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United States Department of Agriculture

Agricultural Research Service

Research Project: Pesticide Application Technologies for Spray-drift Management, Maximizing In-field Deposition, and Targeted Spraying

Location: Crop Production Systems Research

2013 Annual Report

1a. Objectives (from AD-416):
Objectives are: 1) Control off-target drift and enhance penetration of active ingredients, such as fungicides and biological control agents, into crop canopies; and 2) Develop remote sensing methods, utilize and evaluate Global Positioning Systems (GPS), develop methods amenable to rapid image processing, and evaluate flow control systems to support variable rate aerial application.

1b. Approach (from AD-416):
This project seeks to advance application technology through improvements in 1) drift management technology, 2) technologies for improved within-canopy deposition, 3) use of low-altitude remote sensing to identify stressed plants, and 4) performance of variable rate aerial application systems. While drift management is a concern for all pesticide applications, it is of particular concern for aerial applications. The potential for drift is greater for aerial application due to higher altitudes of spray release and greater air turbulence in the wake of the aircraft. Determination of optimal spray release height will be a goal, as the effect of this variable on within-canopy deposition and off-target drift has not been considered adequately. Experiments for both drift and deposition will attempt to reduce confounding of treatment data with environmental effects, preserving statistical precision of the experiments. Penetration of sprayed material to the lower portions of the canopy is critical for control of fungal spore diseases like Asian Soybean Rust (ASR). Studies will compare nozzle types paired with carefully selected formulations and tank mixes for spray penetration. The deleterious effects of off-target herbicide drift to cotton will be detected using hyperspectral, multispectral, and thermal remote sensing techniques. Evaluation of variable rate aerial application systems will be continued and improvements will be made through interaction with system component manufacturers. Experiments are also proposed to demonstrate the validity of techniques developed.

3. Progress Report:
Decision rules for agricultural pilots to avoid spraying during temperature inversions have been developed for weather conditions typical of summer months. There is evidence that field surface conditions also influence the speed at which inversions develop or are mitigated, so new portable weather towers were purchased that can be moved from field to field. Weather logging instruments with Bluetooth logging capabilities were purchased for these towers to indicate vertical profiles for air temperature and wind speed over different surfaces. Remote sensing for plant stress monitoring was accomplished with a four band multispectral imaging system. The system that triggers the camera based on field position has been refined and is operational, facilitating its use in the aircraft. Software upgrades were made to the multispectral camera on the Unmanned Aerial Vehicle (UAV). The cameras were operated over four research farms to acquire imagery. A newly developed lab-scale spray tower was evaluated for bioassay of bio-pesticide formulations. The effects of conidial density and spray volume on the distribution of droplet size and deposit coverage was evaluated using water sensitive paper (WSP) cards. Results of an experiment using different bio-pesticide suspensions showed no adverse effect on the viability of conidia during the spray regardless of conidial density or spray volume. For aerial spraying, a nozzle that does not shear the droplet was investigated for application of non-toxigenic Aspergillis Flavus fungus for biocontrol of mycotoxins. It was found that larger needle openings were required for adequate flow, and alternatives are being investigated. A greenhouse study was conducted to further characterize the onset of soybean and cotton injury caused by application of glyphosate herbicide using hyperspectral imaging and measurements of plant leaf chlorophyll. Hyperspectral imagery was analyzed to characterize the onset of the soybean and cotton injury, and results were also obtained from a spectroradiometer, a fluorescence meter, and a chlorophyll meter. It was found that selected spectral features could clearly differentiate the stressed plants from the control beginning 24 hours after treatment. A field experiment was continued to characterize crop injury caused by ground-sprayed dicamba at different rates using remote sensing and measuring plant biological parameters. The experiment evaluated the refined remote sensing technology to characterize the onset of the crop injury, to study the relationship between crop injury and yield, and to collect data for a new crop injury model.

4. Accomplishments
1. Distinguishing glyphosate-resistant (GR) and susceptible (GS) Palmer amaranth (pigweed) plants. A study was conducted by ARS scientists at the Crop Production Systems Research Unit in Stoneville, MS, to determine if glyphosate-resistant and susceptible pigweed could be distinguished using hyperspectral imagery (imagery represented by several wavebands of light). Results showed that GS plants reflected higher light in the visible region of the spectrum compared to GR plants, while GR plants reflected higher light in the infrared region of the spectrum compared to GS plants. A combination of fourteen narrow bands provided a good classification of unknown set of GR and GS plants with a validation accuracy of 94%. These results demonstrate that hyperspectral imaging has potential to separate GR from GS Palmer amaranth, and this information has potential to develop a custom camera system to distinguish GR and GS plants from aircraft for selective spraying.

Review Publications
Huang, Y. 2013. Automatic process for food industry: an introduction. In: Caldwell, D.G., editor. Robotics and Automation in the Food Industry - Current and Future Technologies. Philadelphia, PA. Woodhead Publishing, pp 3-20.

Yao, H., Huang, Y., Hruska, Z., Thomson, S.J., Reddy, K.N. 2012. Using vegetative index and modified derivative for early detection of soybean plant injury from glyphosate. Computers and Electronics in Agriculture. 89:145-157.

Bianconi, A., Dalgaard, T., Manly, B.F., Govone, J.J., Watts, M.J., Habermann, G., Huang, Y., Serapiao, A.B. 2013. Methodological difficulties of conducting agroecological studies from a statistical perspective. Journal of Sustainable Agriculture. 37:485-506.

Thomson, S.J., Womac, A., Mulrooney, J. 2013. Reducing pesticide drift by considering propeller rotation effects from aerial application and near buffer zones. Sustainable Agriculture. 2(3):41-51.

Last Modified: 06/24/2017
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