Jeanette H. Lyerly 1, Adam J. Becker 1, Democrito Rebong 1, Shailesh Raj Acharya 1, Gina Brown-Guedira 2, LeAnn Lux 3, and Nonoy B. Bandillo 1
1. North Carolina State University, Department of Crop and Soil Sciences, Raleigh, NC
2. USDA-ARS, Plant Science Research Unit, Raleigh, NC
3. North Carolina State University, Department of Plant Pathology, Raleigh, NC.
Corresponding Authors: Jeanette Lyerly, jeanette_lyerly@ncsu.edu; Nonoy Bandillo, nbbandil@ncsu.edu
Lyerly, Jeanette
The Uniform Southern Soft Red Winter Wheat Scab Nursery gives public and private sector breeders the opportunity to obtain valuable data from multi-environment evaluations of FHB resistance for advanced generation breeding materials. The 2025 nursery was comprised of 54 entries, including three resistant checks ‘Ernie’, ‘Bess’, ‘Jamestown’, and two susceptible checks ‘Coker 9835’ and ‘SS8641’. Seven U.S. public programs (Georgia, Louisiana, North Carolina, South Carolina, Texas, Virginia, and Maryland), and one private company (KWS) submitted entries. Field data were collected for the FHB traits Rating, Severity, Incidence, Index, FDK, and DON for breeding lines and compared with data from the long-term resistant check varieties. Data were also collected on important agronomic characteristics, including heading date and plant height. Field data were collected from up to 11 locations in the US. The USDA-ARS Eastern Regional Genotyping Laboratory conducted marker genotyping, identifying alleles for major FHB QTL and other QTL of agronomic importance. Genomic Estimated Breeding Values (GEBV) for nursery entries were provided as part of the continuing evaluation of the FHB training population for the Coordinated Project. The training population was comprised of nursery entries from 2011 to 2024. A combined linear mixed model analysis of the phenotypic data was performed and best linear unbiased estimates (BLUEs) for each genotype were calculated. The genomic prediction model utilized phenotypic BLUEs and 45,695 SNP markers to predict GEBVs for individuals in the 2025 nursery with the R-package RR-BLUP (v 4.6.3). Predictive ability was calculated using Pearson correlation between GEBVs and BLUEs for the 2025 entries. Predictive abilities from 0.57-0.58 were observed for FHB 0-9 Rating, FDK, and DON. Machine learning models were used to provide estimates of presence/absence for 34 QTL of interest. Additionally, a new set of crosses were simulated among the 2024 and 2025 nursery entries using the R package PopVar (v 1.3.1) and estimates of progeny performance were reported. The full 2025 report will be available online at the USWBSI web site at https://scabusa.org. Acknowledgement and disclaimer: This material is based upon work supported by the U.S. Department of Agriculture, under Agreement No. 59-0206-4-046. This is a cooperative project with the U.S. Wheat & Barley Scab Initiative. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.
© Copyright
2025 by individual authors. All rights reserved. No part of this abstract or paper publication may be reproduced without prior permission from the applicable author(s).