Degree Type

Thesis

Date of Award

2020

Degree Name

Doctor of Philosophy

Department

Agronomy

Major

Plant Breeding

First Advisor

Michael Lee

Abstract

Zinc (Zn) deficiency is a global health problem particularly in low- and middle-income countries where diets are cereal-based and typically lower in Zn. Biofortification, the genetic enhancement of staple foods through plant breeding is considered cost-effective and sustainable. Maize is one of the major crops grown and consumed in the regions where Zn deficiency is prevalent. But Zn concentration in maize kernels is insufficient to meet the requirements of humans. Therefore, breeding varieties with increased Zn concentration is an important goal for maize breeders.

To breed Zn-biofortified varieties, it is imperative to identify germplasm with high-Zn concentration, assess their potential for grain yield and other important traits, and develop knowledge-based strategies for artificial selection. Two separate studies were conducted to assess the potential of improving maize adapted to the tropics for kernel Zn concentration.

Study 1: Twenty elite inbred lines (10 quality protein maize (QPM) and 10 non-QPM) were systematically mated using a modified mating design. The generated hybrids were evaluated for kernel Zn, grain yield and flowering time in field experiments across four environments. Statistical analyses with respect to the mating design were implemented and hybrids with high-Zn and grain yield were identified. General combining ability (GCA) effects for Zn concentration were more preponderant than specific combining ability (SCA) effects, suggesting the importance of additive gene action for kernel Zn inheritance.

Study 2: An association mapping panel and two bi-parental populations, evaluated for Zn concentration in three environments were used to assess the feasibility of genomic prediction for kernel Zn. Two distinct cross-validation schemes (CV1 and CV2) simulating two genomic prediction breeding scenarios were used to estimate the prediction ability (rMP) for Zn. Prediction accuracy values ranging from 0.51 to 0.71 were observed indicating the potential of genomic prediction for biofortification breeding to enhance Zn concentration in tropical maize germplasm.

DOI

https://doi.org/10.31274/etd-20200624-114

Copyright Owner

Edna Kemunto Mageto

Language

en

File Format

application/pdf

File Size

130 pages

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