2021
Evaluating UAV (drone) Use for Within Season Management Decisions in NC Soybeans
Category:
Sustainable Production
Keywords:
Data ManagementDrone/UAS
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Rob Austin, North Carolina State University
Co-Principal Investigators:
Project Code:
21-033
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:
Drones are transforming how aerial imagery is captured and used. This interdisciplinary project investigates the use of drones in five key production areas: re-plant decisions, incidence of fungal disease, severity of insect-related defoliation, weed identification and management and nutrient deficiencies. Efforts evaluate common commercial drone technology to document baseline potential for decision support in soybean. This research aims to identify the most promising and profitable uses for drone technology in soybean production, evaluate tradeoffs between satellite and drone imagery in guiding farm-scale decisions, test the use of commercially available drone technology to differentiate between soybean stress and evaluate the use of drone imagery in re-plant decisions and stand counts.
Key Beneficiaries:
#agronomists, #extension agents, #farmers
Unique Keywords:
#ag technology, #drones, #technology, #uavs
Information And Results
Project Summary

Unmanned Aircraft (drones) are marketed in the agricultural sector as a ‘revolutionary’ technology. Although the technology and corresponding data are truly unique, the application of data outputs for agricultural management decisions (e.g., re-plant, pest management) remain unclear. This interdisciplinary project will investigate the use of drones in five key production areas 1) re-plant decisions, 2) incidence of fungal disease, 3) severity of insect-related defoliation, 4) weed identification and management, and 5) nutrient deficiencies. We will evaluate common commercial drone technology to document baseline potential for decision support in soybean. To do this, we have assembled a team of extension specialists with expertise in four key production areas to help guide technology evaluation, inform the analysis, and extend the information to the grower community. Because the number of fields that can be evaluated with drones remains limited, we will also integrate imagery from satellites as a complementary data source to extend the evaluation to farm-scale recommendations. Tradeoffs between the predictive capability and impact on decision-making will be compared between the two technologies and weighed against the costs and likelihood for adoption. The project will leverage ‘off-the-shelf’ drone and satellite data products and services to perform the analysis, but will also investigate the use of multispectral sensors and custom analytical solutions when there is a clear potential for adoption and profit. The information generated by this project will be used to provide robust training to County Extension Agents and farmers across North Carolina on the use of these technologies to enhance profitability.

Project Objectives

1. Identify the most promising and profitable uses for drone technology in soybean production

2. Evaluate tradeoffs between satellite and drone imagery in guiding farm-scale decisions

3. Test the use of commercially available drone technology to differentiate between soybean stress related to disease, pests, and/or weeds.

4. Evaluate the use of drone imagery in re-plant decisions and stand counts.

5. Provide results to stakeholders, educate County Extension Agents and soybean producers on the use of the technology, and publish findings.

Project Deliverables

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.