers. To address this challenge, a universal intelligent spray system was developed by ARS researchers in Wooster, Ohio, as a retrofit unit for conventional orchard sprayers to perform intelligent functions in controlling spray outputs to match plant presence and structures in real time. The retrofit unit was tested in 15 commercial nurseries, fruit and nut orchards, and vineyards in Ohio, Oregon, Tennessee, South Carolina, California, Texas and Australia. Field tests demonstrate this new technology can provide equivalent pest and disease control as conventional spray systems while it can reduce spray drift by up to 87%, ground loss by 90%, and reduce pesticide use between 30 to 85% thereby reducing annual chemical savings between $56 and $812 per acre depending on crop types. This cost savings does not include labor cost and fuel savings. The technology was transferred to a commercial partner and a commercial product was released into the market. Citrus, apple, grape, nursery and pecan growers in the United States and other countries started to upgrade their sprayers with the commercial product. The use of a new laser-guided intelligent spraying system is beneficial to the ecosystems and saves growers’ money by reducing the amount of pesticides used. Therefore, it offers a sustainable and environmentally responsible approach to protecting crops.
2. Advancing peach production with intelligent sprayer system. Conventional air-blast sprayers have been widely used for control of pests and diseases in peach orchards and other specialty crop production. However, the efficiency of these sprayers in pesticide usage is very low and a large portion of the sprayed materials goes into the environment. An intelligent spray control system was recently developed by ARS researchers in Wooster, Ohio, as a retrofit for the air-blast sprayers to revolutionize the modern pesticide application practices. With the retrofit, the sprayers can precisely discharge the amount of chemicals on targets and minimize off target sprays by considering the tree presence, canopy structure, tree row space and travel speed. A standard air-blast sprayer retrofitted with the intelligent spray control system was investigated and compared with the conventional constant-rate application in peach orchards in South Carolina. The comparisons included pest and brown rot disease control, spray volume used per acre, and spray coverage and drift. Field tests demonstrated the intelligent spray system ensured pest and disease control efficacy in peach orchards, while significantly reducing spray drift and the amount of spray materials used. The reduction in spray volume up to 71% was most significant when used on younger trees and on trees early in the season before tree canopy closed. These scientific evidences assured the sustainable benefits of using the new intelligent spray technology to save growers’ money and protect the environment in commercial peach production.
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Lin, J., Zhu, H., Ling, P. 2019. Amendment of herbicide spray solutions with adjuvants to modify droplet spreading and fading characteristics on weeds. Applied Engineering in Agriculture. 35(5):713-721. https://doi.org/10.13031/aea.13339.
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Cui, S., Inocente, E.A., Acosta, N., Keener, H.M., Zhu, H., Ling, P.P. 2019. Development of fast E-nose system for early-stage diagnosis of aphid-stressed tomato plants. Sensors. 19(16):3480. https://doi.org/10.3390/s19163480.