Degree Type

Dissertation

Date of Award

2018

Degree Name

Doctor of Philosophy

Department

Agronomy

Major

Plant Breeding

First Advisor

William Beavis

Abstract

Marker technologies have allowed soybean breeding to exploit genotypic information for traits of various genetic architectures. However, the incorporation of technologies have had qualitative impacts on resources used in variety development projects. The objective of this study was to investigate the impact of integrating Marker Assisted Selection (MAS) for single gene and oligo-genic traits and Genomic Selection (GS) for yield in soybean variety development projects through use of simulations, decision classifier metrics, and cost analysis. The breeding goals of the project are to maximize yield of soybean varieties adapted to maturity zones (MZs) II, III and IV, while assuring that the varieties will not lodge and are resistant to Phytophthora Root Rot (PRR) and one race of Soybean Cyst Nematode (SCN). These goals need to be met while minimizing costs. Results show that MAS for PRR and SCN can be implemented with similar efficacy and greater efficiency than traditional phenotypic selection systems. Integration of GS into variety development projects can be as effective as phenotypic selection for yield, but is not as efficient unless the costs of marker assays are less than $4.65 per sample (line).

DOI

https://doi.org/10.31274/etd-180810-6025

Copyright Owner

Andreomar Kurek

Language

en

File Format

application/pdf

File Size

150 pages

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