2019
Use of High Density Protein Maps and Remote Sensing to Understand Protein Levels in U.S. Produced Soybeans (1920-172-0201-B)
Home
Contributor/Checkoff:
United Soybean Board
Category:
Sustainable Production
Keywords:
(none assigned)
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Scott Nelson, Iowa Soybean Association
Co-Principal Investigators:
Matthew Darr, Iowa State University
Project Code:
1920-172-0201-B
Contributing Organization (Checkoff):
United Soybean Board
$100,000
Institution Funded:
Iowa Soybean Association
$100,000
Brief Project Summary:

Unique Keywords:
#digital agriculture, #protein, #sustainability
Information And Results
Project Deliverables

• Independent characterization and validation of a harvester equipped with NIR sensor for measuring soybean protein.
• Creation of accurate protein maps of production soybean fields.
• New understanding of how soybean protein varies across soils and landscape positions leading to agronomic practices to manage soybeans for higher protein.
• Practical knowledge of how remote sensing and other factors can predict soybean protein within and across fields.

Final Project Results

Updated December 10, 2019:

View uploaded report Word file

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.