Agronomy and Horticulture, Department of

 

First Advisor

P. Stephen Baenziger

Second Advisor

Katherine Frels

Third Advisor

Reka Howard

Date of this Version

Spring 4-27-2022

Document Type

Thesis

Citation

Karahan, E. 2022. Evaluating Traits Influencing Hybrid Wheat Seed Production Using a Double Haploid Population Derived from Freeman x Camelot.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agronomy, Under the Supervision of Professors P. Stephen Baenziger and Katherine Frels. Lincoln, NE: April, 2022

Copyright © Emre Karahan

Abstract

Hybrid wheat (Triticum aestivum L.) cultivars are preferred for their advanced agronomic traits such as a yield improvement increase up to 20%. However, hybrid cultivars remain difficult to produce on a commercial scale due to inadequate pollen dispersal, the closed nature of the wheat floret and the high cost of inducing sterility or restoring fertility in cleistogamous wheat. Redesigning parent-specific traits and understanding their potential interactions with related agronomic traits are needed to breed improved male lines in hybrid seed production fields. To better understand the genetic control of anther extrusion (AE), 174 double haploid lines derived from Freeman (excellent AE) x Camelot (poor AE) were visually assessed in three different environments in 2020 and 2021. Genotypic differences within the DH population were found in 2021. The best linear unbiased estimators found approximately normal distributions with low (AD, PH), moderate (GYLD), and high (AE, LODG) coefficient of variations. Pearson’s correlation coefficient results revealed a significant negative correlation (r=-0.39**) between AE and lodging (LOGD). Moderately high broad sense repeatability was calculated (0.66) for AE and other traits in DH population. The contribution of PC1 and PC2 to the total variance were 45.6% and 27.3% respectively and combined explained approximately 70% of the total variance observed in PCA analysis.

Advisors: P. Stephen Baenziger and Katherine Frels

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