Location: Aerial Application Technology Research2015 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 2015 resulted in significant progress in improving the efficacy of crop production and protection materials (Objective 1), enhancing the use of remote sensing and precision application in crop production systems (Objective 2), and spray droplet modeling (Objectives 1, 2). 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. These projects support the EPA Drift Reduction Technology Program, DoD-Deployed WarFighter Protection Program, and U.S. Navy Entomology Center of Excellence. A variable-rate controller was developed and installed for screwworm dispersion with the APHIS-Screwworm Barrier Maintenance Program in Panama. Biological assessments of various mosquito control products and rates were conducted in conjunction with university and mosquito abatement personnel. These studies also included numerous honeybee toxicity studies. Free smartphone applications along with the Unit’s spray atomization models were further developed and modified for the iPhone and Google Play platforms that transfer the project’s research data into more useful formats for our customers. Remote sensing studies were conducted that identified volunteer cotton plants in ditches and waterways, and diseased cotton plants. Numerous remote sensing flights were conducted to monitor the spread of cotton root rot at two locations in Texas. A single camera imaging system for remote sensing studies was developed using a consumer-grade camera and transferred to aerial applicators to use in their operations. Project scientists during FY 2015 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, DoD, State Department, USDA-APHIS, and representatives from numerous state agencies and organizations. This project supports National Programs 305, 304, and 104.
1. A low-cost single-camera imaging system for aerial applicators. Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. ARS researchers at College Station, Texas, developed a low-cost, user-friendly imaging system that can be easily installed on aerial applicators’ aircraft for pest detection and application assessment. The system employs a digital camera to acquire geotagged images and multiple images can be easily stitched together using readily available software for assessing large cropping areas. Aerial applicators can use the procedures and techniques developed by this work to assemble such a system and use it to generate additional revenues from remote sensing services.
2. Update to the ARS fixed wing spray nozzle models. Successful aerial applications require proper spray nozzle selection and setup to insure droplet size meets both label requirements and meteorological and geographical conditions at the site of application. ARS scientists at College Station, Texas, successfully evaluated the 12 most commonly used aerial spray nozzles for droplet size across all potential nozzle configurations (nozzle size and position in the airstream) and operational settings (spray pressure and flight speed). The new models greatly enhance the currently available data for the aerial nozzles tested and were used to update computer and mobile device based user interfaces. Using the developed spray nozzle models, aerial applicators can properly select nozzle type and operational settings that insure their applications meet agrochemical product label requirements to maximize efficacy with minimal off-target drift.
3. Assessment of spider mite damage via multispectral imaging. Spider mites can cause significant damage in cotton, resulting in significantly decreased yields. ARS researchers at College Station, Texas, used a multispectral optical sensor to quantify spider mite damage in cotton, showing that half-rate application of common acaracides was just as effective as full-rate applications in controlling mites. Farmers, crop consultants, and applicators will be able to use the results of this work to reduce chemical usage and environmental loading while maintaining good control of these cotton pests.
4. Spray adjuvants minimally affect droplet size with rotary atomizers. Rotary atomizers are a type of spray nozzle used by applicators in a variety of spray applications, including forestry sprays and mosquito abatement. ARS researchers at College Station, Texas, conducted a series of fungicide spray atomization trials to determine the effects of spray adjuvants, which can change the physical properties of a spray solution, on spray droplet size from a rotary atomizer. The different adjuvants affected droplet by less than 10 percent as compared to the fungicide only spray solution. Understanding the role different adjuvant types play in the final droplet size of the spray is key to successfully setting up and making effective, environmentally sensitive applications with rotary atomizers.
Fritz, B.K., Hoffmann, W.C., Bonds, J., Haas, K., Zbigniew, C. 2014. The biological effect of cage design corrected for reductions in spray penetration. Journal of Plant Protection Research. 54(4):395-400.
Hoffmann, W.C., Fritz, B.K., Farooq, M., Walker, T., Hornsby, J., Bond, J. 2013. Evaluation of aerial spray technologies for adult mosquito control applications. Journal of Plant Protection Research. 53:222-29.
Huang, Y., Thomson, S.J., Hoffman, W.C., Lan, Y., Fritz, B.K. 2013. Development and prospect of unmanned aerial vehicles for agricultural production management. International Journal of Agricultural and Biological Engineering. 6(3):1-10.
Henry, R., Kruger, G., Fritz, B.K., Hoffmann, W.C., Bagley, B., Czazyck, Z. 2014. Measuring the effect of spray plume angle on the accuracy of droplet size data. In: Sesa, C., editor. Pesticide Formulation and Delivery Systems: 33rd Volume, "Sustainability: Contributions from Formulation Technology." West Conshohocken, PA: ASTM International. p. 129-138. DOI: 10.1520/STP1569-EB.
Villar, J.L., Turland, N.J., Juan, A., Gaskin, J.F., Alonso, M.A., Crespo, M.B. 2015. Tamarix minoa (Tamaricaceae), a new species from the island of Crete (Greece) based on morphological and plastid molecular sequence data. Taxon. 45(2):161-172. DOI: 10.3372/wi.45.45201.
Martin, D.E., Lopez, J., Lan, Y. 2012. Laboratory evaluation of the GreenSeeker (TM) hand-held optical sensor to variations in orientation and height above canopy. International Journal of Agricultural and Biological Engineering. 5(1):43-47.
Liu, Y., Wan, C., Hao, Y., Lan, Y. 2013. Rapid quantitative analysis of Dimethoate pesticide using surface enhanced raman spectroscopy. Food and Bioprocess Technology. 56:1043-1049.
Latheef, M.A., Hoffmann, W.C. 2014. Toxicity of selected acaricides in a glass-vial bioassay to two-spotted spider mite (Acari: Tetranychidae). Southwestern Entomologist. 39(1):29-36.
Suh, C.P., Medrano, E.G., Lan, Y. 2015. Detecting cotton boll rot with an electronic nose. Journal of Cotton Science. 18:435-443.
Lopez, J., Latheef, M.A., Hoffmann, W.C. 2014. A multiyear study on seasonal flight activity based on captures of southern green stink bug (Hemiptera: Pentatomidae) in blacklight traps in Central Texas. Journal of Cotton Science. 18:153-165.
Yang, C., Hoffmann, W.C. 2015. A low-cost single-camera imaging system for aerial applicators. Journal of Applied Remote Sensing (JARS). 9:096064.
Fritz, B.K., Hoffmann, W.C. 2015. Update to the USDA-ARS fixed-wing spray nozzle models. Transactions of the ASABE. 58(2):281-295.
Zhang, D., Chen, L., Zhang, R., Xu, G., Lan, Y., Hoffmann, W.C., Wang, X., Xu, M. 2015. Evaluating effective swath width and droplet distribution of aerial spraying systems on M-18B and Thrush 510G airplanes. International Journal of Agricultural and Biological Engineering. 8(2):21-30.
Everitt, J.H., Summy, K.R., Glomski, L.M., Owens, C.S., Yang, C. 2009. Spectral reflectance and digital image relations among five aquatic weeds. Geocarto International. 61:15-23.
Everitt, J.H., Yang, C., Summy, K.R., Owens, C.S., Glomski, L.M., Smart, R.M. 2011. Using in situ hyperspectral reflectance data to distinquish nine aquatic plant species. Geocarto International. 26(6):459-473.
Martin, D.E. 2013. Flow variability of an aerial variable-rate nozzle at constant pressures. Applied Engineering in Agriculture. 29:483-488.
Luo, B., Yang, C., Chanussot, J. 2013. Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing. 51:162-173.
Yang, C., Everitt, J.H., Du, Q., Luo, B., Chanussot, J. 2013. Using high resolution airborne and satellite imagery to assess crop growth and yield variability for precision agriculture. Proceedings of the Institute of Electrical and Electronics Engineers. 101:582-592.
Moran, P.J., Yang, C. 2012. Distribution of wild taro (Colocasia esculenta) in subtropical Texas, growth of young colonies, and tolerance to simulated herbivory. Subtropical Plant Science. 64:18-28.
Everitt, J.H., Yang, C., Summy, K.R., Nachtrieb, J.G. 2013. Using hyperspectral reflectance data to assess biocontrol damage to giant salvinia. Geocarto International. 28(6):502-516.
Martin, D.E., Carlton, J.B. 2013. Airspeed and orifice size affect spray droplet spectra from an aerial electrostatic nozzle for rotary-wing applications. Atomization and Sprays. 22:997-1010.
Yang, F., Liu, S., Chen, L., Song, H., Wang, Y., Lan, Y. 2012. Detection method of various obstacles in farmland based on stereovision technology. Transactions of the Chinese Agricultural Machinery. 43(5):168-172.
Yang, C., Odvody, G.N., Fernandez, C.J., Landivar, J.A., Minzenmayer, R.R., Nichols, R.L. 2015. Evaluating unsupervised and supervised image classification methods for mapping cotton root rot. Precision Agriculture. 16:201-215.
Westbrook, J.K., Suh, C.P., Yang, C., Lan, Y., Eyster, R.S. 2015. Airborne multispectral detection of regrowth cotton fields. Journal of Applied Remote Sensing (JARS). 9(1):096081.
Li, H., Lee, W., Wang, K., Ehsani, R., Yang, C. 2014. Extended spectral angle mapping (ESAM) for citrus greening disease detection using airborne hyperspectral imaging. Precision Agriculture. 15:162-183.
Li, X., Lee, W., Li, M., Ehsani, R., Mishra, A., Yang, C. 2015. Feasibility study on Huanglongbing (citrus greening) detection based on WorldView-2 satellite imagery. Biosystems Engineering. 132:28-38.
Ran, Q., Li, W., Du, Q., Yang, C. 2015. Hyperspectral image classification for mapping agricultural tillage practices. Journal of Applied Remote Sensing (JARS). 9:097298.