2026
Integrating drone imagery and a self-propelled sprayer to implement SSWC in soybeans
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
(none assigned)
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Paulo Flores, North Dakota State University
Co-Principal Investigators:
Project Code:
2026_Agronomy_02
Contributing Organization (Checkoff):
Leveraged Funding (Non-Checkoff):
Institution Funded:
Brief Project Summary:
The project aims to use cameras mounted into drones to map weeds across a soybean field, convert that map into a herbicide application prescription map that can be uploaded to a commercial field size sprayer to implement site specific weed control. The core idea of the project is to use the prescription map created from the drone images to turn sprayer's nozzles off where there are no weeds in the field.
Information And Results
Project Summary

the goal of the proposal is to develop a workflow to map weeds across a soybean field using drone imagery. The weed map then will be converted to a prescription map to be uploaded to a commercial size sprayer to implement site-specific weed control (SSWC). The general idea is to use the weed map to shut nozzles off on the sprayer on locations where there are no weeds in the field. Previous studies carried out at NDSU with similar approach for corn have yielded savings ranging from 35-50%. Given the acreage of soybean grown in North Dakota (around 6.2 million acres) and the cost of herbicides ($15-20/ac), such approach has the potential to save soybean growers several million dollars annually in chemicals. The reduction on chemical usage can positively impact soybean growers’ bottom line, given the current scenario of the high input costs and low crop price. In addition, weed mapping across a field would be beneficial when controlling herbicide resistant weeds, allowing one to use a more expensive tank mix and applying product only were there are weeds, reducing the overall cost per acre.

Project Objectives

i) determine the best combination of drone flight height and sensor (RGB or multispectral) to maximize data collection efficiency to map weeds across a soybean field; ii) identify and implement algorithms to separate soybean plants from weeds based on the UAS imagery; iii) create a weed control Rx-map based on the UAS imagery and weed distribution across the field; and iv) field implementation and assessment of the SSWC approach versus the current approach (blanket application) used for weed control.

Project Deliverables

a) recommendation regarding flight height and type of sensor to be used to map the weeds across a soybean field; b) a workflow to semi-automate the process of data analysis to generate the weed control Rx-map based on drone imagery; c) an assessment of the efficacy of our site-specific weed control approach compared to a blanket chemical application across the field.

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

The primary impact for North Dakota soybean growers would be opportunities to reduce herbicide input costs and an overall reduction in the amount of herbicide applied to their soybean acreage. The savings potential will further increase if more than one post-emergence application is needed.

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.