Genetic dissection of grain yield and yield component traits in hexaploid spring wheat

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Date

2020

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Montana State University - Bozeman, College of Agriculture

Abstract

Hexaploid wheat accounts for 30% of global grain production, ranking in the top three major food crop species along with maize and rice. Grain yield from hexaploid wheat is an important agronomic consideration for sustainable agriculture. As the human population continues to grow and the amount of farmable land decreases it is imperative that a focus be placed on improving grain yield performance. Grain yield is a quantitative trait and as such improved performance is largely influenced by genetic variation, environment and genotype x environment interactions. Due to the quantitative nature of grain yield the mechanisms of genetic control are largely unknown. The purpose of the presented research was to genetically dissect grain yield and yield component traits in hexaploid spring wheat grown in Montana in order to leverage new understanding to improve Montana germplasm and future breeding programs. This investigation included three research aims: (i) to determine the genetic impact of introgressed durum yield component alleles on hexaploid spring wheat agronomic and end-use quality performance (Chapters 2 and 3); (ii) investigate how resource availability as simulated by plant competition and seed density impacted yield component allele response at four yield component quantitative trait loci (Chapter 4); and (iii) to better understand the mechanism of genetic control of QTn.mst-6B a quantitative trait locus associated with tiller number through high-resolution mapping (Chapter 5). This research highlights the complexity of pleotropic interaction among yield component traits and variability associated with grain yield as impacted by environment and resources availability. Results from the three aims provide a detailed investigation of single quantitative trait loci for use as novel sources of cultivar improvement and increased genetic gain as well as, a better understanding of grain yield and yield component traits.

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