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Selection and Characterization of Previously Plant-Variety-Protected Commercial Maize Inbreds

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posted on 02.01.2019 by Travis J. Beckett
The use of genotypic markers in plant breeding has greatly increased in the last few decades. In this dissertation, I report on three topics that illustrate how genotypic marker information can be applied in maize breeding to increase genetic gain. In the fi rst chapter1, I describe how genotypic and phenotypic data can be used to predict the mean, variance, and superior progeny mean of virtual biparental populations. I use these predictions to identify optimal breeding crosses out of a commercially relevant collection of North American dent inbreds. In the second chapter, within the context of early generation maize inbred development, and using a hybrid testcross data set, I report on the change in genomic prediction accuracy as the size of the training set increases and compare the accuracy of different genomic selection models. In the third chapter2, I used a multi-variable linear regression approach known as genomewide association (GWA) analysis to identify particular genetic locations, known as quantitative trait loci (QTL), that are associated with maize in orescence traits.

History

Degree Type

Doctor of Philosophy

Department

Agronomy

Campus location

West Lafayette

Advisor/Supervisor/Committee Chair

Torbert R. Rocheford

Additional Committee Member 2

William M. Muir

Additional Committee Member 3

Mitch R. Tuinstra

Additional Committee Member 4

Mohsen Mohammadi

Additional Committee Member 5

Klaus L. Koehler

Licence

Exports