2021
sUAS Weed Mapping in Soybeans
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Contributor/Checkoff:
Ohio Soybean Council
Category:
Sustainable Production
Keywords:
AgricultureCrop protectionHerbicide
Parent Project:
sUAS Weed Mapping in Soybeans
Lead Principal Investigator:
Scott A. Shearer, The Ohio State University
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Ohio Soybean Council
$50,000
Institution Funded:
The Ohio State University
$50,000
Brief Project Summary:
This project helps growers identify and map herbicide-resistant weed escapes using small UAS as a precursor for targeted eradication. Weed escapes simply refers to weeds that survive weed management practices. Most weed species produce prolific seed. It’s easier to control weed escapes before they build the soil seed bank. The effort includes building a reference library of herbicide-resistant weed escapes that occur in Ohio soybeans, training Convolutional Neural Nets for sematic segmentation of NADIR imagery generated from fixed wing sUAS overflights, using this technology to map weed escapes and developing methodology for real-time classification of images on-board of the sUAS. The project also includes field tests.
Key Beneficiaries:
#agronomists, #extension agents, #farmers
Unique Keywords:
#drones, #uavs, #weed control, #weed resistance, #weeds
Information And Results
Project Summary

In Ohio, 95% of soybean acres were planted with herbicide tolerant varieties in 2019. The term “weed escapes” simply refers to weeds that survive weed management practices. Presence of few weed escapes during the growing season do not necessarily impact soybean yield. But, most weed species are prolific seed producers. It is much easier to control weed escapes before the soil seed bank is built. The proposed effort will utilize sUAS for identification and mapping of weed escapes as a precursor to sUAS directed spray application for eradication.

Project Objectives

- Image Acquisition and Construction of Image Database
- s UAS Mapping of Weed Escapes

Project Deliverables

We will construct a database of weed images. A database is the first key element in any Artificial Intelligence (AI) application, which will be used for training CNNs. Given the increased use of AI applications in precision agriculture, development of a database is a key step for continued use of AI tools. The image library of weed escapes collected in Ohio will support weed classification.

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

The project will help growers to map and identify weed escapes by using sUAS as a precursor for targeted eradication.
One of the OSC’s objectives under the drive innovation goal is to “develop technologies and practices that support Ohio soybean farmer’s commitment to environmental stewardship.” The severity and nature of weed problems in soybean vary from year to year and location to location, and are influenced by many factors including environmental conditions, crop production practices, previous cropping history and cultivar selection.

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.