ADVANCEMENT OF PESTICIDE SPRAY APPLICATIONS IN SPECIALTY CROP PRODUCTION WITH INTELLIGENT-DECISION TECHNOLOGIES

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: OTHER GRANTS
• Reporting Frequency: Annual
• Accession No.: 1007599
• Grant No.: 2015-51181-24253
• Cumulative Award Amt.: $3,672,482.00
• Proposal No.: 2015-09239
• Project Start Date: Sep 1, 2015
• Project End Date: Aug 31, 2020
• Grant Year: 2015
• Program Code: [SCRI]- Specialty Crop Research Initiative

Recipient Organization
AGRICULTURAL RESEARCH SERVICE
1815 N University
Peoria,IL 61604

Performing Department
(N/A)

Non Technical Summary
Despite growing public interest in organic production, conventionally produced specialty crops represent the majority of production acreage and are a vital source of edible and environmental horticulture crops. In order to assure high quality and abundant products, pesticides will continue to be applied for the majority of acreage in specialty crop production. However, current pesticide spray technologies for specialty crops frequently result in over-application and excessive off-target losses and spray drift, primarily due to large variations in canopy sizes and densities, plant spacing, and constant pesticide delivery rate offered by conventional sprayers. Spray applicators must make decisions within a very narrow time window on how much pesticide and spray volume should be needed to control a specific pest or disease. Accordingly, growers often use a "best guess" practice that usually applies excessive amounts of pesticides for pest control. Often young trees and mature trees are sprayed with the same volume and nozzle settings. In some cases, incorrect chemicals and improper application schedules are chosen due to a lack of accurate information on pest populations and wind conditions for a specific geographical area. Such imprecise application of pesticides is costly to producers and adds an unnecessary pesticide risk to the environment (air, soil, and surface and ground water), wildlife, beneficial insects (for example, pollinators), and sensitive ecosystems.Many specialty crops currently operate in fields ranging from a few acres to several hundred acres close to residential districts and urban or suburban areas as well as water resources. In an environment constrained by residential proximity, an ideal spray management program for pests and diseases would have improved delivery systems with efficient monitoring and the accurate timing of pesticide applications that produce minimum spray drift and off-target loss of pesticide on the ground and in the air. Models to predict pest pressures and spray drift potentials in coordination with local weather conditions will be an effective approach to advise application schedules to further minimize drift potentials for the improved spray systems.Furthermore, pesticide sprays from conventional sprayers indiscriminately kill both pests and insects that are beneficial biological control agents. Excessive and/or repeated pesticide use that eradicates all insects can leave behind a vacuum for any insect pests to recolonize the host crop without competition and then can cause the unintended consequence of exacerbating plant pest and disease problems. Thus, unnecessary overuse of pesticides not only results in economic loss, but also is a potential source of environmental contamination and ecosystem damage, such as recent pollinator crisis. Future pesticide application systems should have the flexibility to spray specific positions on the crops to control particular pests. For example, to control ambrosia beetles, pesticides are only needed on tree trunks. In this way, pollinators and other beneficial insects can still conduct activities in foliage and flowering areas. However, conventional sprayers for specialty crop applications do not have these flexibilities.Therefore, innovative spray application technologies are needed to assure the quality of specialty crops, ensure food safety and security, and promote growers' economic competitiveness. However, adoption of new spray technologies is complicated by trade-offs among competing economic and environmental interests of growers, sprayer manufacturers, chemical companies, and regulating agencies. It will be difficult for growers to dispose their existing sprayers that are still functional when new spray technologies are available. It will be also difficult for sprayer manufacturers to obsolete their existing sprayer designs. Adaptation of the universal new spray-decision control system is an appropriate approach for growers and sprayer manufacturers to improve their existing sprayer application efficiencies.This research envisions that intelligent spray technologies integrated with coordinated strategies can substantially improve pesticide application efficiency for efficacious and affordable control of insects and diseases. The objective of this research is to develop a universal intelligent spray-decision control system that can be easily retrofitted on conventional or new sprayers for pesticide spray applications in field and greenhouse specialty crop productions. The retrofit will enable sprayers to match system operating parameters more effortlessly to crop characteristics, insect/disease pressures and microclimatic conditions in real time, and allow growers to use their existing sprayers rather than rely exclusively on the purchase of new sprayers to provide optimal crop protection. The intelligent spray control system will be developed with integrations of a laser-sensor guided controller to match spray outputs to the unique architecture of each crop species, an expert subsystem including insect and disease as well as spray drift potential prediction models to manage application schedules, and a premixing in-line injection module to avoid leftover tank mixtures. With the intelligent spray decision control system, crop structures, pest pressures and local climatic conditions will govern the amount, type and frequency of spray applications, thus minimizing unnecessary pesticide waste. To validate the intelligent spray control system functions and introduce this new technology into integrated pest management (IPM) programs, growers' standard air-assisted sprayers with and without the intelligent control function will be compared for spray delivery accuracy inside canopies, chemical usage, spray drift and off-target losses, pest control efficacy and application costs in the commercial field and greenhouse specialty crops at various growth stages under different environmental conditions. At completion, the proposed project will enhance the prospects of existing sprayers to be more efficient, effective, reliable, and operator-friendly. These spraying systems will deliver pest control agents in an intelligent, economical, accurate, timely, and environmentally sustainable manner with enhanced safety for spray operators and farm workers.

Animal Health Component

40%

Research Effort Categories

Basic

20%

Applied

40%

Developmental

40%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
402	5310	2020	60%
133	0199	2020	15%
141	0410	2080	15%
216	5220	2020	10%

Knowledge Area
133 - Pollution Prevention and Mitigation; 216 - Integrated Pest Management Systems; 141 - Air Resource Protection and Management; 402 - Engineering Systems and Equipment;

Subject Of Investigation
5310 - Machinery and equipment; 0199 - Soil and land, general; 0410 - Air; 5220 - Pesticides;

Field Of Science
2020 - Engineering; 2080 - Mathematics and computer sciences;

Keywords

automation

environmental protection

food safety

pesticide

specialty crop

spray technology

Goals / Objectives
The primary goal of this research is to develop and implement an advanced and affordable universal intelligent spray-decision control system that is robust, reliable and user-friendly. The system will be retrofitted onto conventional constant-rate or new variable-rate sprayers to minimize pesticide input while maintaining efficacious control of insects and diseases. Accomplishing the goal will permit sprayers to automatically match spray operating parameters to crop characteristics, insect/disease pressures and microclimatic conditions during pesticide spray applications in field and greenhouse specialty crop productions. It will also allow growers to use their existing sprayers rather than relying exclusively on the purchases of new sprayers to accurately and effectively deliver pest control agents to target areas. The new system will provide optimal crop protection in a sustainable manner, reduce pesticide consumption and waste, safeguard the environment and improve operator safety. Specific objectives to achieve the primary goal are to: (1) develop and test a universal intelligent spray-decision control system that can be retrofitted to existing sprayers to increase spray application efficiency and reduce off-target losses in nurseries, orchards, vineyards, small fruit plantings, tree nut orchards and other specialty crop operations; (2) develop and test an automatic greenhouse spray system with integration of the universal intelligent spray-decision control system to apply chemical and biological pesticides; and (3) introduce the new spray technology into integrated pest management (IPM) programs for specialty crop productions. To achieve these objectives, the following three major modules will be developed and tested in commercial nurseries, orchards, greenhouses, vineyards, small fruit plantings, nut orchards and other specialty crop farming operations in different parts of the country under different environmental conditions: (1) an automatic variable-rate nozzle flow control unit comprised of a high-speed laser scanning sensor along with an embedded computer and a touch screen to characterize crop presence, shape, canopy density, and canopy volume to control spray output of each nozzle, and a premixing in-line injection unit to proportionately dispense chemicals on demand and eliminate disposal of leftover tank mixtures; (2) an expert subsystem to make application decisions based on climatic pest pressure determination models for both greenhouse and field specialty crops and spray drift potential models for field specialty crops; and (3) integration of the new spray systems into best pest management programs. The maximum estimated cost of the universal intelligent spray control system for a conventional sprayer is $9,500; however, the initial cost would be offset by more than a 50% reduction in the amount of pesticide use because of increased application efficiency and reduced human decision errors, resulting in a major savings in material and labor costs and environmental risk. Growers of nurseries, orchards, vineyards, small fruit plantings, tree nuts, greenhouses and other specialty crops will be the primary beneficiaries of the outcomes from this research. Pesticide applicators and sprayer manufacturers will have the access to safer and more reliable and user-friendly automatic controllers for their sprayers to deliver pesticides more economically, accurately, and timely with minimum human involvement before, during and after applications.

Project Methods
A universal intelligent spray-decision control system will be developed with integration of three coordinated subsystems: a nozzle flow control subsystem to control individual nozzle outputs to match crop sectional structures and foliage characteristics; an expert subsystem to assist the decision making process of choosing proper chemicals and application schedules as determined by local ambient microclimatic conditions and applicable pest models; and a premixing in-line injection sub-system to eliminate sprayer tank leftover disposal problems. These subsystems can be used independently or disassembled from the spray systems depending on the specific crop production circumstances.The nozzle flow control subsystem is an integration of a high-speed laser scanning sensor, an automatic flow rate control unit, an embedded computer, and a touch screen control. The laser scanning sensor detects plant presence and measures plant size, shape and foliage density on both sides of sprayers. The automatic flow rate control unit processes sensor signals and manipulates individual nozzles with different spray patterns. Microprocessor-controlled circuits will be designed to execute commands from the computer program, and a signal generation-amplification unit will be designed to manipulate flow rates of individual nozzles. With these circuits, nozzles can be controlled independently to produce variable-rate outputs based on the presence, height, width and foliage density of target plants and the sprayer travel speed.The premixing inline injection module will also be a microprocessor controlled unit. Unlike conventional direct inline injection systems that inject chemical concentrates into the delivery lines, this module first dispenses specific amounts of water and chemical concentrates into an injection chamber and then agitates the mixture in a premixing tank. The mixture is then transferred into a buffer tank for the spray pump to discharge. This process is repeated until the buffer tank nears empty. The concentration of chemicals in the premixing container will be synchronously controlled by the automatic flow rate control unit and the expert system. This module will avoid the lag time, inconsistent spray mixture concentrations and inaccurate metering of chemical concentrates at low flow rates associated with conventional direct inline injection systems.The expert subsystem which includes insect, disease and spray drift prediction models will be computer programs installed in the embedded computer and will be linked to local weather stations to determine spray application rates, required chemicals to control insect and disease pests and spray application schedules. The insect and disease prediction models will use existing models nationally based on the historic insect and disease pressure, leaf wetness and degree days, augmented by local pest pressure reports. The models will be used to help applicators choose the most efficacious chemicals and concentrations. Temperature-based insect phenology models will be used as part of the decision support system to predict spray timing. The functions of the models will be continuously improved as more scientific information is available for more pests, and will be accommodated with future new sensors that can detect insect populations and disease pressures. Spray drift models will be developed to predict movements of droplets discharged from sprayers equipped with the intelligent spray control system under turbulent flow conditions. Predictions include droplet drift distances in the production field, the subsequent dispersion, short- and long-range transport, and evaporation. Wind speed and direction, ambient air temperature and relative humidity, droplet size distribution, air velocity and airflow pattern discharged from sprayers will be the variables of the drift models.The automatic greenhouse spray system will be designed with retrofit of the universal intelligent spray-decision system attached to existing watering booms. Due to the unique greenhouse environments, an inexpensive, in-door use laser scanning sensor will be used and installed above the watering boom to detect the presence and canopy structure of plants to be applied with chemical or bio pesticides. Computer programs will be modified for the universal intelligent spray control system while the control circuits will remain unchanged. An IPM approach will be developed to control the intelligent sprayer operation. The spray operation parameters will be adjusted not only for plant canopy structure, size and presence, but also assessed for plant growth stage, and disease and insect pressures. An automated high resolution environmental monitoring system, for disease pressure determination, and a sampling device for insect scouting will be developed and integrated into the automatic greenhouse spray system for determination of disease and insect pressures. To verify the spray deposition accuracy of boom sprayers equipped with the universal intelligent spray control system in greenhouse, tests with randomized complete block designs consisting of five plot replications with five different flowering plants will be conducted to compare spray deposition uniformity inside canopies, chemical usage and off-target losses for the plants at different growth stages. For pest control efficacy tests, the same varieties of plants and same plot designs used for the spray deposition tests will also be used.To verify the spray delivery accuracy of different growers' standard sprayers equipped with the universal intelligent spray control system, field tests will be conducted with randomized complete block designs consisting of field plot replications for the sprayers with intelligent decision control systems and the same sprayers without intelligent decision functions. These tests will compare spray deposition uniformity inside canopies, chemical usage and off-target losses for the plants at different growth stages. Crops in commercial ornamental nurseries, apple orchards, vineyards, peach orchards, blueberry farms and pecan farms in different states will be selected for the field experiments. Spray deposits at different locations inside and outside canopies, on the ground and in the air will be measured.Biological efficacy tests for the sprayers equipped with and without the intelligent spray-decision control function will be conducted and expert model prediction accuracy will be evaluated in commercial specialty crop fields in different states. Comparisons include insect and disease control efficacy, pesticide quantity used, and cost savings in nurseries, apple orchards, peach orchards, vineyard, blueberries, pecan trees, and hazelnuts. Statistical analysis with ANOVA will be used to document the efficacy difference between the sprayers with and without the intelligent spray control system.The economic research will establish cost categories related to the use of sprayers retrofitted with the intelligent control system through guided key stakeholder interviews and expert listening sessions related to the use of existing technologies, and assess the potential environmental and social capital gains achieved by reduced pesticide usage and increased application control.

Progress 09/01/15 to 08/31/20

Outputs
Target Audience:Target audiences are growers, farm managers, and pesticide applicators (including Hispanic and African American growers and workers) of specialty crops (nursery, apple, peach, pecan, citrus, grape, winery, blueberry, raspberry, cranberry, hazelnuts, hops and greenhouse crops), extension specialists and educators, county agents, viticulturists, researchers, undergraduate and graduate students, robotics and artificial intelligence enthusiasts, agricultural industry consultants, commercial diagnosticians, general public, sprayer manufacturers, chemical companies, greenhouse equipment suppliers, national and state legislators, and environmental protection agency regulators.. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Professional development trainings and services in using the intelligent spray technology were provided for growers, farm managers, spray applicators and engineers through numerous workshops and demonstrations during the intelligent spray technology validation tests in commercial production fields. These activities were held in Hale and Hines Nursery, Pleasant Cove Nursey, Wooden's Apple House and The Apple Barn in Tennessee; Hans Nelson & Sons Nurseries, J. Frank Schmidt & Son Co., and Oregon State University Research Farm in Oregon; Willoway Nurseries, Herman Losely & Son Nurseries, Klyn Nurseries, Klinshirn Winery, Moreland Fruit Farm, Bauman Orchards, Blueberry Patch in Ohio, OARDC Horticulture Field in Ohio, Clemson University Musser Fruit Research Farm and Titan Farm in South Carolina; Five R Enterprises pecan farm in Texas; Washington State University Fruit Research Farm; Iowa State University Fruit Farm; University of Queensland in Australia; and Smart Guided Systems in Indiana. Growers, farm managers and spray applicators as well as local extension educators gained first-hand experience in advancing conventional sprayers to the intelligent spray technology based on the sprayer types and functions. The presentations helped many participants maintain their accreditation and helped them think about how to spray their plants for better pest management with the intelligent spray technology. Numerous high school students, undergraduate students, graduate students and post-doctoral fellows at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University and USDA-ARS were trained in research methodologies in development of intelligent spray technologies through presentations, demonstrations and laboratory tours. They were also trained on the development of the techno-economic analysis models, collecting data from different sources and conducting the analyses. These students and post-doctoral fellows learned about the pesticide spraying technologies applicable to different nursery, orchard and vineyard types, pesticide application procedure and schedule, and resources required for spraying pesticides in the orchards to achieve sustainable crop production and environmental stewardship. They also gained an appreciation for the various sensors for advanced agricultural equipment as well as an understanding of conducting field research in collaborations with growers and other cooperators. How have the results been disseminated to communities of interest?The research results on the intelligent spray technology reached target audiences through different outreach efforts including oral and poster presentations, national and international conferences, extension workshops and field days, on-farm demonstrations, pesticide applicator training and licensing programs, trade shows, meetings and consultations, peer reviewed journal articles, and press articles in trade magazines and newsletters, websites, laboratory visits, and regional, national and international conferences. They outreach activities also included on-farm tests of intelligent spray prototype systems in nurseries, apple orchards, peach orchards, pecan orchards, vineyards, and small-fruit farms in Ohio, Oregon, Tennessee, South Carolina, Washington, New York, Michigan, Indiana, Pennsylvania, Iowa, California, Florida and Texas. In addition, results from economic analyses were disseminated to orchard and nursery owners and growers during field visits and personal communication. In his keynote speech for the 2019 Impact Washington Summit, USDA Secretary Sonny Perdue highlighted the intelligent sprayer work as an example of advanced technology research that is positively affecting agriculture production. 2016: The results of this research were disseminated through CENTS, AmericanHort Cultivate, Tennessee Green Industry Expo, Tennessee Fruit and Vegetable Association Meeting, Farwest Show, etc. 2017: Presentations on new intelligent sprayer technologies were given in Kentucky Fruit & Vegetable Meeting, Southeastern Apple Meeting, North GA Apple Meeting, Pick TN Conference, Tennessee Green Industry Field Day, Turf and Ornamental Field Day, Shade Tree Growers Mtg., Ag Day 2017 in Tennessee, Oregon State Board of Agriculture, Napa Valley Wine Growers, California Lodi Wine Growers, J. Frank Schmidt & Sons staff meetings, 2017 Congressional Specialty Crop Committee Meeting, Cultivate'17 Workshop, 2017 Florida Citrus Show, The Ohio State University Extension Orchard Sprayer Technology Field Day, Wayne Economic Development Council, 2017 ASABE Meeting, 2017 Midwest Green Industry Xperience (MGIX) Show, 2017 Farwest Show, 2017 ASHS Conference, the OPGMA Congress, Ohio Berry and Wine Grape Workshop, and Ohio Berry and Wine Grape Field Night in 2017. A press article on the intelligent spray technology with drift reduction models was published in the Ohio's Country Journal to reach more than 25,000 farmers. 2018: Presentations and field demonstrations on new intelligent sprayer technologies were given at Community Open House in Oregon, Farwest Show and Seminars in Oregon, Oregon State University 150 Celebration, The Promise and the Peril of Artificial Intelligence and Robotics of OSU in Oregon, 21st Ornamental Workshop on Insects and Diseases in North Carolina, Clackamas Basin Tech Advisory Group in Oregon, Willamette Valley Viticulture Tech Group meeting in Oregon, 13th Annual Cranberry Production Workshop in Oregon, Willamette Valley Viticulture Tech Group meeting in Oregon, University of California Nursery & Floriculture Alliance 2018 Pest Management Symposium, Western Disease Conference in Oregon, 77th Annual Pacific Northwest Insect Management Conference in Oregon, OSU Hazelnut IPM Workshop in Oregon, Nut Growers Summer Tour in Oregon, J. Frank Schmidt & Sons staff meetings, AgDay in Tennessee, UT/TSU Western Region Extension Agent In-Service, Southern Region Small Fruits Consortium In-service Training for Extension Agents from 6 states, Tennessee Fruit and Vegetable Association Annual Meeting, Tennessee Farm Winegrowers Alliance Annual Meeting, University of Tennessee Plant Sciences Course PS115, Tennessee Green Industry Day, National Association of County Ag Agents in Tennessee, Turf and Ornamental Field Day in Tennessee, AmericanHort's Production Technology Conference, Cultivate'18 in Ohio, IPPS Area Meeting & Tour in Ohio, 2018 Ohio Grape and Wine Conference in Ohio, the Ohio Blueberry, Bramble and Wine Grape Field Night, 2018 Midwest Green Industry Xperience (MGIX) Show in Ohio, Ohio Recertification Conferences for Commercial Pesticide Applicators, Ohio Annual Fruit and Vegetable Growers Conference, Annual Hops Growers Conference, In-service training for Extension Educators, 2018 ASABE Meeting, ASHS Conference, the International Conference of Plant Pathology, Plant Health in a Global Economy, Pesticide Application Technology and Modeling Workshop, EuroAgEng Conference in Netherlands, and Cortona in Italy. 2019: Presentations and field demonstrations on new intelligent sprayer technologies were given at 2019 OPGMA Congress, Columbus, OH; Ohio Grape and Wine Conference, Dublin, OH; Blueberry and Grape Grower Cooperators, Avon Lake and Mansfield, OH; Ohio Blueberry, Bramble and Grape Field Night, Piketon, OH; Spray Drift Seminar, Dayton, OH; Ohio Farm Bureau "ExploreAg", Wooster, OH; Cultivate'19, Columbus, OH; 2019 Farm Science Review, London, OH; The Ohio State University Extension Educators, Columbus, OH; Greenhouse Management Workshop; Wooster, OH; Guest lecture at Agricultural Technical Institute/The Ohio State University, Wooster, OH; NCERA-101 USDA Regional Committee meeting, Montreal, ON, Canada; NASA Utilization and Life Science Workshop, Kennedy Space Center, FL; CPAAS Ag Tech Day, Prosser, WA; Intelligent Sprayer Add-on Kit for Air-blast Sprayers Field Demo, Groveland, FL; Penn State Extension "Orchard Pest Management and Intelligent Spraying Technologies" Workshop, Biglerville, PA; Green Industry Express, Chattanooga, TN; Southeast Apple Growers Meeting, Asheville, NC; Southeast Regional Fruit & Vegetable Conference, Savannah, GA; Pick TN Conference, Franklin, TN; TN Organic Growers Association; TN Fruit & Vegetable Association; TN Farm Winegrowers Alliance; Plateau Fruit School, Crossville, TN; EPP 630 Advanced Integrated Pest and Pathogen Management, Knoxville, TN; UT-TDA Master Producer Oversight meeting, Crossville, TN; HORT 3050 - Viticulture and Enology in the Mediterranean Region, Cortona, Italy; Tennessee Green Industry Day; Tennessee Association of Pesticide Applicators, Gatlinburg, TN; American Society for Horticultural Science Annual Conference, Las Vegas, NV; Hydrangea Production Workshop, Knoxville, TN; Hydrangea Production Workshop, Clarksville, TN; Turf and Ornamental Field Day, Knoxville, TN; FaceBook Live Event, Knoxville, TN; Nutrient Hazelnut growers meeting, Lebanon, OR; Oregon State University Grape Day, Corvallis, OR; Napa Valley Grape Growers, Napa, CA; Shade Tree Growers Meeting, Aurora, OR; Oregon State University Winter Hort. Meeting, Hood River, OR; Oregon Wine Symposium, Portland, OR; Pesticide Recertification Course, Medford, OR; Orchard Pest and Disease Management Conference, Portland, OR; Hermiston Farm Fair, Hermiston, OR; Fall Orchard/Vineyard Pest Management meeting, Roseburg, OR; 21st Ornamental Workshop on Insects and Diseases, Hendersonville, NC; LIVE/OWRI Field Day, NW Wine Studies Center, Chemeketa Community College, West Salem, OR; Spring Vineyard Mechanization Workshop, Medford, OR; Oregon State University 150 Celebration, The Promise and the Peril of Artificial Intelligence and Robotics, Corvallis, OR; Farwest Show, Portland, OR; Intelligent Sprayer Workshop, Boring, OR. Presentations were also given to The University of Manchester, England; Conference on International Developments in Pesticide Application, England; European Technical committee -N8- on Sensors and Electronics; University of Polytechnic at Department of Agricultural and Biological Engineering, Barcelona, Spain; National Institute for Environmental and Agricultural Science and Research at Montpellier, France; two Nozzle manufacturers (Lechler, Albuz), and two sprayer manufacturers (Berthoud, Kuhn), France; Ankara University College of Agriculture, Turkey; and individual researchers specialized in pesticide spray technologies from Spain, Italy and Poland. What do you plan to do during the next reporting period to accomplish the goals? We have accomplished the project goals and will look forward to exploring new opportunities to expand the research goals in the future. The research team will also continuously provide field test findings for this new technology and will support other researchers who have received regional and federal grants to integrate our intelligent spray technology into new IPM programs. The intelligent spray control system has been commercialized by Smart Guided Systems LLC (https://www.smartguided.com/intelligent-sprayer). As a result of this research, growers and sprayer manufacturers will have reliable and affordable new intelligent systems to increase the application efficiency and reduce uncertainty associated with current pesticide delivery systems used in specialty crop production. The newly developed pesticide application technology and strategy from this project have achieved real cost benefits to producers, consumers and the environment, and create safer and healthier conditions for workers.

Impacts
What was accomplished under these goals? A universal intelligent spray control system was developed as a retrofit kit for existing air-assisted sprayers commonly used in specialty crop production. The control system integrated a high-speed laser scanning sensor into an automatic controller to manipulate variable-rate spray outputs of individual nozzles to match plant presence, size, shape and foliage density as well as sprayer travel speed in real time. The system was retrofitted on different types of the air-assisted sprayers owned by growers for field tests. Spray deposition uniformity inside canopies, chemical usage and off-target losses were investigated for the plants at different growth stages in ornamental nurseries, apple orchards, peach orchards and vineyards. Comparative field biological tests were also conducted to evaluate insect and disease control for the sprayers with and without the intelligent-decision control capabilities in commercial ornamental nurseries, apple orchards, peach orchards, pecan orchards, vineyards, and small fruit production in Ohio, Oregon, Tennessee, South Carolina, Texas, California and Washington. Multi-year field tests demonstrated the intelligent spray system was reliable and could reduce pesticide use in a range between 30 and 90%, reduce airborne spray drift between 60 and 90%, and reduce spray loss to the ground between 40 and 80%, resulting in chemical savings in a range of $56 to $812 per acre annually. As a result, Smart Guided Systems LLC. commercialized the intelligent spray system and released it into the market in 2019. The commercial products have been used by growers in the U.S. and other countries with crops including citrus, nursery, pecan, blueberry, peach, almond, apple, and pear with pesticide usage reductions in the range between 30 to 85%. The commercial intelligent spray product received 2020 ASABE Davidson Prize, 2020 ASABE AE50 Award Winners, and 2020 World Ag Expo Top-10 New Product Winners. Growers now can still use their existing sprayers rather than relying on purchasing new intelligent sprayers for sustainable and environmental-friendly crop protection, and sprayer manufacturers do not need to redesign their sprayers to achieve intelligent spray benefits of significant chemical savings and environmental protection. A target-oriented intelligent spray system was designed for real-time control of individual nozzle outputs to precisely apply pesticides, irrigation and nutrients for greenhouse crops. The system was an attachment to the existing water booms commonly used in greenhouses. Spray rates discharged were automatically adjusted according to the plant occurrence and sizes. It mainly consisted of the laser scanning sensor, variable-rate nozzles, an embedded computer, a spray control unit, and a mobile spray boom. Each nozzle was coupled with a pulse width modulated solenoid valve to discharge material at variable rates based on object presence and plant canopy structures. Tests were conducted in laboratories and a commercial greenhouse to validate the accuracy of the intelligent spray control system in terms of the spray delay time, nozzle activation, and spray volume to save pesticides, water, and nutrients. The system was able to carry out asynchronous, precision spray operations based on the mapped 3-D plant canopy information. The new spray system achieved 21 to 89% spray volume reductions compared to the conventional greenhouse spray system. The spray coverage evaluation in a commercial production greenhouse showed the intra-canopy precision control with varied canopy density, resulted in improved spray efficiency while meeting most of the coverage requirements. These efforts improved the feasibility of adopting the precision variable rate spraying technology in commercial production greenhouse environments. An automatic premixing in-line injection system attached on laser-guided intelligent orchard sprayers was developed and tested to eliminate tank mixture leftover problems in both laboratory and fields. This system primarily consisted of a precision fluid metering pump, a premixing tank, a buffer tank, a chemical container assembly, electronic control boards, a graphic user interface, and an embedded computer with a touch screen unit. 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 was performed with loops in dispensing, mixing, and transferring desired amounts of water and chemical concentrates automatically to maintain spray mixtures with a constant concentration for variable-rate nozzles to discharge. The system was rinsed automatically when the spray application task was completed. Test results demonstrated that the chemical concentrates and water could be accurately dispensed into the injection line according to the target concentration inputs and could be well mixed for variable-rate sprayers to discharge to target plants. This new premixing in-line injection system would be a new technology to significantly reduce pesticide waste and improve environmental stewardship for both conventional and new precision variable-rate sprayers. Decision support systems (DSS) complying with weather stations were investigated for managing pesticide spray application schedules to control diseases and insect pests in orchards, nurseries, grapes, blueberry and fruit farms. On-site weather stations were installed to transmit data to the web via a wireless or cellular connection. Approaches were proposed to adaptively implement the orchard DSSs for use in commercial nursery production. Information gathered from the individual insect pest and disease models was combined for future development of a consensus model for spray application recommendations to manage plant diseases and insect pests under complex and uncertain conditions for specialty crop production. An integrated computational fluid dynamics model, SAAS, was developed to improve pesticide application accuracy by predicting target spray deposition and drift potentials for conventional and new intelligent air-assisted sprayers. This software consisted of a database of pesticide spray deposition and drift generated by computational fluid dynamics simulations, embedded data analysis and presentation programs, and user-friendly graphical interfaces. The software was able to estimate the spray mass balances, spray drift through airborne and ground deposition by distance, and pesticide drift setback distances to prevent the potential risk of spray drift. Farmers and extension educators could use the program to evaluate spray drift problems and adjust spray settings to improve the application performance under different weather and crop conditions. The outputs of the SAAS could help spray applicators and farm managers to make tactical decisions on when applications should take place to achieve the high spray efficiency and low risk of spray drift to the environment and ecosystems. A techno-economic analysis (TEA) model was developed to analyze the technical feasibility and economic impacts of pesticide application using conventional and intelligent sprayers for orchard and nursery crop production. The model accounted for increased cost due to sprayer retrofitting, and reduced cost for lower quantities of pesticides, number of tank mixture refills, total spraying time, tractor fuel consumption, and labor hour requirements. Data on pesticide application schedule, pesticide spraying time, and pesticide cost were collected from growers for the model development. For nurseries with area of 10 to 200 acres, cost savings of $245 - $446/acre could be achieved with a payback period of 2-5 years. For apple orchards with 10 to 100 acres, cost savings of $400 - $570/acre was obtained with the retrofitted intelligent sprayers, and payback time was 4 years for 10-acre orchards and 1 year for 100-acre orchards.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: 27. Boatwright, H., and Schnabel, G. 2019. Evaluation of laser-guided air blast sprayer on pest and disease control in peach orchards. Presentation at the annual southeastern fruit workers conference, November 2019, Tifton, Georgia. 28. Warneke, B.W., Pscheidt, J.W., Rosetta, R. and Nackley, L. 2019. Out of the box and through the rows: Intelligent spray system research at Oregon State University. Presentation at APS Pacific Division meeting. 29. Pscheidt, J.W., Warneke, B.W., Rosetta, R. and Nackley, L. 2019. Efficacy of an intelligent sprayer on grape powdery mildew. Presentation at OWRI Grape Day. 30. Warneke, B., Pscheidt, J.W., Rosetta, R., and Nackley, L. 2019. Sensor sprayers for specialty crop production. Oregon State University, University of Idaho, and Washington State University. PNW 727. https://catalog.extension.oregonstate.edu/pnw727 31. Ozkan, E., and Zhu, H. 2019. An update on the intelligent spraying system development for fruit and nursery crop applications. 15th Workshop on Spray Application and Precision Technology in Fruit Growing. SuproFruit 2019. NIAB EMR. United Kingdom. Pp. 35-37. 32. Guler, H., Zhu, H., You, K., Zhang,Z., Abbott, J.P., Cui, S. and Ozkan, E. 2019. Evaluation of spray deposition and off-target loss in apple orchard with an air-blast sprayer retrofitted with intelligent spray control system. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA.
• Type: Journal Articles Status: Published Year Published: 2020 Citation: 26. Abbott, J. R., Ambrose, A.E., and Zhu, H. 2020. Determining effects of leaf surface roughness and adjuvants type and concentration on impacting droplet adhesion. Journal of ASTM International. 40: 128-139. 27. Abbott, J. R., Zhu, H., Ambose, A.E. 2020. Droplet impact and adhesion on leaf surfaces as related to the arithmetic mean roughness length. Transactions of the ASABE. In press. 28. Boatwright, H., and Schnabel, G. 2020. Evaluation of the intelligent sprayer system in peach production. Plant Disease. In press. https://doi.org/10.1094/PDIS-04-20-0696-RE. 29. Chen, L., Wallhead, M., Reding, M., Horst, L., and Zhu, H. 2020. Control of insect pests and diseases in an Ohio fruit farm with laser-guided intelligent sprayer. HortTechnology. 30(2): 168⿿175. https://doi.org/10.21273/HORTTECH04497-19. 30. Chen L., and Zhu, H. 2020. Evaluation of laser-guided intelligent sprayer to control insects and diseases in ornamental nurseries and fruit farms. Journal of ASTM International. 40: 1-10. 31. Fessler, L., Fulcher, A., Lockwood, D., Wright, W. and Zhu, H. Advancing sustainability in tree crop pest management: Refining spray application rate with a laser-guided variable-rate sprayer in apple orchards. HortScience. 55(9):1522-1530. https://doi.org/10.21273/HORTSCI15056-20. 32. Guler, H., Zhang, Z., Zhu, H., Grieshop, M., and Ledebuhr, M. 2020. Spray characteristics of rotary micro sprinkler nozzles used in orchard pesticide delivery. Transactions of the ASABE. In press. 33. Manandhar, A., Zhu, H., Ozkan, E., and Shah, A. 2020. Techno-economic impacts of using a laser-guided variable-rate spraying system to retrofit conventional constant-rate sprayers. Precision Agriculture. 21: 1156⿿1171. https://doi.org/10.1007/s11119-020-09712-8. 34. Salcedo, R., Zhu, H., Zhang, Z., Wei, Z., Chen, L., Ozkan, E., and Falchieri, D. 2020. Foliar deposition and coverage on young apple trees with PWM-controlled spray systems. Computers and Electronics in Agriculture. 178: 105794. https://doi.org/10.1016/j.compag.2020.105794. 35. Warneke, B., Zhu, H., Pscheidt, J. W., Nackley, L. L. 2020. Canopy spray application technology in specialty crops: A slowly evolving landscape. Pest Management Science. In press. http://dx.doi.org/10.1002/ps.6167. 36. Wei, Z., Zhu, H., Zhang, Z., Salcedo, R., and Duan, D. 2020. Droplet size spectrum, activation pressure and flow rate discharged from PWM flat-fan nozzles. Transactions of the ASABE. In press. 37. Zhang, Z., Zhu, H., and Guler, H. 2020. Quantitative analysis and correction of temperature e?ects on fluorescent tracer concentration measurement. Sustainability. 12: 4501. doi:10.3390/su12114501 38. Zhang, Z., and Zhu, H. 2020. Hardware and software design for premixing in-line injection system attached on variable-rate orchard sprayers. Transactions of the ASABE. Transactions of the ASABE. 63(4): 823-831. 39. Zhang, Z., Zhu, H., Salcedo, R., and Wei, Z. 2020. Assessment of premixing in-line injection system attached on variable-rate orchard sprayer. Journal of ASTM International. 40: 11-24. 40. Zhang, Z., Zhu, H., Salcedo, R., and Wei, Z. 2020. Assessment of chemical concentration accuracy and mixture uniformity of premixing in-line injection system. Computers and Electronics in Agriculture. 176: 105670. https://doi.org/10.1016/j.compag.2020.105670. 41. Chen, L., Zhu, H., Horst, L., Wallhead, M., Reding, M., and Fulcher, A. 2020. Management of pest insects and plant diseases in fruit and nursery production with laser-guided variable-rate sprayers. HortScience. In press.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: 1. Li, Y. and Zhu, H. 2016. A versatile strategy to upgrade conventional sprayers with intelligent spray control functions. Abstract ID#: 2452704. 2016 ASABE Annual International Meeting. 2. Fulcher, A., McHugh, J., Collier, R., Zhu, H., Yeary, W., Wright, W., Xiaocun, S., Collier, F., and Lockwood, D.W. 2017. Evaluating variable-rate, laser-guided sprayer performance and powdery mildew control in Cornus florida Cherokee Princess. HortScience 52S. 3. Hong, S.W., Zhao, L., and Zhu, H. 2017. CFD simulations of fate and transport of pesticide droplets discharged from air-assisted sprayers in orchards. The ASABE Annual International Meeting, Spokane, Washington.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: 18. Zhang, Z., Zhu, H., Guler, H., and Shen, Y. Improved premixing in-line injection system for variable-rate orchard sprayers with Arduino platform. Computers and Electronics in Agriculture. 162: 389-396. 2019. 19. You, K., Zhu, H., and Abbott, J. Assessment of fluorescent dye Brilliant Sulfaflavine deposition on stainless steel screens as spray droplet collectors. Transactions of the ASABE. 62(2): 495-503. 2019. 20. Yan, T., Zhu, H., Sun, L., Wang, X., and Ling, P. Investigation of an experimental laser sensor-guided spray control system for greenhouse variable-rate applications. Transactions of the ASABE. 62(4): 899-911. 2019. 21. Lin, J-L., Zhu, H., and Ling, P. Amendment of herbicide spray solutions with adjuvants to modify droplet fading activities on weeds. Applied Engineering in Agriculture. 35(5): 713-721. 2019. 22. Chen, L., H. Zhu, M. Wallhead, and A. Fulcher. 2019. Control of insects and diseases with intelligent variable-rate sprayers in ornamental nurseries. Journal of Environmental Horticulture. 37(3):90-100. https://doi.org/10.24266/0738-2898-37.3.90. 23. Cui, S., Inocente, E. A. A., Acosta, N., Keener, H. M., Zhu, H., and Ling, P. 2019. Development of fast e-nose system for early-stage diagnosis of aphid-stressed tomato plants. Sensors. 19(16): 3480. DOI: 10.3390/s19163480. 24. Abbott, J., and Zhu, H. 2019. 3D optical surface profiler for quantifying leaf surface roughness. Surface Topography: Metrology and Properties. 7(4): 045016. DOI: 10.1088/2051-672X/ab4cc6. 25. Yan, T., Wang, X., Zhu, H., and Ling, P. 2019. Evaluation of object surface edge profiles detected with a 2-D laser scanning sensor. Sensors. 18(11): 1-17.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: 4. Hong, S.W., Zhao, L., and Zhu, H. 2017. A universal spray drift model for estimating spray efficacy and off-target drifts from orchard spray applications. The ASABE Annual International Meeting. 5. Hong, S.W., Zhao, L., and Zhu, H. 2017. CFD simulations of fate and transport of pesticides droplets discharged from air-assisted sprayers in orchards. OARDC (Ohio Agricultural Research and Development Center) Poster Award, Columbus, Ohio. 6. Hong, S.W., Zhao, L., and Zhu, H. 2017. CFD simulations of fate and transport of pesticide droplets discharged from air-assisted sprayers in orchards. OSC (Ohio Supercomputer Center) Statewide Users Group Conference, Columbus, Ohio. 7. Manandhar, A., Shah, A., Zhu, H., and Ozkan, E. 2017. Techno-economic analysis of implementing the intelligent pesticide sprayer for specialty crop production. ASABE Annual International Meeting, Spokane, WA. 8. Zhao, L. 2017. Reducing pesticide spray drift using a universal computational model. Ohio⿿s Country Journal (Online available at http://ocj.com/2017/09/reducing-pesticide-spray-drift-using-a-universal-computational-model/). 9. Zhu, H., Boldt, J., Fulcher, A., Gao, Y., Herms, D. A., Krause, C. R., Ling, P., Lockwood, D., Niu, G., Ozkan, E., Pscheidt, J., Rosetta, R., Schnabel, G., Shah, A., Zhao, L., and Zondag, R.H. 2017. Advancement of laser-guided intelligent pesticide spray control technology in specialty crop production. Abstract. ASHS. Hawaii. 10. Zhu, H., Li, Y., Shen, Y., and Liu, H. 2017. Versatile laser-guided spray control system to implement variable-rate functions for conventional air-blast sprayers. The ASABE Annual International Meeting, Spokane, Washington. 11. Fulcher, A., Lockwood, D., Wright, W., Zhu, H., Burnett, M., Smith, L., McHugh, J. and Pietsch, G. 2018. Characterizing spray penetration of a novel sprayer into Malus domestica ⿿Golden Delicious⿿ apple trees at a commercial orchard. HortScience 53S. 12. Fulcher, A., McHugh, J., Zhu, H., Collier, R, Wright, W., and Yeary, W. 2018. Powdery mildew control and spray application characteristics of a laser-guided sprayer. HortScience 53S. 13. Hong, S.W., Zhao, L. and Zhu, H., 2018. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers. Computers and Electronics in Agriculture. 149: 121-132. https://doi.org/10.1016/j.compag.2017.07.011 14. Hong, S., Zhao, L.Y., and Zhu, H. 2018. SAAS, A model tool for predicting spray drift from air-assisted sprayers. Presentation at 2018 ASABE Annual International Meeting, Detroit, MI. 15. Hong, S., Zhao, L.Y., and Zhu, H. 2018. SAAS, A model tool for predicting spray drift from air-assisted sprayers. Presentation at 2018 Pesticide Application Technology and Modeling Workshop, Detroit, MI. 16. Manandhar, A., Shah, A., Zhu, H., and Ozkan, E. 2018. Techno-economic analysis of using a conventional sprayer retrofitted with intelligent control functions for pesticide application in nursery crops. Presentation at 2018 ASABE Annual International Meeting, Detroit, MI. 17. Manandhar, A., Zhu, H., Ozkan, E. and Shah, A. 2018. Evaluating techno-economic impacts of using conventional sprayer retrofitted with intelligent control functions for pesticide application in apple orchards. Presented at: Plant Sciences Symposium at The Ohio State University 2018, April 6-7, Wooster, OH. and CFAES Annual Research Conference at The Ohio State University 2018, April 27, Wooster, OH. (Poster)
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: 18. Rosetta, R., Nackley, L., Pscheidt, J., and Zhu, H. 2018. Preliminary Evaluation of Intelligent System Retrofit Sprayer in Nursery Production. Reports from the 77th Annual Pacific Northwest Insect Management Conference. Portland, OR. p. 71-72. http://ipmnet.org/PNWIMC/Proceedings_and_Agenda_2018.pdf 19. Cui, S., Adriana, E., Inocente, A., Zhu, H., Acosta, N., Ling, P. and Keener, H. Development of portable E-nose system for early diagnosis of insect-stressed tomato plants. 2018. ASABE Paper No. 1800990. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 20. Yan, T., Zhu, H., Sun, L., Wang, X. and Ling, P. 2018. Detection of 3-D objects with a 2-D laser scanning sensor for greenhouse applications. ASABE Paper No. 1800179. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 21. Yan, T., Zhu, H., Sun, L., Wang, X. and Ling, P. 2018. Evaluation of spray accuracy for an experimental greenhouse variable-rate spray system. ASABE Paper No. 1800183. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 22. Zhang, Z., Zhu, H., Guler, H. and Shen, Y. 2018. Developing of premixing inline injection system for agricultural sprayers based on arduino and its performance evaluation. ASABE Paper No. 1800399. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 23. Zhu, H., Boldt, J., Fulcher, A., Gao, Y., Herms, D.A., Krause, C., Ling, P.,Lockwood, D., Niu, G., Ozkan, E., Pscheidt, J., Rosetta,R., Schnabel, G., Shah, A., Zhao, L., and Zondag, R. 2018. Laser-guided variable-rate pesticide spray technology for specialty crop Ppoduction. EuroAgEng Conference 2018. Page 176. 24. Zhu, H., Fulcher, A., Rosetta, R, and Wallhead, M. 2018. Advanced precision spray application technology for effective control of ornamental diseases. at the International Conference of Plant Pathology, Plant Health in a Global Economy held in Boston. 25. Fessler, L., Fulcher, A., Hines, J., Zhu, H., Hines, T, Wright, W., Yeary, W., Sun, X., and McClanahan, S. 2019. A dynamic laser-guided sprayer reduces pesticide use in large pot-in-pot production. HortScience, Issue 54. 26. Fulcher, A., Lockwood, D.W.,Wright, W., Fessler, L., Yeary, W., Burnett, M., Zhu, H., Sun, X., Pietsch, G. and McHugh, J. 2019. Characterizing spray penetration of a novel sprayer into Malus domestica ⿿Golden Delicious⿿ apple trees at a commercial orchard. HortScience, Issue 54.
• Type: Journal Articles Status: Published Year Published: 2016 Citation: 1. Liu, H., and Zhu, H. Evaluation of a laser scanning sensor on detection of complex shaped targets for variable-rate sprayer development. Transactions of the ASABE, 59(5): 1181-1192. 2016.
• Type: Journal Articles Status: Published Year Published: 2017 Citation: 2. Zhu, H., Rosetta, R., Reding, M. E., Zondag, R. H., Ranger, C. M., Canas, L., Fulcher, A., Derksen, R. C., Ozkan, H. E., and Krause, C. R. Validation of laser-guided variable-rate sprayer for managing insects in ornamental nurseries. Transactions of the ASABE, 60(2): 337-345. 2017. 3. Ru, Y., Zhao, L., Hadlocon, L. J. S., Zhu, H, and Ramdon, S. K. Laboratory evaluation of electrostatic spray wet scrubber to control particulate matter emissions from poultry facilities. Environmental Technology, 38(1): 23-33. 2017. 4. Zhu, H., Liu, H., Shen, Y., Liu, H., and Zondag, R. H. Spray deposition inside multiple-row nursery trees with a laser-guided sprayer. Journal of Environmental Horticulture, 35(1): 13-23. 2017. 5. Shen, Y., Zhu, H., Liu, H., Chen, Y., and Ozkan, E. Development of a laser-guided embedded-computer-controlled air-assisted precision sprayer. Transactions of the ASABE, 60(6): 1827-1838. 2017. 6. Wallhead, M., Zhu, H., and Broders, K. Hyperspectral evaluation of Venturia inaequalis Management using the disease predictive model RIMpro in the Northeastern U.S. Agricultural Sciences, 8: 1358-1371. 2017. 7. Wallhead, M., and Zhu, H. Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review. Journal of Environmental Horticulture, 35(2): 84-92. 2017.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: 8. Hong, S. W., Zhao, L., and Zhu, H. CFD simulation of pesticide spray from air-assisted sprayers in an apple orchard: Tree deposition and off-target losses. Atmospheric Environment, 175: 109-119. 2018. 9. Yeary, W., Fulcher, A., Zhu, H., Klingeman, W., and Grant, J. Spray penetration and natural enemy survival in dense and sparse plant canopies treated with carbaryl: implications for conventional and biological control. Journal of Environmental Horticulture, 36(1): 21-29. 2018. 10. Hong, S. W., Zhao, L., and Zhu, H. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers. Computers and Electronics in Agriculture, 149: 121-132. 2018. 11. Cui, S., Ling, P., Zhu, H., and Keener, H. M. Plant pest detection using artificial nose system: a review. Sensors, 18(2): 378-396. 2018. 12. Silva, J. E., Zhu, H., and Cunha, J. P. A. R. Spray outputs from a variable-rate sprayer manipulated with PWM solenoid valves. Applied Engineering in Agriculture, 34(3): 527-534. 2018. 13. Xiao, L., Zhu, H., Wallhead, M., Horst, L., Ling, P., and Krause, C. R. Characterization of biological pesticide deliveries through hydraulic nozzles. Transactions of the ASABE, 61(3): 897-908. 2018. 14. Yan, T., Zhu, H., Sun, L., Wang, X. and Ling, P. Detection of 3-D objects with a 2-D laser scanning sensor for greenhouse spray applications. Computers and Electronics in Agriculture, 152, 363-374. 2018. 15. Yan, T., Wang, X., Zhu, H., and Ling, P. Evaluation of object surface edge profiles detected with a 2-D laser scanning sensor. Sensors. 18(11): 1-17. 2018. 16. Hong, S. W., Zhao, L., and Zhu, H. SAAS, a computer program for estimating pesticide spray efficiency and drift of air-assisted pesticide applications. Computers and Electronics in Agriculture. 155: 58-68. 2018. 17. Lin, J. and Zhu, H. Fading process of herbicidal droplets amended with emulsifiable spray adjuvants on cucurbitaceae leaves. Transactions of the ASABE. 61(6): 1881-1888. 2018.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: 33. You, K., Zhu, H., Guler, H., Zhang, Z., Abbott, J.P., and Cui, S. 2019. Spray deposition and coverage on nursery trees with laser-guided variable-rate spray application. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 34. Zhang, Z., Zhu, H., and Hu, C. 2019. Integration of premixing in-line injection system into variable-rate orchard spraying systems. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 35. Abbott, J., and Zhu, H. 2019. Effects of maize leaf aging on sprayed droplet impact and adhesion. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 36. Zhang, Z., Zhu, H., and Hu, C. 2019. Assessments of premixing in-line injection system retrofitting on variable-rate orchard sprayers. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 37. Zhu, H. 2019. Laser-guided intelligent sprayer technology for fruit production⿝ at ⿿Orchard Pest Management and Intelligent Spraying Technologies. Presented at Penn State Fruit Research and Extension Workshop. 38. Abbott, J., and Zhu, H. 2019. Droplet impact and adhesion as related to quantified industry surface roughness parameters. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 39. Abbott, J., and Zhu, H. 2019. Interactions of hairy trichomes with sprayed droplet adhesion and spreading on leaves. 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 40. Chen, L., Zhu, H., Wallhead, M.,and Fulcher, A. 2019. Control of insects and diseases with intelligent variable-rate sprayers in ornamental nurseries. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 41. You, K., Zhu, H., Guler, H., Zhang, Z., Chen, L., Yan, T., Ozkan, E., and Zhao, L. 2019. Evaluation of airborne spray drift and ground loss from laser-guided variable-rate spray applications. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 42. Yan, T., Zhu, H.,Wang, X., and Ling, P. 2019. Development of a laser-guided boom spray system for greenhouse applications. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 43. Guler, H., Zhu, H., You, K., Zhang, Z., Chen, L.,Yan , L., and Ozkan, E. 2019. Spray performance comparisons between retrofitted intelligent sprayers and conventional constant-rate sprayers in vineyard applications. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 44. Chen, L., Zhu, H., Wallhead, M., Reding, M., and Horst, L. 2019. Evaluation of laser-guided intelligent sprayer to control insects and diseases in fruit plants. Presentation at 2019 ASABE Annual International Meeting, July 7-11, 2019, Boston, MA. 45. Boatwright, H., and Schnabel, G. 2020. Evaluation of laser-guided air blast sprayer on pest and disease control in peach orchards. 2020 APS Southern Division Meeting. Charleston, SC. 46. Chen, L., and Zhu, H. 2019. Evaluation of laser-guided intelligent sprayer to control insects and diseases in ornamental nurseries and fruit farms. The 40th Symposium on Pesticide Formulation and Delivery Systems: Formulation, Application and Adjuvant Innovation. Houston, Texas. 47. Fessler, L., Fulcher, A., Lockwood, D., Wright, W., Pietsch, G., Zhu, H., McClanahan, S., and Burnett, M. 2020. Controlling bitter and white rot in ⿿Golden Delicious⿿ apple trees with laser-guided variable-rate spray technology. HortScience 55(9): S252-253. 48. Fulcher, A., Fessler, L., Wright, W., Zhu, H., Pietsch, G., Yeary, W., Bordeau, T., and Nadaud, L. 2020. Improving nursery crop pest management with precision pesticide application technology. HortScience 55(9): S400-401.
• Type: Websites Status: Published Year Published: 2020 Citation: Precision Spray Application Research at Oregon State University website: https://horticulture.oregonstate.edu/nursery/precision-spray-applications Intelligent Spray Control Systems at Smart Guided Systems website: https://www.smartguided.com/intelligent-sprayer Good Fruit Grower Magazine ⿿Upgrade Your Airblast⿝ at https://indd.adobe.com/view/3f2ef5b3-0f6d-417d-ae61-d90b2e841a4b?transition Good Fruit Grower Magazine: https://www.youtube.com/watch?v=l2S5E2Vb-QA. The University of Tennessee Facebook Live Event ⿿A New Way to Keep Bugs Away⿝ at https://www.facebook.com/UTinstituteofagriculture/videos/615921495605329/. University of Tennessee AgCast https://anchor.fm/utiag/episodes/AgCast-Nursery-Sprayer-e484m7?fbclid=IwAR1eRsK54L1IErY812i6OGzbyu7x5804RzuzTLALvSQ8L5r0a43bMWwWT5U ⿿Nursery Sprayer⿝ UTIA YouTube Video. https://www.youtube.com/watch?v=8IlcZ6sY1io 6. Podcast: AgCast: ⿿Nursery Sprayer⿝. https://anchor.fm/utiag/episodes/AgCast-Nursery-Sprayer-e484m7/a-agjace The Ohio State University ⿿A Better Way to Spray⿝ at https://cfaes.osu.edu/news/articles/better-way-spray. USDA ARS News Services ⿿Precision Sprayer Benefits Growers and the Environment⿝ at https://www.ars.usda.gov/oc/dof/precision-sprayer-benefits-growers-and-the-environment/?utm_medium=email&utm_source=govdelivery. Maple Spider Mite. Pacific Northwest Nursery IPM website. http://oregonstate.edu/dept/nurspest/maple_spider_mite.html Precision Spray Application Research at Oregon State University website: https://horticulture.oregonstate.edu/nursery/precision-spray-applications Maple Spider Mite. Pacific Northwest Nursery IPM at Oregon State University website: http://oregonstate.edu/dept/nurspest/maple_spider_mite.html Intelligent Spray Control Systems at Smart Guided Systems website: https://www.smartguided.com/intelligent-sprayer Ohio State University College of Food Agricultural and Environmental Sciences YouTube Page announcing the Intelligent sprayer study receiving the ⿿Innovation of the Year⿝ award: https://www.youtube.com/watch?v=5H9Nm2a_qOE&feature=emb_title
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: 49. Fulcher, A., Lockwood, D., Fessler, L., Wright, W., Zhu, H., Bordeau, T., Nadaud, L., Pietsch, G., Yeary, W., and Nackley, L. 2020. Reduce pesticide volume and off-target loss across a range of apple phenological stages with variable-rate spray technology. HortScience 55(9): S373. 50. Gao, G. 2019. ⿿Cool Tips to Winterize Your Orchard Sprayers.⿝ American Fruit Grower Magazine (November, 2019) and GrowingProduce.com (December 11, 2019.) Retrieved online at https://www.growingproduce.com/fruits/5-cool-tips-to-winterize-your-orchard-sprayers/#Tinsel/147611/3 51. Manandhar, A., Zhu, H., Ozkan, E. and Shah, A. 2020. Techno-economic impacts of laser-guided variable-rate pesticide application for maintaining health of nursery crops. Presented at: Plant Sciences Symposium at The Ohio State University 2020, April 6-7, Online. (Poster) 52. Nair, U. 2020. Development of an intelligent sprayer with improved canopy estimations for greenhouse sprayer applications. Master of Science thesis, The Ohio State University. 53. Nair, U., H. Zhu, A. Shah, and P. Ling. 2020. Improved Canopy Estimation for Greenhouse Spray Application. Northeast Agricultural and Biological Engineering Conference (NABEC). July 28, 2020. Online. 54. Pscheidt, J.W., Warneke, B.W., Rosetta, R. and Nackley, L. 2019 (Nov). The intelligent sprayer system ⿿ second year evaluation of a sprayer retrofit for management of grape powdery mildew. Vine to Wine Newsletter. OWRI. 55. Salcedo, R., Zhu, H., Zhang, Z., Wei, Z., Chen, L., and Ozkan, E. 2020. Evaluation of PWM technologies for pesticide spray applications in a two-year old apple orchard. ASABE Paper No. 2000079. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 56. Scherr, M., Rosetta, R. and Nackley, L. 2020. A new pocket guide common natural enemies of crop and garden pests in the Pacific Northwest. In press 57. Schnabel, G. 2020. Disease management in peach. Production meeting. Clemson Extension. Walhalla, Edgefield, Gaffney, SC. 58. Si, G. 2020. A review of 3D lidar point cloud registration for mapping of plant properties in indoor greenhouse environment. NABEC2020. Virtual presentation. 59. Warneke, B., Nackley, L.L., Rosetta, R., and Pscheidt, J.W. 2020. Using an intelligent sprayer and sulfur for management of grape powdery mildew. Abstract. Phytopathology (in press, poster presentation at APS Annual Meeting) 60. Warneke, B., Pscheidt, J. Rosetta, R. and Nackley, L.L. 2019. Efficacy of an intelligent sprayer on grape powdery mildew management, Oregon Wine Symposium, Portland, OR (February 12, 2019). 61. Warneke, B.W., Pscheidt, J.W., Rosetta, R. and Nackley, L.L. 2019. Out of the box and through the rows: Intelligent spray sstem research at Oregon State University. Abstract. Phytopathology S3.7 (Oral and Poster presentation at APS Pacific Division meeting.) 62. Warneke, B.W., Pscheidt, J.W., and Nackley, L.L. Routine maintenance for airblast sprayers. 202X (in review). OSU Extension Publication (includes video) 63. Wei, Z., Zhu, H., Salcedo, R., Zhang, Z., and Duan, D. 2020. Effect of pressure fluctuation on droplet size distribution from pulse width modulated nozzles. ASABE Paper No. 2000124. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). 64. Zhang, Z., and Zhu, H. 2019. Integration of premixing in-line injection system into variable-rate orchard spraying systems. The 40th Symposium on Pesticide Formulation and Delivery Systems: Formulation, Application and Adjuvant Innovation. Houston, Texas. 65. Zhang, Z., Zhu, H., Hu, C., Wei, Z. and Salcedo, R. 2020. Graphical user interface design for premixing in-line injection system attached to a variable-rate orchard sprayer. ASABE Paper No. 2000099. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085).

Progress 09/01/19 to 08/31/20

Outputs
Target Audience:Target audiences are growers, farm managers, and sprayer applicators (including Hispanic and African American growers and workers) of specialty crops (nursery, peach orchard, apple orchard, pecan orchard, citrus, grape, winery, blueberry, raspberry, cranberry, hazelnuts, hops and greenhouse crops), extension specialists and educators, county agents, viticulturists, researchers, undergraduate and graduate students, robotics and artificial intelligence enthusiasts, agricultural industry consultants, commercial diagnosticians, general public, sprayer manufacturers, chemical companies, greenhouse equipment suppliers, national and state legislators, and environmental protection agency regulators. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Similar to previous years, professional development trainings and services in using the intelligent spray technology were provided for growers, farm managers, spray applicators and engineers in Hale and Hines Nursery in Tennessee, The Apple Barn in Tennessee, Hans Nelson & Sons Nurseries in Oregon, J. Frank Schmidt & Son Co. in Oregon, Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klyn Nurseries in Ohio, Klinshirn Winery in Ohio, Bauman Orchards in Ohio, Blueberry Patch in Ohio, OARDC Horticulture Field in Ohio, Clemson University Musser Fruit Research Farm, Oregon State University Research Farm, University of Queensland, Washington State University Fruit Research Farm, and Smart Guided Systems. These growers, farm managers and spray applicators as well as local extension educators gained first-hand experience in advancing conventional sprayers to the intelligent spray technology based on the sprayer types and functions. The presentations given as part of this project had pesticide recertification training credits available for participants and had them indirectly learn and better understand aspects of sprayer calibration and application. Spray applicators in every state must accumulate a certain number of credits each year to maintain their pesticide licenses. This project has helped many participants maintain their accreditation and helped them think about how to spray their plants for better pest management with the intelligent spray technology. High school research interns, undergraduate students, graduate students and post-doctoral fellows at The Ohio State University, Oregon State University, University of Tennessee, Clemson University and USDA-ARS were trained in research methodologies in development of intelligent spray technologies through their involvements in the research, presentations at meetings, demonstrations, and laboratory and on-farm tours. They were also trained on the development of the techno-economic analysis models, collecting data from different sources and conducting the analyses. These students and post-doctoral fellows learned about the pesticide sprayer technologies applicable to different nursery, orchard and vineyard types, pesticide application procedure and schedule, and resources required for spraying pesticides in the orchards to achieve sustainable crop production and environmental stewardship. They also gained an appreciation for the various sensors for advanced agricultural equipment as well as an understanding of conducting field research with grower-cooperators. How have the results been disseminated to communities of interest?The research results on the intelligent spray technology reached communities of interest through different disseminated efforts. The communities included specialty crop growers, farm managers, spray applicators, allied suppliers, industries, chemical companies, sprayer manufacturers, undergraduate and graduate students, researchers, extension agents and area specialists, educators, ag consultants, legislators, environmental policy regulators, water quality providers, and public. The disseminated efforts included oral and poster presentations, national and international conferences, extension workshops, field demonstrations, pesticide applicator training and licensing programs, trade shows, meetings and consultations, peer reviewed journal articles, and press articles in trade magazines and newsletters, and website as reported in Products and Other Products above. They also included on-farm tests of intelligent spray prototype systems in nurseries, apple orchards, peach orchards, pecan orchards, vineyards, and small-fruit farms in Ohio, Oregon, Tennessee, South Carolina, Washington, New York, Michigan, Indiana, Pennsylvania, Iowa, California, Florida and Texas. Results from economic analyses were also disseminated to orchard and nursery owners and growers during field visits and personal communication. Smart Guided Systems, LLC, in Indianapolis, IN, commercialized the intelligent spray-control system. The commercial product was recognized by American Society of Agricultural and Biological Engineers (ASABE) as the 2020 AE50 Award Winners that are the best 50 new product innovations in engineering and technology for agricultural, food, and biological systems in 2019, received the Davidson Prize for being selected as the top winner of the 2020 AE50 award winners by ASABE, and was selected as the 2020 Top-10 New Product Winners by World Ag Expo. Citrus, apple, grape, pecan, and nursery growers in the United States and other countries are upgrading their sprayers with the commercial product. What do you plan to do during the next reporting period to accomplish the goals?We have accomplished the project goals and will look forward new opportunities to expand the research goals in the future.

Impacts
What was accomplished under these goals? In Tennessee: Determined the appropriate spray rates and the associated drift for utilizing Intelligent spray technology based on spray application characteristics on water sensitive cards for spindle-trained Fuji apples (less than or equal to 0.03 fl oz/ft^3). Initiated a study on pesticide volume savings, target foliage coverage and deposit density, and aerial and ground drift from utilizing Intelligent spray technology across a range of phenology stages for spindle trained Fuji apples. Established target canopy spray characteristics, aerial and ground drift, and pesticide volume savings from utilizing Intelligent spray technology in 2 phenological stages of oaks grown in a multi-row pot-in-pot production system (40-46% reduction). In Oregon: A conventional Mini-Pac air-blast sprayer retrofitted with the intelligent spray system (ISS) was evaluated for powdery mildew management in a research vineyard at Oregon State University. Comparisons between the ISS and standard/conventional applications of sulfur and biologicals were evaluated on several different vines. Using more concentrate sulfur solutions, doubling the spray rate from 0.06 fl oz/ft3 to 0.12 fl oz/ft3 of canopy or using systemic fungicides resulted in similar powdery mildew control compared to standard airblast spraying. Coverage of boxwood plants was evaluated with the ISS at different rates of water/A. All intelligent and conventional spraying modes did well at covering the outside leaves but not for interior leaves. Rates needed to be at least 300 gal/A to begin to penetrate tightly sheared plants. In South Carolina: Evaluated a LIDAR-based variable rate sprayer system in three experimental peach orchards for pest and brown rot disease control, spray volume output, spray coverage, and spray drift. A single 378 L air-blast sprayer was used for both the conventional air-blast and the Intelligent Sprayer (iSprayer) treatments. Treatments were started at the phenological stage of bloom and continued through final swell. The iSprayer treatment was as effective in controlling pests and brown rot disease as the conventional air-blast treatment. Compared to the conventional air-blast treatment, the iSprayer treatment reduced the spray volume (liter/hectare) in cultivar 'PF23' by 71% at bloom, 62% at pit hardening and 55% at final swell, respectively. For 'Juneprince' the spray volume reduction was 50% at bloom, 40% at pit hardening, and 13% at final swell, respectively. Spray drift was significantly (P<0.05) reduced only at bloom in the iSprayer treatment. Spray coverage was increased by 50.13% and 26.67% in the iSprayer treatment at bloom and pit hardening, respectively, but not at final swell. Test results show that the iSprayer maintained pest and disease control efficacy in peach orchards, while reducing spray volume and drift compared to the conventional air-blast treatment. In Ohio: (1) A new approach was investigated to improve canopy characterization for greenhouse crops. This was done with the introduction of a point cloud data processing algorithm to map 3-D plant canopy and an evaluation of mounting height of the laser sensor. Compared to previous method, a 46% measurement error reduction was achieved by effectively isolating individual targets from the dataset, removing distortion, and estimating the occluded portion of the plant canopies. The proposed processing algorithm was also more reliable in accurately measuring plant canopies for the different sensor heights, and the distances between the plants and the laser sensor. The improvement was largely due to more accurate measurement of farther away plants where less point cloud data and more occlusion was observed. Consequently, an offline precision variable-rate spray control system was developed for greenhouse applications. The system was able to carry out asynchronous, precision spray operations based on the mapped 3-D plant canopy ests of retrofitted intelligent variable-rate sprayers in three commercial nurseries, a commercial winery and a commercial blueberry farm in Ohio further confirmed the reliability and chemical reduction benefits of the intelligent spray technology for specialty crop production. (3) The newly developed premixing in-line injection system attached on a laser-guided intelligent orchard sprayer was tested to eliminate tank mixture leftover problems in both laboratory and fields. This system primarily consisted of a precision fluid metering pump, a water pump, a static mixer, a premixing tank and a buffer tank. Accuracy of the system was tested with simulated pesticides (tap water, turpentine oil, prime oil, and four concentrations of sucrose solutions) with various viscosities. Test results demonstrated that the premixing in-line injection system could further reduce pesticide waste and improve environmental stewardship for conventional and precision variable-rate orchard sprayers. (4) Results from the techno-economic analysis evaluating the technical feasibility and economic impacts of pesticide application using conventional and intelligent sprayers (conventional sprayer retrofitted with intelligent control functions) for apple orchards were finalized. Data on pesticide application schedule, pesticide spraying time, and pesticide cost was collected from growers and updated in the TEA model. The variable-rate sprayer reduced pesticide requirements, number of sprayer refills, spraying time and resources requirements. For nurseries with area of 10 to 200 acres, cost savings of $245 to $446/acre was obtained with variable-rate sprayer, with a payback period of 2-5 years. Lower overall pesticide application costs and payback period was for 200-ac nursery.

Publications

• Type: Journal Articles Status: Published Year Published: 2020 Citation: Abbott, J. R., Zhu, H., Ambose, A.E. 2020. Droplet impact and adhesion on leaf surfaces as related to the arithmetic mean roughness length. Transactions of the ASABE. In press. Abbott, J., and Zhu, H. 2019. 3D optical surface profiler for quantifying leaf surface roughness. Surface Topography: Metrology and Properties. 7(4): 045016. DOI: 10.1088/2051-672X/ab4cc6. Boatwright, H. and Schnabel, G. 2020. Evaluation of the intelligent sprayer system in peach production. Plant Disease. In press. https://doi.org/10.1094/PDIS-04-20-0696-RE. Chen, L., Wallhead, M., Reding, M., Horst, L., and Zhu, H. 2020. Control of insect pests and diseases in an Ohio fruit farm with laser-guided intelligent sprayer. HortTechnology. 30(2): 168⿿175. https://doi.org/10.21273/HORTTECH04497-19. Chen L., and Zhu, H. 2020. Evaluation of laser-guided intelligent sprayer to control insects and diseases in ornamental nurseries and fruit farms. Journal of ASTM International. 40: 1-10. Chen, L., H. Zhu, M. Wallhead, and A. Fulcher. 2019. Control of insects and diseases with intelligent variable-rate sprayers in ornamental nurseries. Journal of Environmental Horticulture. 37(3):90-100. https://doi.org/10.24266/0738-2898-37.3.90 Cui, S., Inocente, E. A. A., Acosta, N., Keener, H. M., Zhu, H., and Ling, P. 2019. Development of fast e-nose system for early-stage diagnosis of aphid-stressed tomato plants. Sensors. 19(16): 3480. DOI: 10.3390/s19163480. Fessler, L., Fulcher, A., \Lockwood, D., Wright, W., and Zhu, H. Advancing sustainability in tree crop pest management: Refining spray application rate with a Llser-guided variable-rate sprayer in apple orchards. HortScience. 55(9):1522-1530. https://doi.org/10.21273/HORTSCI15056-20. Guler, H., Zhang, Z., Zhu, H., Grieshop, M., and Ledebuhr, M. 2020. Spray characteristics of rotary micro sprinkler nozzles used in orchard pesticide Ddelivery. Transactions of the ASABE. In press. Manandhar, A., Zhu, H., Ozkan, E., and Shah, A. 2020. Techno-economic impacts of using a laser-guided variable-rate spraying system to retrofit conventional constant-rate sprayers. Precision Agriculture. 21: 1156⿿1171. https://doi.org/10.1007/s11119-020-09712-8. Salcedo, R., Zhu, H., Zhang, Z., Wei, Z., Chen, L., Ozkan, E., and Falchieri, D. 2020. Foliar deposition and coverage on young apple trees with PWM-controlled spray systems. Computers and Electronics in Agriculture. 178: 105794. https://doi.org/10.1016/j.compag.2020.105794. Warneke, B., Zhu, H., Pscheidt, J. W., Nackley, L. L. 2020. Perspective: Canopy spray application technology in specialty crops: A slowly evolving landscape. Pest Management Science. In press. Wei, Z., Zhu, H., Zhang, Z., Salcedo, R., and Duan, D. 2020. Droplet size spectrum, activation pressure and flow rate discharged from PWM flat-fan nozzles. Transactions of the ASABE. In press. Zhang, Z., Zhu, H., Guler, H. 2020. Quantitative analysis and correction of temperature e?ects on fluorescent tracer concentration measurement. Sustainability. 12: 4501. doi:10.3390/su12114501 Zhang, Z., and Zhu, H. 2020. Hardware and software design for premixing in-line injection system attached on variable-rate orchard sprayers. Transactions of the ASABE. Transactions of the ASABE. 63(4): 823-831. Zhang, Z., Zhu, H., Salcedo, R., and Wei, Z. 2020. Assessment of premixing in-line injection system attached on variable-rate orchard sprayer. Journal of ASTM International. 40: 11-24. Zhang, Z., Zhu, H., Salcedo, R., and Wei, Z. 2020. Assessment of chemical concentration accuracy and mixture uniformity of premixing in-line injection system. Computers and Electronics in Agriculture. 176: 105670. https://doi.org/10.1016/j.compag.2020.105670.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Chen, L., and Zhu, H. 2019. Evaluation of laser-guided intelligent sprayer to control insects and diseases in ornamental nurseries and fruit farms. The 40th Symposium on Pesticide Formulation and Delivery Systems: Formulation, Application and Adjuvant Innovation. Houston, Texas. Gao, G. 2019. ⿿Cool Tips to Winterize Your Orchard Sprayers.⿝ American Fruit Grower Magazine (November, 2019) and GrowingProduce.com (December 11, 2019.) Retrieved online at https://www.growingproduce.com/fruits/5-cool-tips-to-winterize-your-orchard-sprayers/#Tinsel/147611/3 Warneke, B., Pscheidt, J. Rosetta, R. Nackley, L.L. 2019. Efficacy of an Intelligent Sprayer on Grape Powdery Mildew Management, Oregon Wine Symposium, Portland, OR (February 12, 2019). Warneke, B. W., Pscheidt, J. W., Rosetta, R. and Nackley, L.L. 2019. Out of the Box and Through the Rows: Intelligent Spray System Research at Oregon State University. Abstract. Phytopathology S3.7 (Oral and Poster presentation at APS Pacific Division meeting.) Zhang, Z., and Zhu, H. 2019. Integration of premixing in-line injection system into variable-rate orchard spraying systems. The 40th Symposium on Pesticide Formulation and Delivery Systems: Formulation, Application and Adjuvant Innovation. Houston, Texas.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Boatwright, H. and Schnabel, G. 2020. Evaluation of laser-guided air blast sprayer on pest and disease control in peach orchards. 2020 APS Southern Division Meeting. Charleston, SC. Fessler, L., Fulcher, A. Lockwood, D. Wright, W. Pietsch, G. Zhu, H., McClanahan, S. and Burnett, M. 2020. Controlling bitter and white rot in ⿿Golden Delicious⿿ apple trees with laser-guided variable-rate spray technology. HortScience 55(9): S252-253. Fulcher, A., Fessler, L.,Wright, W., Zhu, H., Pietsch, G., Yeary, W., Bordeau, T., and Nadaud, L. 2020. Improving nursery crop pest management with precision pesticide application technology. HortScience 55(9): S400-401. Fulcher, A., Lockwood, D., Fessler, L., Wright, W., Zhu, H., Bordeau, T., Nadaud, L., Pietsch, G., Yeary, W., and Nackley, L. 2020. Reduce pesticide volume and off-target loss across a range of apple phenological stages with variable-rate spray technology. HortScience 55(9): S373. Manandhar, A., Zhu, H., Ozkan, E. and Shah, A. 2020. Techno-economic impacts of laser-guided variable-rate pesticide application for maintaining health of nursery crops. Presented at: Plant Sciences Symposium at The Ohio State University 2020, April 6-7, Online. (Poster) Nair, U. 2020. Development of an Intelligent Sprayer with Improved Canopy Estimations for Greenhouse Sprayer Applications. Master thesis, The Ohio State University Nair, U., H. Zhu, A. Shah, and P. Ling. 2020. Improved Canopy Estimation for Greenhouse Spray Application. Northeast Agricultural and Biological Engineering Conference (NABEC). July 28, 2020. Online. Pscheidt, J. W., Warneke, B. W., Rosetta, R. and Nackley, L. 2019 (Nov). The Intelligent Sprayer System ⿿ second year evaluation of a sprayer retrofit for management of grape powdery mildew. Vine to Wine Newsletter. OWRI. Salcedo, R., Zhu, H., Zhang, Z., Wei, Z., Chen, L., and Ozkan, E. 2020. Evaluation of PWM technologies for pesticide spray applications in a two-year old apple orchard. ASABE Paper No. 2000079. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Scherr, M., Rosetta, R. and Nackley, L. 2020. A new Pocket Guide Common Natural Enemies of Crop and Garden Pests in the Pacific Northwest. In press Schnabel, G. 2020. Disease management in peach. Production meeting. Clemson Extension. Walhalla, SC. Schnabel, G. 2020. Disease management in peach. Production meeting. Clemson Extension. Edgefield, SC. Schnabel, G. 2020. Disease management in peach. Production meeting. Clemson Extension. Gaffney, SC. Si, G. 2020. A review of 3D lidar point cloud registration for mapping of plant properties in indoor greenhouse environment. NABEC2020. Virtual presentation. Warneke, B., Nackley, L. L., Rosetta, R., Pscheidt, J. W. 2020. Using an intelligent sprayer and sulfur for management of grape powdery mildew. Abstract. Phytopathology (in press, poster presentation at APS Annual Meeting) Warneke, B. W., Pscheidt, J. W., and Nackley, L.L. Routine Maintenance for Airblast Sprayers. 202X (in review). OSU Extension Publication (includes video) Wei, Z., Zhu, H., Salcedo, R., Zhang, Z., and Duan, D. 2020. Effect of Pressure Fluctuation on Droplet Size Distribution from Pulse Width Modulated Nozzles. ASABE Paper No. 2000124. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Zhang, Z., Zhu, H., Hu, C., Wei, Z. and Salcedo, R. 2020. Graphical user interface design for premixing in-line injection system attached to a variable-rate orchard sprayer. ASABE Paper No. 2000099. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085).

Progress 09/01/18 to 08/31/19

Outputs
Target Audience:Target audiences are growers, farm managers, and sprayer applicators (including Hispanic and African American growers and workers) of specialty crops (nursery, peach orchard, apple orchard, pecan orchard, citrus, grape, winery, blueberry, raspberry, cranberry, hazelnuts and greenhouse crops), extension specialists and educators, county agents, viticulturists, researchers, undergraduate and graduate students, robotics and artificial intelligence enthusiasts, agricultural industry consultants, commercial diagnosticians, general public, sprayer manufacturers, chemical companies, national and state legislators, and environmental protection agency regulators. Efforts were made through on-farm field demonstrations, extension workshops and field days, pesticide applicator training and licensing programs, trade shows, trade magazines, newsletters, scientific journal articles, and regional, national and international conferences. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Similar to previous years, professional development trainings and services in using the intelligent spray technology were provided for growers, farm managers, spray applicators and engineers in Hale and Hines Nursery in Tennessee, Wooden's Apple House in Tennessee, Hans Nelson & Sons Nurseries in Oregon, J. Frank Schmidt & Son Co. in Oregon, Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio, Blueberry Patch in Ohio, Bauman Fruit orchards in Ohio, OARDC Horticulture Field in Ohio, Five R Enterprises pecan farm in Texas, Clemson University Musser Fruit Research Farm, Oregon State University Research Farm, University of Queensland, and Smart Guided Systems. These growers, farm managers and spray applicators as well as local extension educators gained first-hand experience in advancing conventional sprayers to the intelligent spray technology based on the sprayer types and functions as well as engineers to prepare for commercialization of the intelligent sprayer technology. Many of the presentations given as part of this project had pesticide recertification training credits available for participants. When discussing the intelligent spray systems, participants indirectly learned and better understood aspects of sprayer calibration and application. In many states, spray applicators possessing pesticide licenses must accumulate a certain number of credits each year to maintain their licenses. This project helped many participants maintain their accreditation. During sprayer demonstrations, participants were involved in placing water sensitive spray cards wherever they wanted in the test plots. After spraying water and collecting the cards, group discussions helped participants understand why their cards were or were not covered well. Discussions centered on sprayer calibration, how to get better coverage, sprayer speed, etc., and how to take this information back to their own situations. Numerous high school students, undergraduate students, graduate students and post-doctoral fellows at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University and USDA-ARS were trained in research methodologies in development of intelligent spray technologies through presentations, demonstrations and laboratory tours. They were also trained on the development of the techno-economic analysis models, collecting data from different sources and conducting the analyses. These students and post-doctoral fellows learned about the pesticide sprayer technologies applicable to different nursery, orchard and vineyard types, pesticide application procedure and schedule, and resources required for spraying pesticides in the orchards to achieve sustainable crop production and environmental stewardship. They also gained an appreciation for the various sensors for advanced agricultural equipment as well as an understanding of conducting field research with grower-cooperators. How have the results been disseminated to communities of interest?Research outcomes of the new intelligent sprayer technologies reached target audiences through different outreach efforts including presentations and field demonstrations given at 2019 ASABE Meeting; 2019 ASHS Conference, 2019 American Phytopathology Society Pacific Division meeting; 15th Workshop on Spray Application and Precision Technology in Fruit Growing in United Kingdom; 2019 OPGMA Congress, Columbus, OH; Ohio Grape and Wine Conference, Dublin, OH; Blueberry and Grape Grower Cooperators, Avon Lake and Mansfield, OH; Ohio Blueberry, Bramble and Grape Field Night, Piketon, OH; Spray Drift Seminar, Dayton, OH; Ohio Farm Bureau "ExploreAg", Wooster, OH; Cultivate'19, Columbus, OH; 2019 Farm Science Review, London, OH; The Ohio State University Extension Educators, Columbus, OH; Greenhouse Management Workshop; Wooster, OH; Guest lecture at Agricultural Technical Institute/The Ohio State University, Wooster, OH; NCERA-101 USDA Regional Committee meeting, Montreal, ON, Canada; NASA Utilization and Life Science Workshop, Kennedy Space Center, FL; CPAAS Ag Tech Day, Prosser, WA; Intelligent Sprayer Add-on Kit for Air-blast Sprayers Field Demo, Groveland, FL; Penn State Extension "Orchard Pest Management and Intelligent Spraying Technologies" Workshop, Biglerville, PA; Green Industry Express, Chattanooga, TN; Southeast Apple Growers Meeting, Asheville, NC; Southeast Regional Fruit & Vegetable Conference, Savannah, GA; Pick TN Conference, Franklin, TN; TN Organic Growers Association; TN Fruit & Vegetable Association; TN Farm Winegrowers Alliance; Plateau Fruit School, Crossville, TN; EPP 630 Advanced Integrated Pest and Pathogen Management, Knoxville, TN; UT-TDA Master Producer Oversight meeting, Crossville, TN; HORT 3050 -Viticulture and Enology in the Mediterranean Region, Cortona, Italy; Tennessee Green Industry Day; Tennessee Association of Pesticide Applicators, Gatlinburg, TN; American Society for Horticultural Science Annual Conference, Las Vegas, NV; Characterizing spray penetration of a novel sprayer intoMalus domestica'Golden Delicious' apple trees at a commercial orchard; Hydrangea Production Workshop, Knoxville, TN; Hydrangea Production Workshop, Clarksville, TN; Turf and Ornamental Field Day, Knoxville, TN; FaceBook Live Event, Knoxville, TN; Nutrient Hazelnut growers meeting, Lebanon, OR; Oregon State University Grape Day, Corvallis, OR; Napa Valley Grape Growers, Napa, CA; Shade Tree Growers Meeting, Aurora, OR; Oregon State University Winter Hort. Meeting, Hood River, OR; Oregon Wine Symposium, Portland, OR; Pesticide Recertification Course, Medford, OR; Orchard Pest and Disease Management Conference, Portland, OR; Hermiston Farm Fair, Hermiston, OR; Fall Orchard/Vineyard Pest Management meeting, Roseburg, OR; 21st Ornamental Workshop on Insects and Diseases, Hendersonville, NC; LIVE/OWRI Field Day, NW Wine Studies Center, Chemeketa Community College, West Salem, OR; Spring Vineyard Mechanization Workshop, Medford, OR; Oregon State University 150 Celebration, The Promise and the Peril of Artificial Intelligence and Robotics, Corvallis, OR; Farwest Show, Portland, OR; Intelligent Sprayer Workshop, Boring, OR; and South Caroline extension and grower meetings, SC. Presentations were also given to The University of Manchester, England; European Technical committee -N8- on Sensors and Electronics; University of Polytechnic at Department of Agricultural and Biological Engineering, Barcelona, Spain; National Institute for Environmental and Agricultural Science and Research at Montpellier, France; two Nozzle manufacturers (Lechler, Albuz), and two sprayer manufacturers (Berthoud, Kuhn), France; Ankara University College of Agriculture, Turkey; and individual researchers specialized in pesticide spray technologies from Spain, Italy and Poland. Results from economic analyses were also disseminated to orchard and nursery owners and growers during field visits and personal communication. A manuscript entitled 'Techno-economic impacts of using laser-guided variable-rate spraying system to retrofit on conventional constant-rate sprayers for pesticide savings in apple orchards' was submitted to 'Precision Agriculture' journal for publication. The research results on the intelligent spray technology reached communities of interest including specialty crop growers, farm managers, allied suppliers, industries, chemical companies, sprayer manufacturers, high school students, university undergraduate and graduate students, researchers, extension agents and area specialists, educators, ag consultants, legislators, environmental policy regulators, water quality providers, and public through presentations, workshops, field demonstrations, trade shows, meetings and consultations, peer reviewed journal articles, and press articles in trade magazines and newsletters, website, and also through on-farm tests of intelligent spray prototype systems in nurseries, apple orchards, peach orchards, pecan orchards, vineyards, and small-fruit farms in Ohio, Oregon, Tennessee, South Carolina, Washington, New York, Michigan, Indiana, Pennsylvania, Iowa, California, Florida and Texas. USDA Secretary Sonny Perdue highlighted the intelligent sprayer research as an exemplary example of the advanced technology to improve agriculture production at his keynote speak for the 2019 Impact Washington Summit. What do you plan to do during the next reporting period to accomplish the goals?Spray deposition and coverage, spray volume consumption, pesticide cost savings, and biological efficacy will be continuously investigated for growers' existing sprayers retrofitted with the universal intelligent spray control systems in Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klyn Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio; Bauman Orchards in Ohio, The Blueberry Patch in Ohio; Hans Nelson & Sons Nurseries in Oregon, J Frank Schmidt Nurseries in Oregon, Hale & Hines Nursery in Tennessee, The Apple Barn in Tennessee, Renteria Vineyard in California, Clemson University Musser Fruit Research Farm, Oregon State University Botany Plant Pathology Farm, The Ohio State University OARDC Horticulture Field, University of Tennessee Plant Sciences Experiment Station, and University of Queensland in Australia. Crops will be apples, peaches, grapes, blueberries, raspberries, pecans, hazelnuts, and different species and varieties of ornamental nursery stocks. Pests will be historical and emerging insects and diseases. Comparison tests will be conducted for the sprayers with and without the automatic intelligent control functions to optimize the intelligent sprayer parameters. Fruit quality data will be measured and assessed with refractometers, pH meters and HPLC-Mass Spectrometer. In addition, the tests will include investigating effects of sprayer type on beneficial insect population, and effects of tree phenology and tree age on pesticide consumption and spray characteristics from intelligent and conventional spray applications on nursery stocks and apples at Hale and Hines Nursery and The Apple Barn in Tennessee. Pesticide costs from different vendors will be continuously collected and economic advantages will be analyzed for using the intelligent spray technology to spray nursery crops of different canopy sizes. Field test data will be analyzed, summarized and formatted for preparing manuscripts to be submitted for publications and disseminated via peer-review journals. Research findings will be shared with more growers at upcoming conferences, workshops, and field days in 2020. Improvement of the intelligent greenhouse spray system design will be continued and will be tested in a commercial greenhouse (Casa Verde Growers in Ohio). The spray system validation will include its accuracy to detect the presence, size, shape, and foliage density of different plants and then discharge desired amounts of sprays from each nozzle as needed in real time. Improvement of techno-economic models, spray deposition and drift prediction models, and pest management expert decision models will be continued for different specialty crops. The SAAS program will be further validated for its reliability and validity to be used in a wide range of pesticide application scenarios, and will be integrated with the intelligent sprayer control system as an expert system to make the intelligent sprayer more precisely controlled. It will also be distributed as forms of stand-alone software so that farmers and extension agencies can evaluate spray drift problems and adjust spray settings to improve the application performance according to weather and crop conditions. Research results will be continuously dismissed to communities of interest, commodity stakeholders and public through workshops, on-farm field demonstrations, trade magazines, trade shows, extension education events, professional meetings, and scientific journals. The intelligent spray control system has been commercialized by Smart Guided Systems LLC (https://www.smartguided.com/intelligent-sprayer). The research team will continuously provide field test findings for this new technology, so growers and sprayer manufacturers will have a reliable and affordable new intelligent system to increase the application efficiency and reduce uncertainty associated with current pesticide delivery systems used in specialty crop production. As a result of this research, newly developed pesticide application technology and strategy will achieve real cost benefits to producers, consumers and the environment, and create safer and healthier conditions for workers.

Impacts
What was accomplished under these goals? In Tennessee: (1) the appropriate spray rates of 0.03 fl oz per cubic ft or less were determined for utilizing the intelligent spray technology to control pests on semi-dwarf 'Golden Delicious' apples; (2) pesticide volume savings in the range between 59% and74% for Red Rome apples and between 40% and 45% for oaks at different phenology stages were documented from utilizing the intelligent spray technology; (3) beneficial insect populations in an orchard and a nursery were documented to facilitate future research; (4) efficacy of conventional and intelligent treatments along with spray coverage was compared by scouting and rating oaks for oak leaf blister and oak leaf spot, maples for tar spot an anthracnose, and zelkova for leaf spot biweekly. In Oregon: (1) A conventional Mini-Pac air-blast sprayer retrofitted with the intelligent spray system (ISS) was evaluated for powdery mildew management in a research vineyard at Oregon State University. Comparisons between the ISS and conventional applications of sulfur were evaluated on Pinot noir and Pinot gris vines. Using more concentrate sulfur solutions, doubling the spray rate from 0.06 fl oz/ft3 to 0.12 fl oz/ft3 of canopy or using systemic fungicides resulted in similar powdery mildew control to standard airblast spraying. (2) A phenological coverage trial was concurrently conducted with the grape powdery mildew trial at three different time points important in grape development. While the ISS did not have as good of spray coverage as a standard sprayer, it significantly reduced drift in the first two time points, with reductions of 79%, 71%, and 61% in spray volume at each time point, respectively. (3) Coverage of young hazelnut tree shoot tips was evaluated with the ISS at different ground speeds but normalizing the rate/A with different nozzles to compensate for speed. Shoots were evaluated with a new digitization system that detects the coverage of shoot tips using the white colored product Surround (kaolin clay). In Texas: An intelligent spray system was installed on a 1000-gallon air-assisted pecan orchard sprayer as a retrofit to spray zinc, manganese and copper solutions in a mature commercial pecan orchard. Spray coverage test results showed equivalent deposition to the top canopy with the intelligent sprayer was achieved compared to a conventional sprayer. However, improvements were needed to prevent the laser sensor from heavy dust for the intelligent sprayer to be used in dusty pecan orchards in Texas. In South Carolina: Field experiments were conducted in blocks of early season (Juneprincess) and late season (PF23) cultivars during the growing season in peach orchards. Results indicated that the intelligent sprayer controlled cat facing and brown rot disease as effectively as the conventional sprayer. The intelligent sprayer used significantly less material especially early season when canopy density was low. In Ohio: (1) Two more growers' sprayers were retrofitted with the intelligent spray system and were tested for their efficacy in Bauman Orchards and The Blueberry Patch in Ohio. With the retrofit, these conventional sprayers were upgraded to perform intelligent functions in controlling spray outputs to match canopy presence, size and leaf density in real time. (2) Field experiments conducted in a young apple orchard demonstrated that the intelligent system had higher uniformity of vegetation deposition and lower off-target spray losses than the conventional spray systems. Tests also demonstrated that the intelligent spray system was able to apply adequate spray deposition on multiple-row trees in the young apple orchard to improve application efficiency with reduced application times. (3) Field experiments at a winery with three different commercial grape cultivars illustrated 20-30% pesticide cost savings were achieved with the intelligent sprayer. (4) Field tests at a fruit farm for the third year demonstrated less or equal severity of pests between intelligent and conventional spray applications while the intelligent spray reduced pesticide use by 58.6%, 28.9%, 47.5% and 53.1% in average for apple, peach, blueberry and raspberry, respectively. (5) Third-year tests for two different intelligent sprayers at two ornamental nurseries showed the intelligent spray technology reduced pesticide use by 56.1% and 51.8% while achieving equivalent or greater insect and disease control in ornamental tree nurseries. (6) Quantifying and relating the effects of surface roughness and adjuvants on spray droplet retention and spreading was investigated to further increase spray delivery accuracy and reduce off-target losses for intelligent spray systems. (7) Tests of two retrofitted intelligent variable-rate sprayers in an experimental vineyard illustrated that the sprayers in the intelligent mode consumed only half of the spray volume and produced much less spray drift than the conventional mode. (8) The plant characterization accuracy was improved for the greenhouse intelligent spray system development. Clustering techniques were developed and evaluated to extract plant canopy information from point clouds generated by the laser sensor. The improvement made advances in better following true contour of a plant to improve volume estimates of plants that are pyramidal-, globe-, and vase-shaped. An airborne sensing platform was investigated by building a drone-based sensing platform for the intelligent spray operation in greenhouses. (9) A variable-rate and target-oriented intelligent spray control system was developed for greenhouse applications. Spray rates discharged were automatically adjusted according to the plant occurrence and sizes. Spray coverage inside canopies treated by the spray control system was consistent regardless of the canopy growth stages. The variable-rate spray system only consumed 21.3 to 89.3% of the spray volume compared to the constant-rate spray mode at different travel speeds. (10) A retrofittable premixing in-line injection system was designed and assembled as an attachment on a laser-guided intelligent orchard sprayer to eliminate tank mixture leftover problems. Preliminary tests demonstrated that the simulated pesticide and water could be accurately dispensed and discharged separately into the injection line and mixed well in the buffer tank before the spray mixture was delivered to the nozzles. This new system would have great potentials to further reduce pesticide wastes and improve environmental stewardships for conventional and precision variable-rate orchard sprayers. (11) A decision support system complying with weather stations was continuously evaluated in nursery, grape, blueberry and fruit farms in Ohio to manage pesticide spray application schedules to control diseases and pest insects. Information gathered from the individual insect pest and disease models was combined for future development of a consensus model for spray application recommendations to manage plant diseases and insect pests under complex and uncertain conditions. (12) Results from the techno-economic analysis based on studies conducted in apple orchards in Ohio illustrated intelligent sprayer reduced pesticide costs by 60-67%, pesticide application time by 27-32%, and labor and fuel by 28% compared to conventional sprayers. The payback time for using intelligent sprayer was estimated to be 1.1 and 3.8 years, respectively, for 4- and 20-hectare apple orchards in Ohio.

Publications

• Type: Journal Articles Status: Published Year Published: 2019 Citation: Chen, L., Wallhead, M., Zhu, H., and Fulcher, A. Control of insects and diseases with intelligent variable-rate sprayers in ornamental nurseries. Journal of Environmental Horticulture. 37(3): 90100. 2019. Yan, T., Zhu, H., Sun, L., Wang, X., and Ling, P. Investigation of an experimental laser sensor-guided spray control system for greenhouse variable-rate applications. Transactions of the ASABE. 62(4): 899-911. 2019. Zhang, Z., Zhu, H., Guler, H., and Shen, Y. Improved premixing in-line injection system for variable-rate orchard sprayers with Arduino platform. Computers and Electronics in Agriculture. 162: 389-396. 2019. Xiao, L., Zhu, H., Wallhead, M., Horst, L., Ling, P., and Krause, C. R. Characterization of biological pesticide deliveries through hydraulic nozzles. Transactions of the ASABE, 61(3): 897-908. 2018. Yan, T., Wang, X., Zhu, H., and Ling, P. Evaluation of object surface edge profiles detected with a 2-D laser scanning sensor. Sensors. 18(11): 1-17. 2019. Lin, J. and Zhu, H. Fading process of herbicidal droplets amended with emulsifiable spray adjuvants on cucurbitaceae leaves. Transactions of the ASABE. 61(6): 1881-1888. 2018. You, K., Zhu, H., and Abbott, J. Assessment of fluorescent dye Brilliant Sulfaflavine deposition on stainless steel screens as spray droplet collectors. Transactions of the ASABE. 62(2): 495-503. 2019. Lin, J-L., Zhu, H., and Ling, P. Amendment of herbicide spray solutions with adjuvants to modify droplet fading activities on weeds. Applied Engineering in Agriculture. 35(5): 713-721. 2019.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Fessler, L., A. Fulcher, J. Hines, H. Zhu, T. Hines, W. Wright, W. Yeary, X. Sun, and S. McClanahan. 2019. A dynamic laser-guided sprayer reduces pesticide use in large pot-in-pot production. HortScience, Issue 54. Fulcher, A., D.W. Lockwood, W. Wright, L. Fessler, W. Yeary, M. Burnett, H. Zhu, X. Sun, G. Pietsch and J. McHugh. 2019. Characterizing spray penetration of a novel sprayer into Malus domestica Golden Delicious apple trees at a commercial orchard. HortScience, Issue 54. Boatwright , H. and G. Schnabel 2019. Evaluation of laser-guided air blast sprayer on pest and disease control in peach orchards. Presentation at the annual southeastern fruit workers conference, November 2019, Tifton, Georgia. Warneke, B. W., Pscheidt, J. W., Rosetta, R. and Nackley, L. 2019. Out of the Box and Through the Rows: Intelligent Spray System Research at Oregon State University. Presentation at APS Pacific Division meeting. Pscheidt, J. W., Warneke, B. W., Rosetta, R. and Nackley, L. 2019. Efficacy of an intelligent sprayer on grape powdery mildew. Presentation at OWRI Grape Day. Warneke, B., Pscheidt, J.W., Rosetta, R., Nackley, L. 2019. Sensor sprayers for specialty crop production. Oregon State University, University of Idaho, and Washington State University. PNW 727. Zhu, H. . 2019. Laser-Guided Intelligent Sprayer Technology for Fruit Production at Orchard Pest Management and Intelligent Spraying Technologies. Presented at Penn State Fruit Research and Extension Workshop. Ozkan, E., and Zhu, H. 2019. An update on the intelligent spraying system development for fruit and nursery crop applications. 15th Workshop on Spray Application and Precision Technology in Fruit Growing. SuproFruit 2019. NIAB EMR. United Kingdom. Pp. 35-37. 12 presentations at 2019 ASABE Annual International Meeting in Boston, Massachusetts: Guler, H., H. Zhu, K. You, Z. Zhang, JP. Abbott, S. Cui and E. Ozkan. 2019. Evaluation of spray deposition and off-target loss in apple orchard with an air-blast sprayer retrofitted with intelligent spray control system. You, K., H. Zhu, H. Guler, Z. Zhang, JP. Abbott, and S. Cui. 2019. Spray deposition and coverage on nursery trees with laser-guided variable-rate spray application. Zhang, Z., Zhu, H., and Hu, C. 2019. Integration of premixing in-line injection system into variable-rate orchard spraying systems. Abbott, J. and Zhu, H. Effects of maize leaf aging on sprayed droplet impact and adhesion. Zhang, Z., Zhu, H., and Hu, C. 2019. Assessments of premixing in-line injection system retrofitting on variable-rate orchard sprayers. Abbott, J. and Zhu, H. 2019. Droplet impact and adhesion as related to quantified industry surface roughness parameters. Abbott, J. and Zhu, H. 2019. Interactions of hairy trichomes with sprayed droplet adhesion and spreading on leaves. Chen, L., H. Zhu, M. Wallhead, A. Fulcher. 2019. Control of insects and diseases with intelligent variable-rate sprayers in ornamental nurseries. You, K., H. Zhu, H. Guler, Z. Zhang, L. Chen, T. Yan, E. Ozkan, L. Zhao. 2019. Evaluation of airborne spray drift and ground loss from laser-guided variable-rate spray applications. Yan, T., H. Zhu, X. Wang, P. Ling. 2019. Development of a laser-guided boom spray system for greenhouse applications. Guler, H., H. Zhu, K. You, Z. Zhang, L. Chen, T. Yan and E. Ozkan. 2019. Spray performance comparisons between retrofitted intelligent sprayers and conventional constant-rate sprayers in vineyard applications. Chen, L., H. Zhu, M. Wallhead, M. Reding and L. Horst. 2019. Evaluation of laser-guided intelligent sprayer to control insects and diseases in fruit plants.
• Type: Websites Status: Published Year Published: 2019 Citation: Precision Spray Application Research at Oregon State University website: https://horticulture.oregonstate.edu/nursery/precision-spray-applications Maple Spider Mite. Pacific Northwest Nursery IPM at Oregon State University website: http://oregonstate.edu/dept/nurspest/maple_spider_mite.html Intelligent Spray Control Systems at Smart Guided Systems website: https://www.smartguided.com/intelligent-sprayer

Progress 09/01/17 to 08/31/18

Outputs
Target Audience:Target audiences are growers, farm managers, and sprayer applicators (including Hispanic and African American growers and workers) of specialty crops (nursery, peach orchard, apple orchard, pecan orchard, citrus, grape, winery, blueberry, raspberry, cranberry, nuts and greenhouse crops), extension specialists and educators, county agents, researchers, undergraduate and graduate students, agricultural industry consultants, commercial diagnosticians, general public, sprayer manufacturers, chemical companies, national and state legislators, and environmental protection agency regulators. Efforts were made through on-farm field demonstrations, extension workshops and field days, pesticide applicator training and licensing programs, trade shows, trade magazines, newsletters, scientific journal articles, and regional, national and international conferences. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Professional development trainings in using the intelligent spray technology were provided for growers, farm managers, spray applicators and engineers in Blankenship Farms and Nursery in Tennessee, Hale and Hines Nursery in Tennessee, Wooden's Apple House in Tennessee, Hans Nelson & Sons Nurseries in Oregon, J. Frank Schmidt & Son Co. in Oregon, Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio, OARDC Horticulture Field in Ohio, Five R Enterprises pecan farm in Texas, Clemson University Musser Fruit Research Farm, Oregon State University Research Farm, University of Queensland, and Smart Guided Systems. These growers, farm managers and spray applicators as well as local extension educators gained first-hand experience in advancing conventional sprayers to the intelligent spray technology based on the sprayer types and functions as well as engineers to prepare for commercialization of the intelligent sprayer technology. Undergraduate students, graduate students and post-doctoral fellows at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University and USDA-ARS were trained in research methodologies in development of intelligent spray technologies. Six summer interns were trained through the intelligent spray research activities and field trials in Ohio, Oregon and Tennessee. Undergraduate students in Nursery Production at Oregon State University were introduced to the research and potential impacts of intelligent spray systems. These students and post-doctoral fellows learned about the pesticide sprayer technologies applicable to different orchard types, pesticide application procedure and schedule, and resources required for spraying pesticides in the orchards and their cost. One Post-doc research associate trained at USDA-ARS became a faculty member at University of Maine. How have the results been disseminated to communities of interest?Presentations and field demonstrations on new intelligent sprayer technologies were given at Community Open House in Oregon, Farwest Show and Seminars in Oregon, Oregon State University 150 Celebration, The Promise and the Peril of Artificial Intelligence and Robotics of OSU in Oregon, 21st Ornamental Workshop on Insects and Diseases in North Carolina, Clackamas Basin Tech Advisory Group in Oregon, Willamette Valley Viticulture Tech Group meeting in Oregon, 13th Annual Cranberry Production Workshop in Oregon, Willamette Valley Viticulture Tech Group meeting in Oregon, University of California Nursery & Floriculture Alliance 2018 Pest Management Symposium, Western Disease Conference in Oregon, 77th Annual Pacific Northwest Insect Management Conference in Oregon, OSU Hazelnut IPM Workshop in Oregon, Nut Growers Summer Tour in Oregon, J. Frank Schmidt & Sons staff meetings, AgDay in Tennessee, UT/TSU Western Region Extension Agent In-Service, Southern Region Small Fruits Consortium In-service Training for Extension Agents from 6 states, Tennessee Fruit and Vegetable Association Annual Meeting, Tennessee Farm Winegrowers Alliance Annual Meeting, University of Tennessee Plant Sciences Course PS115, Tennessee Green Industry Day, National Association of County Ag Agents in Tennessee, Turf and Ornamental Field Day in Tennessee, AmericanHort's Production Technology Conference, Cultivate'18 in Ohio, IPPS Area Meeting & Tour in Ohio, 2018 Ohio Grape and Wine Conference in Ohio, the Ohio Blueberry, Bramble and Wine Grape Field Night, 2018 Midwest Green Industry Xperience (MGIX) Show in Ohio, Ohio Recertification Conferences for Commercial Pesticide Applicators, Ohio Annual Fruit and Vegetable Growers Conference, Annual Hops Growers Conference, In-service training for Extension Educators, 2018 ASABE Meeting, ASHS Conference, the International Conference of Plant Pathology, Plant Health in a Global Economy, Pesticide Application Technology and Modeling Workshop, EuroAgEng Conference in Netherlands, and Cortona in Italy. The research results on the intelligent spray technology reached communities of interest including specialty crop growers, farm managers, industries, chemical companies, sprayer manufacturers, students, researchers, educators, ag consultants, legislators, environmental policy regulators, water quality providers, and public through presentations, workshops, field demonstrations, trade shows, meetings and consultations, peer reviewed journal articles, and press articles in trade magazines and newsletters, website, and also through on-farm tests of intelligent spray prototype systems in nurseries, apple orchards, peach orchards, pecan orchards, vineyards, and small-fruit farms in Ohio, Oregon, Tennessee, South Carolina and Texas. The Ohio State University team received 2018 The Ohio State University CFAES Innovator of the Year Award for participation in the development the intelligent sprayer technology. What do you plan to do during the next reporting period to accomplish the goals?Spray deposition and coverage, spray volume consumption, pesticide cost savings, and biological efficacy will be continuously investigated for growers' existing sprayers retrofitted with the universal intelligent spray control systems in Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klyn Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio; Hans Nelson & Sons Nurseries in Oregon, J Frank Schmidt Nurseries in Oregon, Hale & Hines Nursery in Tennessee, Wooden's Apple House in Tennessee, Five R Enterprises Pecan Farm in Texas, Silverado Farming in California, Clemson University Musser Fruit Research Farm, Oregon State University Botany Plant Pathology Farm, The Ohio State University OARDC Horticulture Field, University of Tennessee Plant Sciences Experiment Station, and University of Queensland in Australia. Crops will be apples, peaches, grapes, blueberries, raspberries, pecans, hazelnuts, and different species and varieties of ornamental nursery stocks. Pests will be historical and emerging insects and diseases. Comparison tests will be conducted for the sprayers with and without the automatic intelligent control functions to optimize the intelligent sprayer parameters. In addition, the tests will include investigating effects of sprayer type on beneficial insect population, and effects of tree phenology and tree age on pesticide consumption and spray characteristics from intelligent and conventional spray applications on apples and peaches at Wooden's Apple House in Tennessee. Validation of the intelligent greenhouse spray system accuracy will be continued in a commercial greenhouse (Casa Verde Growers in Ohio). The spray system will be validated for its accuracy to detect the presence, size, shape, and foliage density of different plants and then discharge desired amounts of sprays from each nozzle as needed in real time. Improvement of techno-economic models, spray deposition and drift prediction models, and pest management expert decision models will be continued for different specialty crops. The SAAS program will be further validated for its reliability and validity to be used in a wide range of pesticide application scenarios, and will be integrated with the intelligent sprayer control system as an expert system to make the intelligent sprayer more precisely controlled. It will also be distributed as forms of stand-alone software so that farmers and extension agencies can evaluate spray drift problems and adjust spray settings to improve the application performance according to weather and crop conditions. Research results will be continuously dismissed to communities of interest, commodity stakeholders and public through workshops, on-farm field demonstrations, trade magazines, trade shows, extension education events, professional meetings, and scientific journals.

Impacts
What was accomplished under these goals? In Tennessee: (1) Powdery mildew control and spray application characterization trials were conducted in a commercial nursery with the intelligent sprayer. Test data showed 54% reduction in pesticide consumption with no reduction in tree growth and powdery mildew control compared to a conventional airblast sprayer. The intelligent sprayer reduced pesticide cost by 66% compared to the conventional sprayer. Spray time was reduced by approximately 50% just due to spraying from both sides of the sprayer compared to the conventional sprayer, which in this case one sprayed from one side. Drift coverage was reduced 63.5% by using the intelligent sprayer. The test site was at a nursery in close proximity to an elementary school and a frequently traveled road. Therefore, environmental quality was improved for not only the nursery but also the adults and children in the vicinity. (2) Spray rate trials were conducted with an intelligent sprayer in the apple orchard. One of four rates, 0.03, 0.05, 0.07, or 0.09 fl oz/ft3, was randomly assigned to each pair of trees within the row so that all four rates were tested on each run. Coverage from the highest two rates did not differ but both had greater coverage than the 0.05 fl oz/ft3 rate, which had greater coverage than the lowest rate. As the distance from the sprayer increased, coverage decreased and droplet density increased. Applications at all rates and all card positions met or exceeded the recommended guidelines for insecticides and fungicides. A spray rate of 0.03 fl oz/ft3 applied by a laser guided sprayer met or exceeded suggested guidelines while using less pesticide than more common, higher rates. (3) Spray volume reductions and pest control trials with the intelligent and conventional sprayers were evaluated in two commercial nurseries. Using the intelligent sprayer reduced spray volume by 30% although trees in the intelligent plot had a 70% greater tree row volume than those in the conventionally sprayed plot. Oak fungal diseases were within 1.5% of one another in the 2 plots. In Oregon: Two conventional air-blast sprayers were retrofitted with the universal intelligent spray system, one was used in a research vineyard and the other one was used in a commercial nursery. The intelligent and conventional applications resulted in similar spray coverage in vineyards, hazelnut fields and nursery fields. In Texas: A 1000-gallon air-assisted pecan orchard sprayer was retrofitted with the universal intelligent spray system. Spray deposition coverage was s between the intelligent and conventional spray modes with spraying zinc, manganese and copper solutions in the commercial pecan orchard in Texas. Leaf samples were collected for nutrient analyses. Pecan yields were also compared for the two spray modes. In South Carolina: Durability of the intelligent spray system that was retrofitted on an air-assisted peach orchard sprayer was tested at Titan Farm in South Carolina. The original display touch screen could not withstand the South Carolina heat and was fixed with a different type, more heat resistant screen. A modified intelligent spray system was installed on another air-assisted peach orchard sprayer used in the Clemson University Musser Fruit Research Farm for experiments in the 2019 season. Preliminary trials were conducted for establishing future test standards in assessment of spray deposition quality and drift potentials in peach orchards with the sprayer operated in both intelligent and conventional modes. In Ohio: (1) A universal intelligent spray control system was modified as a retrofit kit for conventional orchard sprayers. The retrofit kit was mounted on nine growers' sprayers used in nurseries, fruit and nut orchards, and vineyards in Ohio, Oregon, Tennessee, South Carolina, Texas and Australia. With the retrofit, these conventional sprayers were upgraded to perform intelligent functions in controlling spray outputs to match canopy presence, size and leaf density in real time. Total seventeen sprayers equipped with the intelligent spray technology were on-farm tests for their efficacy, efficiency and reliability. (2) Field experiments were conducted at a commercial vineyard to compare performances between the intelligent and conventional spray applications. Comparison assessments included spray deposition coverage, leaf chlorophyll content level, grape juice quality, disease rating and Japanese beetle damage. Three different commercial grape cultivars were selected in this experiment, representing American, French-American hybrid, and European grape types, respectively. (3) Comparative experiments of intelligent and conventional sprays for pest control were conducted at a fruit farm and three nurseries. There were no differences in severities of pests in the fruit farm for intelligent and conventional sprays. There was no difference in disease severity of apple scab for intelligent and conventional spray in crabapple trees and less severity for intelligent spray in apple trees. Severity of powdery mildew was less or equal for intelligent spray compared to conventional spray in dogwood and sycamore. Compared to conventional spray, there were equal or fewer numbers of leafhoppers in maple trees and aphids in birch trees for intelligent spray. These results suggested that intelligent spray was equally or more effective for control of insect and disease pests in the orchard and nurseries compared to conventional constant-rate spray. (4) Potential adaptations of an inexpensive indoor-use laser scanning sensor to measure complex-shaped plants were analyzed for future development of automatic spray systems to achieve variable-rate functions in greenhouse applications. Consequently, an experimental laser-guided intelligent spray system for greenhouse applications was developed to control real-time spray outputs with variable rates based on the presence and plant canopy structures. Tests were conducted to validate the control system accuracies in spray delay time, spray volume and spray activation by single and group of objects under both laboratory and greenhouse conditions. (5) A universal model tool, SAAS, for predicting spray deposition and drift from pesticide applications using air-assisted sprayers has been developed. The tool was designed for pesticide applicators to preliminarily examine the efficiency and potential drift of a spray application under specific conditions including crop type, growth stage, tractor speed, nozzle type, ambient wind speed, air temperature, and relative humidity. (6) A decision support system complying with weather stations was evaluated in seven nursery, grape and fruit farms in Ohio to manage pesticide spray application schedules to control diseases and pest insects. Information gathered from the individual insect pest and disease models was combined for future development of a consensus model for spray application recommendations to manage plant diseases and insect pests under complex and uncertain conditions. (7) A preliminary techno-economic analysis (TEA) model was developed to evaluate the technical feasibility and economic impacts of pesticide application for nursery crop production using conventional and intelligent sprayers. Data on pesticide application schedule, pesticide spraying time, and pesticide cost were collected from growers for the model development. Based on the available data, intelligent sprayer could considerably reduce pesticide requirements, number of sprayer refills, spraying time and resources requirements. For nurseries with area of 10 to 200 acres, cost savings of ~ $245 - $446/acre could be achieved with retrofitted intelligent sprayer, with a payback period of 2-5 years.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Fulcher, A., D. Lockwood, W. Wright, H. Zhu, M. Burnett, L. Smith, J. McHugh, and G. Pietsch. 2018. Characterizing spray penetration of a novel sprayer into Malus domestica Golden Delicious apple trees at a commercial orchard. HortScience 53S. Fulcher, A., J. McHugh, H. Zhu, R. Collier, W. Wright, and W. Yeary. 2018. Powdery mildew control and spray application characteristics of a laser-guided sprayer. HortScience 53S. Hong, S., Zhao, L.Y., and Zhu, H. 2018. SAAS, A model tool for predicting spray drift from air-assisted sprayers. Presentation at 2018 ASABE Annual International Meeting, Detroit, MI. July 29th to Aug. 1st, 2018. Hong, S., Zhao, L.Y., and Zhu, H. 2018. SAAS, A model tool for predicting spray drift from air-assisted sprayers. Presentation at 2018 Pesticide Application Technology and Modeling Workshop, Detroit, MI. July 29th, 2018. Manandhar, A., Shah, A., Zhu, H., Ozkan, E. 2018. Techno-economic analysis of using a conventional sprayer retrofitted with intelligent control functions for pesticide application in nursery crops. Presentation at 2018 ASABE Annual International Meeting, July 29-August 1, 2018, Detroit, MI. Manandhar, A., Zhu, H., Ozkan, E. and Shah, A. 2018. Evaluating techno-economic impacts of using conventional sprayer retrofitted with intelligent control functions for pesticide application in apple orchards. Presented at: Plant Sciences Symposium at The Ohio State University 2018, April 6-7, Wooster, OH. and CFAES Annual Research Conference at The Ohio State University 2018, April 27, Wooster, OH. (Poster) Robin Rosetta, Lloyd Nackley, Jay Pscheidt, Heping Zhu. 2018. Preliminary Evaluation of Intelligent System Retrofit Sprayer in Nursery Production. Reports from the 77th Annual Pacific Northwest Insect Management Conference. Portland, OR. p. 71-72. http://ipmnet.org/PNWIMC/Proceedings_and_Agenda_2018.pdf Shaoqing Cui, Elvia Adriana, Alfaro Inocente, Heping Zhu, Nuris Acosta, Peter. P. Ling, Harold. M. Keener. 2018. Development of portable E-nose system for early diagnosis of insect-stressed tomato plants. ASABE Paper No. 1800990. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Tingting Yan, Heping Zhu, Li Sun, Xiaochan Wang, Peter Ling. 2018. Detection of 3-D objects with a 2-D laser scanning sensor for greenhouse applications. ASABE Paper No. 1800179. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Tingting Yan, Heping Zhu, Li Sun, Xiaochan Wang, Peter Ling. 2018. Evaluation of spray accuracy for an experimental greenhouse variable-rate spray system. ASABE Paper No. 1800183. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Zhihong Zhang, Heping Zhu, Huseyin Guler, Yue Shen. 2018. Developing of Premixing Inline Injection System for Agricultural Sprayers Based on Arduino and Its Performance Evaluation. ASABE Paper No. 1800399. (American Society Agricultural and Biological Engineers, St. Joseph, MI 49085). Zhu, H., J. Boldt, A. Fulcher, Y. Gao, D. A. Herms, C. Krause, P. Ling, D. Lockwood, G. Niu, E. Ozkan, J. Pscheidt, R. Rosetta, G. Schnabel, A. Shah, L. Zhao, R. Zondag. 2018. Laser-guided Variable-rate Pesticide Spray Technology for Specialty Crop Production. EuroAgEng Conference 2018. Page 176. Zhu, H., A. Fulcher, R. Rosetta and M. Wallhead. 2018. Advanced precision spray application technology for effective control of ornamental diseases. at the International Conference of Plant Pathology, Plant Health in a Global Economy held in Boston, 29-Jul-3-Aug 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Zhao, L. 2017. Reducing pesticide spray drift using a universal computational model. Ohios Country Journal. Sep. 11, 2017. http://ocj.com/2017/09/reducing-pesticide-spray-drift-using-a-universal-computational-model/
• Type: Websites Status: Published Year Published: 2018 Citation: http://oregonstate.edu/dept/nurspest/maple_spider_mite.html
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Cui, S., Ling, P., Zhu, H., and Keener, H. M. Plant pest detection using artificial nose system: a review. Sensors, 18(2): 378-396. 2018. Hong, S.W., Zhao, L. and Zhu, H., 2018. SAAS, a computer program for estimating pesticide spray efficiency and drift of air-assisted pesticide applications. Computers and Electronics in Agriculture.155:58-68. https://doi.org/10.1016/j.compag.2018.09.031 Hong, S.W., Zhao, L. and Zhu, H., 2018. CFD simulation of pesticide spray from air-assisted sprayers in an apple orchard: Tree deposition and off-target losses. Atmospheric Environment. 175:109-119. https://doi.org/10.1016/j.atmosenv.2017.12.001 Hong, S.W., Zhao, L. and Zhu, H., 2018. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers. Computers and Electronics in Agriculture. 149: 121-132. https://doi.org/10.1016/j.compag.2017.07.011 Shen, Y., Zhu, H., Liu, H., Chen, Y., and Ozkan, E. Development of a laser-guided embedded-computer-controlled air-assisted precision sprayer. Transactions of the ASABE, 60(6): 1827-1838. 2017. Silva, J. E., Zhu, H., and Cunha, J. P. A. R. Spray outputs from a variable-rate sprayer manipulated with PWM solenoid valves. Applied Engineering in Agriculture, 34(3): 527-534. 2018. Wallhead, M., and Zhu, H. Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review. Journal of Environmental Horticulture, 35(2): 84-92. 2017. Wallhead, M., and Zhu, H., and Broders, K. Hyperspectral evaluation of Venturia inaequalis Management using the disease predictive model RIMpro in the Northeastern U.S. Agricultural Sciences, 8: 1358-1371. 2017. Yan, T., Zhu, H., Sun, L., Wang, X. and Ling, P., 2018. Detection of 3-D objects with a 2-D laser scanning sensor for greenhouse spray applications. Computers and Electronics in Agriculture, 152, 363-374. Yeary, W., Fulcher, A., Zhu, H., Klingeman, W., and Grant, J. Spray penetration and natural enemy survival in dense and sparse plant canopies treated with carbaryl: implications for conventional and biological control. Journal of Environmental Horticulture, 36(1): 21-29. 2018.

Progress 09/01/16 to 08/31/17

Outputs
Target Audience:Target audiences are growers, farm managers and sprayer applicators (including Hispanic or Latino growers) of specialty crops (ornamental nursery, peach orchard, apple orchard, citrus, grape, winery, blueberry, raspberry, nuts and greenhouse crops), extension specialists and educators, researchers, undergraduate and graduate students, agricultural industry consultants, general public, sprayer manufacturers, chemical companies, national and state legislators, and environmental protection agency regulators. Efforts were made through on-farm field demonstrations, extension workshops and field days, pesticide applicator training and licensing programs, trade shows, trade magazines, scientific journal articles, and regional, national and international conferences. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Professional development trainings in using the intelligent spray technology were provided for growers, farm managers and spray applicators in Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klyn Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio, J Frank Schmidt Nurseries in Oregon, Hans Nelson & Sons Nurseries in Oregon, Pleasant Cove Nurseries in Tennessee, Wooden's Apple House in Tennessee, Hale&Hines Nursery in Tennessee, Titan Farm in South Carolina, Constellation Brands in California and Silverado Farming in Napa Valley California. These growers, farm managers and spray applicators as well as local extension educators gained first-hand experience in advancing conventional sprayers to the intelligent spray technology based on the sprayer types and functions. Undergraduate students, graduate students and post-doctoral fellows at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University and USDA-ARS were trained in research methodologies in development of intelligent spray technologies. Five summer interns were trained through the intelligent spray research activities and field trials in Ohio, Oregon and Tennessee. How have the results been disseminated to communities of interest?Research results have been disseminated to communities of interest through presentations, workshops, field demonstrations, trade shows, trade magazines, meetings and consultations with growers, each specialty crop management company personnel, commodity trade associations, local county extension agents; through collaborations with researchers, extension specialists, farm managers and spray applicators; through on-farm tests of intelligent spray prototype systems in ornamental nurseries, apple orchards, peach orchards, vineyards, and small-fruit farms in Ohio, Oregon, Tennessee, South Carolina and California; through publications of research articles in scientific journals. Presentations on new intelligent sprayer technologies were given in Kentucky Fruit & Vegetable Meeting, Southeastern Apple Meeting, North GA Apple Meeting, Pick TN Conference, Tennessee Green Industry Field Day, Turf and Ornamental Field Day, Shade Tree Growers Mtg., Ag Day 2017 in Tennessee, Oregon State Board of Agriculture, Napa Valley Wine Growers, California Lodi Wine Growers, J. Frank Schmidt & Sons staff meetings, 2017 Congressional Specialty Crop Committee Meeting, Cultivate'17 Workshop, 2017 Florida Citrus Show, The Ohio State University Extension Orchard Sprayer Technology Field Day, Wayne Economic Development Council, 2017 ASABE Meeting, 2017 Midwest Green Industry Xperience (MGIX) Show, 2017 Farwest Show, 2017 ASHS Conference, the OPGMA Congress, Ohio Berry and Wine Grape Workshop, and Ohio Berry and Wine Grape Field Night in 2017. A press article on the intelligent spray technology with drift reduction models was published in the Ohio's Country Journal to reach more than 25,000 farmers. Field demonstrations of the intelligent sprayer technology were given specifically to engineers and product development managers of sprayer managers, chemical company representatives, Wayne Economic Development Council board members, researchers, extension educators, students, growers and farm managers who attended the Ohio State University Extension Orchard Sprayer Technology Field Day, and over 110 attendees of Cultivate'17 Workshop. What do you plan to do during the next reporting period to accomplish the goals?Spray deposition and coverage, spray volume consumption, pesticide cost, and biological efficacy will be evaluated for growers' existing sprayers retrofitted with the universal intelligent spray control systems in Willoway Nurseries in Ohio, Herman Losely & Son Nurseries in Ohio, Klyn Nurseries in Ohio, Klinshirn Winery in Ohio, Moreland Fruit Farm in Ohio, J Frank Schmidt Nurseries in Oregon, Hans Nelson & Sons Nurseries in Oregon, Pleasant Cove Nurseries in Tennessee, Hale & Hines Nursery in Tennessee, Wooden's Apple House in Tennessee, Titan Farm in South Carolina, Five R Enterprises in Texas, and Silverado Farming in California. Crops will be apples, peaches, grapes, blueberries, raspberries, pecans, and different species and varieties of ornamental nursery stocks. Comparison tests will be conducted for the sprayers with and without the automatic intelligent control functions. In addition, the tests will include comparisons with the Smartsprayer which has been used at Titan Farms, and assess the effect of sprayer type on beneficial insect population. Design of an intelligent greenhouse spray system will be completed and tested. The spray system will integrate an in-door use laser scanning sensor with the intelligent spray control system. The spray system will be validated for its accuracy to detect plant presence, size, shape, and foliage density of different plants and then discharge the desired amounts of sprays from each nozzle in real time. Improvement of techno-economic models, spray deposition and drift prediction models, and pest management expert decision models will be continued for different specialty crops. Research results will be continuously dismissed to communities of interest, commodity stakeholders and public through workshops, on-farm field demonstrations, trade magazines, trade shows, extension education events, professional meetings, and scientific journals.

Impacts
What was accomplished under these goals? The efficacy of intelligent sprayers were evaluated in five specialty crop farms in Ohio in the 2017 growing season. One location was Moreland Fruit Farm in Wooster, Ohio for evaluation of the intelligent sprayer effectiveness to manage insect pests and diseases of apple, black raspberry, blueberry and peach. The second location was Willoway Nurseries in Avon, Ohio for managing insect pests and diseases of birch, crabapple and maple. The third location was Herman Losely and Son Nursery in Perry, Ohio for birch, crabapple and fruiting apple, dogwood and maple. The fourth location was Klyn Nursery located in Perry, Ohio for amelanchier, birch, crabapple, dogwood, maple and sycamore. The fifth location was at Klingshirn Winery in Avon Lake, Ohio, and pest and disease control with the intelligent sprayer was evaluated with three grape cultivars of American Concord, European Riesling, and hybrids Vidal. The same sprayers with the intelligent spray functions disabled were also tested for comparison. In addition, spray coverage tests for the intelligent sprayers with and without intelligent spray functions were conducted at these five farms. Unmanned aerial systems were evaluated to identify and quantify diseases and insect pest infestations in the test fields. Four decision support systems, which were originally used for managing diseases and pest insects in orchards, were evaluated in 17 locations across Ohio for development of a consensus expert decision model that would combine the information generated from the individual models into a single spray recommendation for specialty crops. Laser scanning sensors and imaging sensors were investigated for development of intelligent spray systems used in greenhouses. The sensors were tested for their accuracy to characterize sizes and shapes of regular shaped objects and artificial plants. A prototype of laser-guarded intelligent spray system was designed for greenhouse tests. The efficacy and spray coverage of an experimental intelligent sprayer were investigated in Pleasant Cove Nursery in McMinnville, Tennessee in 2016 and 2017 growing seasons. Test results from the 2016 season in Tennessee were analyzed and demonstrated pesticide usage reduction with the intelligent sprayer reached 56.1% with no reduction in powdery mildew control compared to a conventional air-blast sprayer. The test site was at a nursery in close proximity to an elementary school and a frequently traveled road. Therefore, environmental quality was improved with the intelligent spray technology for not only the nursery but also the adults and children in the vicinity. In addition, plant height and caliper growth during the growing season were not affected by sprayer type. There was no effect of sprayer type on powdery mildew severity on the average of the three leaf pair ratings or overall tree rating while the intelligent sprayer reduced pesticide cost by 51% and spray time by approximately 50%. An experimental intelligent sprayer was tested for its efficacy and reliability in Hans Nelson & Sons Nurseries in Oregon. A conventional Mini-Pac air-blast sprayer was retrofitted with the universal intelligent spray system, and experiments were conducted in the commercial nursery of J. Frank Schmidt and Son Co. in Oregon. Pesticide delivery accuracy of the retrofitted sprayer was evaluated with water sensitive papers to measure spray coverage and deposition with and without the intelligent spray system activated. The experiment was conducted in a field of 'Royal Raindrops' Crabapple. Row of trees were blocked into either 'on' or 'off' treatment groups, indicating whether or not the Mini-Pac blast sprayer was controlled by the intelligent spray system (on) or run without it (off). Spray coverage and droplet sizes on the water sensitive cards from the trial were analyzed. A spray drift model was developed to help pesticide applicators to choose the most efficient application practices with minimum environmental impact under complex specialty crop field conditions. The computer simulation complied with calculated trajectories of billions of pesticide droplets from their release to the final destinations under 15,000 different conditions. The developed Universal Orchard Spray Drift Prediction program provides an estimation of the fate of pesticide spray droplets within and beyond the intended target orchard according to the sprayer type and nozzles, crop species and their growth stages, tractor speed, and weather conditions. The program will be distributed as forms of stand-alone software so that farmers and extension educators can evaluate spray drift problems and adjust spray settings to improve the application performance under different weather and crop conditions. A preliminary techno-economic analysis (TEA) model was developed to analyze the technical feasibility and economic impacts of the intelligent sprayers compared to the conventional sprayers. The model accounts for increased cost due to sprayer retrofitting, and reduced cost for lower quantities of pesticides, number of tank mixture refills, total spraying time, tractor fuel consumption, and labor hour requirements. Data collected for the preliminary TEA model development included pesticide application schedule, spray time, and cost. These information were obtained from the growers. In addition, information on productivity of different spray equipment was obtained from the literature review as well as interview of growers. Based on the preliminary analysis, the intelligent sprayers considerably reduced pesticide consumption, number of tank refills, spraying time and resources requirements. For an apple orchard with 10 to 100 acres, cost savings of approximately $400 - $570/acre was obtained with retrofitted intelligent pesticide sprayers. Payback time for the cost of retrofitting the conventional sprayer with the intelligent spray control system was 4 years for 10 acre orchard and 1 year for 100 acre orchard.

Publications

• Type: Journal Articles Status: Published Year Published: 2017 Citation: Hong, S.W., Zhao, L., Zhu, H. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers. Computers and Electronics in Agriculture. 2017. (Online available at https://doi.org/10.1016/j.compag.2017.07.011) Liu, H., Zhu, H. Evaluation of a laser scanning sensor on detection of complex shaped targets for variable-rate sprayer development. Transactions of the ASABE, 59(5): 1181-1192. 2016. Zhu, H., Liu, H., Shen, Y., and Zondag, R. H. Spray deposition inside multiple-row nursery trees with a laser-guided sprayer. Journal of Environmental Horticulture, 35(1): 13-23. 2017. Zhu, H., Rosetta, R., Reding, M. E., Zondag, R. H., Ranger, C. M., Canas, L., Fulcher, A., Derksen, R. C., Ozkan, H. E., Krause, C. R. Validation of a Laser-Guided Variable Rate Sprayer for Managing Insects in Ornamental Nurseries. Transactions of the ASABE. Vol. 60(2): 337-345. 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Fulcher, A., J. McHugh, R. Collier, H. Zhu, W. Yeary, W. Wright, S. Xiaocun, F. Collier, and D.W. Lockwood. Evaluating variable-rate, laser-guided sprayer performance and powdery mildew control in Cornus florida 'Cherokee Princess'. HortScience 52S. 2017. Hong, S.W., Zhao, L., Zhu, H., 2017. CFD simulations of fate and transport of pesticide droplets discharged from air-assisted sprayers in orchards. The ASABE Annual International Meeting, Spokane, Washington, July 16-19, 2017. Hong, S.W., Zhao, L., Zhu, H., 2017. A Universal Spray Drift Model for estimating spray efficacy and off-target drifts from orchard spray applications. The ASABE Annual International Meeting, Spokane, Washington, July 16-19, 2017. Hong, S.W., Zhao, L., Zhu, H., 2017. CFD simulations of fate and transport of pesticides droplets discharged from air-assisted sprayers in orchards. OARDC (Ohio Agricultural Research and Development Center) Poster Award, Columbus, Ohio, April 20, 2017. Hong, S.W., Zhao, L., Zhu, H., 2017. CFD simulations of fate and transport of pesticide droplets discharged from air-assisted sprayers in orchards. OSC (Ohio Supercomputer Center) Statewide Users Group Conference, Columbus, Ohio, April 6, 2017. Manandhar, A., Shah, A., Zhu, H., Ozkan, E. Techno-economic analysis of implementing the intelligent pesticide sprayer for specialty crop production. 2017 ASABE Annual International Meeting, July 18, 2017, Spokane, WA. 2017. Zhao, 2017. Reducing pesticide spray drift using a universal computational model. Ohios Country Journal, September 11, 2017. (Online available at http://ocj.com/2017/09/reducing-pesticide-spray-drift-using-a-universal-computational-model/) Zhu, H., Boldt, J., Fulcher, A., Gao, Y., Herms, D. A., Krause, C. R., Ling, P., Lockwood, D., Niu, G., Ozkan, E., Pscheidt, J., Rosetta, R., Schnabel, G., Shah, A., Zhao, L., Zondag, R. H. Advancement of Laser-guided Intelligent Pesticide Spray Control Technology in Specialty Crop Production. Abstract. ASHS. Hawaii. 2017. Zhu, H., Li, Y., Shen, Y., Liu, H. Versatile Laser-guided Spray Control System to Implement Variable-rate Functions for Conventional Air-blast Sprayers. The ASABE Annual International Meeting, Spokane, Washington, July 16-19, 2017.

Progress 09/01/15 to 08/31/16

Outputs
Target Audience:Target audiences are growers and farm managers of specialty crops (including ornamental nurseries, orchards, grapes, small fruit production, nuts and greenhouse crops), extension educators, researchers, sprayer manufacturers, chemical companies, national and state legislators, and environmental protection agency regulators. Efforts were made through on-farm demonstrations, extension workshops and field days, pesticide applicator training and licensing programs, trade shows, and regional, national and international conferences. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Professional development activities included presentations of the research outcomes at the 2015 IPM Strategies Workshop organized by North Central Extension & Research Activity, American Hort and HRI executive board member meeting, 2015 Annual Conference of the California Citrus Nursery Society, the 2016 CENTS Show, 2016 California NAPA Valley Grapegrowers Association workshops, the Academy of Crop Production in Georgia, the Annual Swedish Agricultural Fair in Sweden, the 2016 CIGR meeting in Denmark, the American Hort Cultivate'16, The Ohio State University Extension Orchard Sprayer Technology Field Day, and the 2016 Farwest Show in Oregon. Consulted by a Horticultural Research Institute writer for an article featuring the intelligent sprayer technologies. How have the results been disseminated to communities of interest?The results of this research were disseminated through direct interactions with growers during on-farm tests and through field demonstration events, state pesticide safety education coordinators and extension agents/educators, state, regional and national industry educational events, and trade shows such as such as CENTS, AmericanHort Cultivate, Tennessee Green Industry Expo, Tennessee Fruit and Vegetable Association Meeting, Farwest Show, etc. What do you plan to do during the next reporting period to accomplish the goals?Conventional sprayers retrofitted with the universal intelligent spray control system will be tested in nurseries, apple orchards, vineyards and blueberry fields. Spray deposition quality inside canopies and off-target losses will be quantified and compared for the sprayers with and without automatic control functions. An automatic greenhouse spray system will be designed with the intelligent-decision spraying system attached to existing watering booms. An in-door use laser scanning sensor will be used in the intelligent spray control system. The laser sensor will be validated for its accuracy to detect plant presence, size, shape, and foliage density for different plants with different planting patterns. Based on laser sensor detection data, a computer programs will be written to determine the canopy volume and foliage density and then calculate the amount of water and chemical needed for each nozzle to discharge. Expert system will be developed including insect and disease prediction models for making decisions on when spray applications should be executed. A computer program will also be developed to predict spray drift potentials for the field sprayers retrofitted with and without the intelligent spray control system.

Impacts
What was accomplished under these goals? A sophisticated strategy was developed to integrate intelligent spray control functions onto conventional sprayers based on the success of previous intelligent sprayer development. The critical component of the strategy was the versatile algorithm that was able to comply with a high-speed laser scanning sensor, a non-contact Doppler radar travel speed sensor, a custom-designed nozzle flow rate controller, and an embedded computer to control outputs of individual nozzles on conventional air-assisted sprayers. A computer program was written for the algorithm to determine the presence of a tree canopy, map the canopy structure, estimate the foliage density, calculate the sectional canopy volume and spray volume designated to individual nozzles, and manipulate variable numbers of nozzles to discharge variable spray rates to match tree structures. Laboratory tests were conducted to ensure the control system to meet the expectations. These tests included automatically controlling each individual nozzle, separate groups of nozzles and random number of nozzles by changing target positions, determining delay times to fit different size sprayers by changing laser sensor positions and travel speeds, and manually selecting active nozzles to discharge sprays to desired target heights. As a result, the flow rate of each nozzle was automatically optimized to cover different parts of canopies at different travel speeds in real time. In addition, operators could use the touch screen to modify spray parameters corresponding to types of conventional sprayers and number of nozzles on the sprayers as needed. Consequently, adaptation of the intelligent spray control technology into the conventional sprayers would offer a sustainable and environmentally responsible approach to control insects and diseases. An integrated CFD model was developed to predict air velocity distributions inside and around tree canopies from an air-assisted pesticide sprayer. The motion of sprayer was simulated by the sliding mesh technique, and the tree canopies were defined in the computational domain as virtual porous media without their geometric modeling. Validation of the CFD model was accomplished in three steps by comparing the CFD results with previous measurements. Air velocities and airflow pressures downwind from the sprayer agreed well with the measurements when the sprayer was both stationary and in motion.

Publications

• Type: Journal Articles Status: Published Year Published: 2016 Citation: Liu, H. and H. Zhu. 2016. Evaluation of a laser scanning sensor on detection of complex shaped targets for variable-rate sprayer development. Transactions of the ASABE, 59(5): 1181-1192.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Liu, H. and H. Zhu. 2016. Evaluation of a laser scanning sensor on detection of complex shaped targets for variable-rate sprayer development. Transactions of the ASABE, 59(5): 1181-1192. Li, Y. and H. Zhu. 2016. A Versatile Strategy to Upgrade Conventional Sprayers with Intelligent Spray Control Functions. Abstract ID#: 2452704. 2016 ASABE Annual International Meeting.