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ARS Home » Southeast Area » Raleigh, North Carolina » Soybean and Nitrogen Fixation Research » Research » Research Project #445571

Research Project: Yield Limitations of Soybean Varieties Under Drought: Identifying and Overcoming Weaknesses by Team Drought (University of Arkansas)

Location: Soybean and Nitrogen Fixation Research

Project Number: 6070-21220-070-047-A
Project Type: Cooperative Agreement

Start Date: Oct 1, 2023
End Date: Sep 30, 2024

Objective:
1. Germplasm and cultivar development: a) Develop and release drought-resilient germplasm and high yielding varieties. b) Incorporate high oleic acid and high protein genes into elite drought-resilient breeding stock. 2. Gene discovery and genetic marker development: a) Identify and incorporate newly discovered drought tolerance genes (slow wilting and beneficial root traits) into high-yielding backgrounds. 3. Improve drought screening and selection.

Approach:
The Cooperator will focus on breeding and characterization of the genetic architecture of drought tolerance in soybean. Between 8 to 10 bi-parental breeding populations will be developed during the summer of 2024; sets will be harvested and F1 seeds sent to an off-season nursery in Puerto Rico or Costa Rica. Populations will be advanced using the modified pod descent method from generation F1 to F4 in about 18 months. Progeny rows (100 per population, 800-1,000 total) will return to Fayetteville, AR in 2026. Selected progenies based on pod load, overall agronomic traits, and desirable marker characterization will be grown in replicated preliminary trials in 2027 and pending satisfactory yield performance will be moved for multi-environment finals in 2028. In addition, 3 bi-parental mapping populations consisting of elite, well-adapted lines and drought-tolerant diverse accessions will be developed for further narrowing down genomic regions associated with drought tolerance. These mapping lines will be phenotyped based on visual wilting scores, as well as a combination of RGB/thermal cameras and machine learning/deep learning algorithms to identify features highly correlated with drought. Lastly, a collaborative test consisting of approximately 50 breeding lines will be grown in replicated trials in two locations in Arkansas.