2026
Modern breeding methodologies to expediate elite variety release
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
(none assigned)
Lead Principal Investigator:
Carrie Miranda, North Dakota State University
Co-Principal Investigators:
Project Code:
2026_Agronomy_23
Contributing Organization (Checkoff):
Leveraged Funding (Non-Checkoff):
Institution Funded:
Brief Project Summary:
This project allows for expediated release of elite soybean varieties using genomic prediction and speed breeding techniques for generation advancement and trait introgression. Genomic prediction will help identify high-yielding and early-maturing soybean lines before field testing, improving breeding efficiency. This work as integrates valuable traits such as herbicide tolerance into high-yielding germplasm through a rapid backcrossing method; an approach is similar to private industry techniques, creating competitive soybean varieties. The project benefits North Dakota farmers by producing high yielding, herbicide-resistant soybean varieties tailored to the region at a lower cost than private options. It also provides students with hands-on training in advanced breeding techniques, strengthening the future agricultural workforce.
Information And Results
Project Summary

This project will allow the expedition of elite variety release by utilizing speed breeding techniques to introgress economically important traits and implement genomic prediction. 1) Trait Integration: Using elite, high yielding materials created in the Core germplasm project, newly acquired high value, single gene traits can be introgressed into the elite germplasm quickly utilizing a backcrossing protocol that expedites generation turnaround time. It is much faster to add a single gene to elite background through backcrossing than to try to improve yield and add the trait simultaneously. This is a methodology similar to what is used in private companies. 2) Genomic Prediction: Genomic prediction is a technique to assist breeders to select high yielding lines before they have yield data. This methodology is used in private company breeding practices for several years and has led to significant yield gains. The goal is to add this methodology to the NDSU soybean breeding pipeline over time. This entails genotyping a subset of the F5 populations of experimental lines which have not entered yield testing and developing statistical models for yield and maturity to predict successful performance.

Project Objectives

• Creation of high yielding varieties with herbicide traits.
• Development of a prediction tool that will facilitate more accurate selection of high yielding lines.
• Development of a prediction tool that will facilitate more accurate selection of early maturing 00 lines before being tested in their correct environment.

Project Deliverables

The trait introgression pipeline will be the final step in creation of competitive, high yielding soybean varieties with licensed herbicide traits. This improved pipeline will lead to faster creation of released varieties. The genomic prediction tool will also facilitate faster creation of high yielding varieties by assisting the breeder in decision making both for yield and maturity before conducting years of yield testing. Students will also be trained to create these prediction models which is a desirable and necessary skill set for employment both in public and private professions.

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

This project will directly benefit ND farmers with the creation of high yielding, disease resistant varieties that are created specifically for North Dakota. NDSU soybean varieties are typically less expensive than private company varieties. This project will allow the NDSU soybean breeding program to have yields and herbicide traits that rival private company varieties.

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.