Location: Aerial Application Technology Research2017 Annual Report
1a. Objectives (from AD-416):
Objective 1: Optimize aerial spray technologies for on-target deposition and drift mitigation. Subobjective 1A: Characterize effects of spray systems and formulations on droplet size. Subobjective 1B: Enhance spray swath deposition and uniformity. Subobjective 1C: Develop criteria for efficient operation and selection of aerial spray systems. Objective 2: Develop geospatial data processing and analyses methods for crop condition assessment and pest management. Subobjective 2A: Develop variable rate application methods for plant growth regulators (PGRs) and defoliants based on physiological conditions. Subobjective 2B: Develop precision aerial application methods for fertilization and disease control based on biotic conditions.
1b. Approach (from AD-416):
Utilizing engineering and biological principles, laboratory and field studies will be conducted to evaluate the effects of various aerial application parameters, such as spray formulation and droplet size, on aerial application efficiency and biological efficacy. Efforts will focus on the integration of laboratory spray droplet measurements and remote sensing systems to maximize the efficacy of crop production materials while minimizing any off-target impact from these sprays. Plant health and species differences will be determined from remotely sensed data and used to make spray application decisions related to spatial locations and dosages. This project will develop and implement new and improved aerial application technologies for safe, efficient, and sustainable crop production and protection.
3. Progress Report:
Work under this project during FY 2017 resulted in significant progress in improving the effective use of crop production and protection materials, enhancing the use of remote sensing and precision application in crop production systems, and spray droplet modeling with an emphasis on rotary-wing aircraft models. Spray atomization models were completed for fixed and rotary wing aircraft and the smartphone app was updated (Objective 1). Significant progress was made in development of spray deposition and drift models, which will aid spray applicators in making spray applications that increase efficacy and minimize off-target spray drift. Wind-tunnel tests were completed to determine the levels of spray drift mitigation from a number of spray nozzles and formulations including real-world tank mixes used by aerial applicators and public health users (Objective 1). To control cotton root rot, a variable-rate fungicide applicator was installed on a cooperator’s planter. The applicator only applied fungicide in the areas of the field where root rot had been identified resulting in significant cost saving through reduced application rates of the fungicide (Objective 2). Remote sensing studies were conducted that identified volunteer cotton plants in ditches and waterways, and diseased cotton plants; the data from these flights was coupled with prescription application maps to regulate the usage of agrochemicals based on field conditions (Objective 2). Numerous remote sensing flights were conducted to monitor the spread of cotton root rot at two locations in Texas. A dual-camera imaging system for remote sensing studies was developed using a consumer-grade camera and transferred to aerial applicators to use in their operations (Objective 2). These projects support the DoD-Deployed WarFighter Protection Program with specific collaborations with the U.S. Navy Entomology Center of Excellence, EPA Drift Reduction Technology Program, several agrochemical companies, and equipment manufacturers. Project scientists during FY 2017 served on numerous occasions as experts in the aerial application industry and were sought out for advice and consultation by industry and academic research personnel, and by officials with the EPA, Department of Homeland Security, Department of Defense, State Department, USDA-APHIS, and representatives from numerous state agencies and organizations. This project supports National Programs 305, 304, and 104.
1. Early identification of cotton fields using mosaicked aerial multispectral imagery. Early identification of cotton fields is important for advancing boll weevil eradication progress and reducing the risk of reinfestation. Remote sensing has long been used for crop identification, but limited work has been reported on early identification of cotton fields. ARS scientists at College Station, Texas, evaluated aerial imagery for identifying cotton fields before cotton plants start to bloom. Aerial color and near-infrared images taken over an 8 km by 12 km cropping area were mosaicked and then classified into different crops and cover types using image classification techniques. Results showed that classification maps were able to correctly identify over 90% of the cotton areas. The methodologies presented in this study will be useful for boll weevil eradication program managers to quickly and efficiently identify cotton fields at relatively early growth stages using mosaicked aerial imagery.
2. Standardized methods to evaluate agricultural spray nozzles for droplet size. Any successful agrochemical application starts with understanding the role that nozzle type and operational setup play in creating the applied droplet size. With a number of testing methods and instruments available for these evaluations, standard methods are critical to ensure that consistent, repeatable results are obtained. Standardized methods, shown to minimize sampling bias and provide reliable results, were developed by ARS researchers at College Station, Texas, and were reported as part of a novel publication outlet devoted to documentation of scientific experimental methods through both written and video media. Reporting and demonstrating the standard methods provide a significant record of guidance for other research personnel and locations conducting research related to agrochemical spray applications. These standard methods currently provide the basis for a number of national and international programs and standards, including the EPA Drift Reduction Technology Program and standards from the American Society of Agricultural and Biological Engineers, American Society for Testing and Materials International, and the International Standards Organization.
Fritz, B.K., Hoffmann, W.C., Henry, R. 2016. The effect of adjuvants at high spray pressures for aerial applications. American Society for Testing and Materials. doi:10.1520/STP159520150086.
Yang, C., Suh, C.P., Westbrook, J.K. 2017. Early identification of cotton fields using mosaicked aerial multispectral imagery. Journal of Applied Remote Sensing (JARS). 11(1):016008.
Chu, T., Chen, R., Landivar, J., Maeda, M., Yang, C., Starek, M. 2016. Cotton growth modeling and assessment using UAS visual-band imagery. Journal of Applied Remote Sensing (JARS). 10(3):036018.
Shi, Y., Thomasson, A., Murray, S., Pugh, N.A., Rooney, W.L., Shafian, S., Rajan, N., Rouze, G., Morgan, C.L., Neely, H.L., Rana, A., Bagavathiannan, M.V., Henrickson, J., Bowden, E., Valasek, J., Olsenholler, J., Bishop, M.P., Sheridan, R., Putman, E.B., Popescu, S., Burks, T., Cope, D., Ibrahim, A., McCutchen, B.F., Baltensperger, D.D., Avant, R.V., Vidrine, M., Yang, C. 2016. Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PLoS One. 11(7):e0159781.
Wu, M., Yang, C., Song, X., Hoffmann, W.C., Huang, W., Niu, Z., Wang, C., Wang, L. 2017. Evaluation of orthomosics and digital surface models derived from aerial imagery for crop mapping. Remote Sensing. doi:10.3390/rs9030239.
Henry, R., Fritz, B.K., Hoffmann, W.C., Kruger, G. 2016. The influence of nozzle type, operating pressure, and tank-mixture components on droplet characteristics and the EPA's drift reduction rating. Journal of ASTM International. doi:10.1520/STP159520150098.
Thistle, H.W., Bonds, J.S., Kees, G.J., Fritz, B.K. 2017. Evaluation of spray drift from backpack and UTV spraying. Transactions of the ASABE. 60(1):41-50.
Westbrook, J.K., Eyster, R.S., Yang, C., Suh, C.P. 2016. Airborne multispectral identification of individual cotton plants using consumer-grade cameras. Remote Sensing Applications: Society and Environment. 4:37-43.
Lan, Y., Chen, S., Fritz, B.K. 2017. Current status and future trends of precision agricultural aviation technologies. International Journal of Agricultural and Biological Engineering. 10(3):1-17.
Fisher, A., Coleman, C., Hoffmann, W.C., Fritz, B.K., Rangel, J. 2017. The synergistic effects of almond protection fungicides on honey bee (Apis mellifera) forager survival. Journal of Economic Entomology. 110(3):802-808.
Song, X., Yang, G., Yang, C., Wang, J., Cui, B. 2017. Spatial variability analysis of within-field winter wheat nitrogen and grain quality using canopy fluorescence sensor measurements. Remote Sensing. 9:237.