Location:2011 Annual Report
1a. Objectives (from AD-416)
1) Improve existing aerial application technologies to maximize efficiency and biological efficacy of crop production and protection compounds with minimal spray drift and impact to non-target systems. Subobjective 1A: Develop and implement standard procedures for evaluating drift reduction technologies (DRTs) and assessing biological impacts of sprays in crop canopies. Subobjective 1B: Develop and optimize the use of autonomous unmanned aerial vehicles (UAVs) for pest control. Subobjective 1C: Assess biological impacts of spray drift. 2) Develop remote sensing and variable rate aerial application systems that enhance detection, prevention, and control of plant diseases, nutritional deficiencies, or insect damage in annual and perennial crops. Subobjective 2A: Characterize spatial variability of crop conditions using multispectral imaging to develop treatment maps for use with site-specific aerial application systems. Subobjective 2B: Integrate remote sensing and variable rate aerial application technologies to optimize crop management strategies. Subobjective 2C: Develop sensors that rapidly and/or remotely detect pest presence, crop condition, spray droplets, and volatile organic compounds. Subobjective 3D: Adapt autonomous unmanned aerial vehicles (UAVs) for remote sensing of crop conditions. 3) Develop, enhance, and implement decision support systems that improve user ability to select and operate application equipment and schedule spray treatments that optimize biological efficacy. Subobjective 3A: Correlate aerial spray dispersion model estimates with off-target biological effects and in-swath deposition. Subobjective 3B: Develop and implement crop growth and management decision systems to optimize aerial applications.
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 spectrum, on aerial application efficiency and biological efficacy. Efforts will focus on the integration of remote sensing and variable rate application systems to maximize the efficacy of crop production materials while minimizing any off-target impact from these sprays. Decision support systems will be developed that help applicators, farmers, and crop consultants in making the correct treatment decisions to protect a crop from pests. This project will develop and implement new and improved aerial application technologies for safe, efficient, and sustainable crop production and protection.
3. Progress Report
Progress was made in FY 2011 on all three NP 305 objectives; the project also contributes to NP 304 (Component 2). Project scientists made significant progress in improving the efficacy of crop production and protection materials, enhancing the use of remote sensing and precision application in crop production systems, and spray droplet movement modeling. Tests were conducted in high-speed and low-speed wind tunnels to determine the levels of spray drift mitigation from a number of spray nozzles and formulations. The best drift reduction technologies were further evaluated under real-world, field conditions; these projects support the EPA Drift Reduction Technology Program. The Unmanned Aerial Vehicles (UAVs) that crashed during FY 2010 have been repaired and are being fitted with multispectral cameras to take airborne images of crops and to locate and identify weeds and disease states in corn, cotton, and sorghum fields. Biological assessments of various mosquito control products and rates were conducted in wind tunnel trials coupled with assessment of various bioassay cages. A volatile organic compound analyzer was evaluated in the field using a mosquito control product; success was achieved in detecting the temporal signature of the spray cloud as it moved past the analyzer. Remote sensing studies were conducted that successfully differentiated between healthy and disease-state cotton plants. Remote sensing also was effective in identifying volunteer cotton plants in ditches and waterways. Multi-sensor data fusion techniques and technologies were shown by project scientists to enhance the accuracy of field crop structure analyses as compared to single sensor assessments. Integration of data from several aspects of project work yielded significant progress in development of spray deposition and drift models; these models will be utilized to help spray applicators make more informed decisions on issues related to spray application needs, including how such applications should be made and how to best minimize the chances of off-target spray drift. Smartphone applications are being developed to transfer the Project's research data into more useful formats for our customers. Project scientists during FY 2011 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, Dept. of Homeland Security, Dept. of Defense, USDA-APHIS, and representatives from numerous state agencies and organizations.
1. High speed wind tunnel supports aerial application industry. Modern aerial application aircraft make spray applications at speeds up to 220 mph, which exceeds the capability of current wind tunnels used to develop spray models. ARS researchers at College Station, TX, developed a new high-speed wind tunnel testing facility capable of generating airspeeds in excess of 220 mph, and developed and implemented testing protocols for the new wind tunnel. This facility has already been utilized to extend the airspeed range of the ARS spray atomization models, including the first-ever documented atomization data for U.S. Air Force C-130 aircraft spray application at airspeeds exceeding 200 mph. These new high-speed models are critical in helping aerial applicators make effective spray applications that meet regulatory requirements and that are in full compliance with agrochemical product use labels.
2. Improved techniques/protocols for spray applications in pest control. Effective control of mosquitoes and other insects that vector human diseases requires precise spray application techniques. New technologies are needed to efficiently monitor the dispersal of very small droplets over large sampling areas, and to evaluate the efficacy of insecticide treatments using caged insects in the field. ARS researchers at College Station, TX, established the collection efficiency of two commonly used rotary slide spray samplers under multiple wind speeds and spray droplet sizes, and developed correction factors that estimate actual spray droplet size and aerial concentration. The work also established the impact of insect bioassay cages on airspeed, spray droplet size, and spray concentration inside the cages, and developed correction factors that estimate actual spray concentration presented to caged mosquitoes. The sampling techniques and protocols developed by this work provide major advancement in the predictive value of laboratory/field test data in guiding real world spray application for control of major pest and disease-transmitting arthropods.
3. Fusion of remotely sensed data enhances field detection of cotton plants. Aerial and ground-based remotely sensed data can be used to detect both different types of vegetation and the vigor/health of this vegetation over large areas. However, new techniques are needed to improve the capability to accurately discriminate between cotton plants and other crop types, given issues with wild/volunteer cotton and the ongoing Boll Weevil Eradication Program and other cotton pest management issues. ARS researchers at College Station, TX, acquired airborne and ground-based spectral reflectance data over three large agricultural fields in central Texas. Accurate discrimination between cotton plants and other crop types was achieved by analysis of independent aerial and ground-based datasets, and by analysis of combined datasets using a multi-sensor data fusion technique. Crop type classification accuracy of remotely sensed data acquired by the aerial and ground-based sensors was approximately 90%, but improved to greater than 99% using a data fusion technique. This work has achieved great accuracy and reliability in detection of growing cotton, and will be of major benefit in supporting the Boll Weevil Eradication Program by detecting plants that harbor weevils that would otherwise go unnoticed and untreated.Lopez, J., Latheef, M.A., Hoffmann, W.C. 2011. Mortality and reproductive effects of ingested spinosad on adult bollworm. Pest Management Science. 67:220-225.