Location: Crop Production Systems Research
Project Number: 6066-22000-079-00-D
Project Type: In-House Appropriated
Start Date: Aug 4, 2014
End Date: Apr 30, 2019
Objective 1: Develop analytical methods and integrate them into decision support tools for effective aerial application. Sub-objective 1.1: Verify new drift modeling paradigms with field data; optimize spray delivery systems for drift reduction considering temporal weather differences in statistical analysis. Sub-objective 1.2: Determine plant injury due to off-target drift by spray sampling, biological measurements, and remote sensing. Sub-objective 1.3: Determine periods of stable atmosphere favorable for long-distance movement of spray deleterious to susceptible crops downwind from spray application; quantify the effect of surface conditions with weather and incorporate this information into new guidelines for pilots to reduce potential for off-target movement of spray. Objective 2: Develop laboratory, ground application, and aerial systems for delivery of biological control agents such as non-toxigenic A. flavus for control of mycotoxin and evaluate their effectiveness with bio-assay analysis. Sub-objective 2.1: Determine field conditions that promote fungal contamination using on-the-go soil sensors and remote sensing; map risk zones for targeted application. Sub-objective 2.2: Develop aerial application systems to deliver biological control agents and evaluate effectiveness of control with bio-assay analysis. Objective 3: Develop methodologies that utilize existing remote sensing technologies for user- accessible agricultural aircraft and Unmanned Aerial System (UAS) platforms to detect invasive weeds and wild host plants for insect pests and distinguish between herbicide resistant and non-resistant weeds for use in selective spray management strategies. Sub-objective 3.1: Identify spectral signatures and classification techniques to distinguish herbicide resistant from non-herbicide resistant weeds; evaluate imaging sensors using the identified signatures and map the distribution of herbicide resistant weeds for selective spraying. Sub-objective 3.2: Identify spectral bands and classification techniques most useful in discriminating wild host plants of the tarnished plant bug from other land cover features and evaluate airborne imagery acquired to map these plants in and surrounding agricultural fields. Sub-objective 3.3: Develop accessible remote sensing and rapid image processing systems for targeted application that can be operated by agricultural pilots; develop lightweight remote sensing systems requiring minimal user intervention for Unmanned Aerial Systems (UAS).
This project seeks to advance application technology through improvements in 1) drift management technologies and models; 2) aerial systems to effectively deliver biological control agents; and 3) remote sensing systems usable by pilots for agricultural aircraft to identify herbicide-damaged plants, invasive weeds, and wild host plants. While drift management is a concern for all pesticide applications, it is of particular concern for aerial applications. The use of herbicide-resistant crop varieties has increased use of glyphosate, both exacerbating the drift problem and giving rise to herbicide resistant weeds that need to be dealt with. Biological control is making headway, but aerial systems are needed to apply these agents. Aerial systems will be developed to effectively deliver liquid formulations of non-toxigenic biological agents to control mycotoxins in corn. Experiments for drift will attempt to reduce confounding of treatment data with environmental effects, preserving statistical precision of the experiments. Specific guidelines for pilots to prevent spraying during temperature inversions will be developed. The deleterious effects of off-target herbicide drift will be detected using spray and biological sampling, and hyperspectral and multispectral remote sensing. Remote sensing will also be used to detect herbicide resistant weeds and wild hosts for plant bug for targeted management. Improvements in remote sensing and rapid image analysis systems will allow accessibility of these systems by agricultural pilots. Autonomous Unmanned Aerial (or ”drone”) platforms will be developed with rapid image analysis capabilities for areas not served by agricultural aircraft. Experiments are also proposed to demonstrate the validity of techniques developed.