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Poster # 515
Poster Title: The 2024 Uniform Southern Soft Red Winter Wheat Scab Nursery
Authors: Jeanette H. Lyerly 1, J. Paul Murphy 1, Gina Brown-Guedira 2, 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
Corresponding Author: Jeanette Lyerly, jeanette_lyerly@ncsu.edu
Presenting Author:   Jeanette Lyerly



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 2024 nursery was comprised of 54 advanced generation lines, 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. Data were collected for the FHB traits Rating, Severity, Incidence, FDK, and DON for breeding lines and compared with data from the long-term resistant check varieties. Data were also collected on important fungal and viral diseases, Hessian fly resistance, and agronomic characteristics. Field data were returned from up to nine locations in the US. Two USDA-ARS laboratories conducted evaluations for Hessian fly resistance and marker genotyping. Genotyping analyses for major QTL identified alleles present at 19 important loci. 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 2023. A combined mixed model analysis of the phenotypic data was performed using R (v 4.3.2) and best linear unbiased estimates (BLUEs) for each genotype were calculated. The genomic selection (GS) model utilized phenotypic BLUEs and 37,041 SNP markers to predict GEBVs for individuals in the 2024 nursery with the R-package RR-BLUP (v 4.6.3). GS model accuracy was evaluated by Pearson correlation between GEBVs and BLUEs for the 2024 entries. Correlation varied between 0.38 for DON and 0.69 for FHB 0-9 Rating. Machine learning models were used to provide estimates of presence/absence for 34 QTL of interest. Additionally, crosses were simulated among the 2023 and 2024 nursery entries using the R package PopVar (v 1.3.1) and estimates of progeny performance were reported. Copies of the full report will be available at the 2024 National Fusarium Head Blight Forum and subsequently 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. 59-0206-2-136. 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.