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ARS Home » Research » Research Project #426883

Research Project: Discovering, Understanding, and Utilizing Wheat Genes for FHB Resistance in Ohio

Location: National Programs

Project Number: 0500-00053-003-094-G
Project Type: Grant

Start Date: Jul 6, 2014
End Date: Jul 5, 2019

Objective:
Project 1 - Discovering, Understanding, and Utilizing Wheat Genes for FHB Resistance in Ohio: Use traditional and molecular breeding technologies in a program that will insure a steady release of FHB resistant cultivars while building parents for future success. Project 2 - Coordinated Phenotyping of Uniform Nurseries and Official Variety Trials: Screen and Evaluate approx. 450 unique advanced breeding lines and released cultivars for FHB resistance. Project 3 - Implementing Genomic Selection for FHB Resistance in Soft Winter Wheat (SWW) Adapted to the Corn Belt: 1) to implement Genomic Selection (GS) for FHB resistance in soft winter wheat by completing two cycles of GS; and 2) initiate evaluation of the effectiveness of GS.

Approach:
Project 1: 1) generate new populations of inbred lines from parents chosen to facilitate recombination of genes from elite and exotic sources for yield, adaptation to Ohio, and resistance to FHB and other diseases; 2) use parents generated by molecular breeding as parents to pyramid QTL for FHB resistance; 3) use best lines in crossing program to initiate backcross and recurrent selection populations; and 4) screen inbred lines for FHB resistance in misted and inoculated FHB nurseries. 5. Evaluate the FHB resistance of the soft winter wheat TCAP elite panel. Project 2: 1) Phenotype advanced breeding lines that are candidates for release: 2) place FHB and other agronomic, disease resistance, and quality data in database: 3) report on purification and seed increase of the best lines. Project 3: Over the past three years the USWBSI has funded the phenotyping of a training population of 649 lines. These 649 lines will be genotyped and use the phenotypic and genotypic data to develop a GS model to predict the value for each FHB traits. The model will then be used to execute two cycles of Genomic Selection (GS) during the duration of this grant.