2017
Increasing the rate of genetic gain for yield in soybean breeding programs
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Contributor/Checkoff:
North Central Soybean Research Program
Category:
Sustainable Production
Keywords:
GeneticsGenomics
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Leah McHale, The Ohio State University
Co-Principal Investigators:
William Beavis, Iowa State University
Silvia Cianzio, Iowa State University
David Hyten, Iowa State University
Asheesh Singh, Iowa State University
William Schapaugh, Kansas State University
Dechun Wang, Michigan State University
Jianxin Ma, Purdue University
Katy M Rainey, Purdue University
Brian Diers, University of Illinois at Urbana-Champaign
Matthew Hudson, University of Illinois at Urbana-Champaign
Aaron Lorenz, University of Minnesota
Pengyin Chen, University of Missouri
Andrew Scaboo, University of Missouri
George Graef, University of Nebraska
Steven Clough, USDA/ARS-University of Illinois
+14 More
Project Code:
NCSRP
Contributing Organization (Checkoff):
North Central Soybean Research Program
$1,075,355
Institution Funded:
The Ohio State University
$1,075,355
Brief Project Summary:

Increases in soybean yield through breeding have been slower than growers expect, with the rate of yield increases for soybean substantially less than that for corn. A collaborative study led by Diers of a historic set of MG II-IV varieties released from 1923 to 2008 revealed a recent rate of genetic gain of 0.43 bu/ac/yr, whereas reports of genetic gain in corn generally range from 1.0 to 1.2 bu/ac/yr.

There are several possible targets for improving the rate of gain in soybean grain yield if the equation of genetic gain is considered. The rate of genetic gain from a single cycle of selection can be predicted by the breeders’ equation (?G = S[sA/sP]), where ?G is the change in yield...

Unique Keywords:
#breeding & genetics
Information And Results
Project Deliverables

• Observed data, selection information, pedigree and plot layout (range-row information), and shipment of seed for planting for breeders at 11 locations.
• Overall data management plan, preliminary analytical pipeline implemented and coordinated by the Rainey lab.
• All breeders’ lines ranked simultaneously for yield breeding value, maturity prediction and a metric of diversity. Lines selected using additional sources of information may provide higher rank-order correlation with the performance of preliminary yield trails.

Final Project Results

Update:

View uploaded report PDF 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.