Keith A. Gardner

The paper introduces the Desired Gains Index as an optimal method for parent selection in plant breeding, demonstrating its effectiveness through simulations and comparisons with other strategies.

The paper uses multi-trait genomic prediction models and simulations to show that complex trait genetic architecture improves long-term genetic gains in wheat breeding.

This paper enhances multi-year genomic prediction of wheat breeding data by integrating environmental associations (EPA) to improve genotype-by-environment interaction predictions.

This paper uses EnvGWAS and EigenGWAS on historical wheat and barley varieties to identify genomic regions under selection without phenotyping, finding 16 barley and 10 wheat regions with adaptation-related introgressions.

The paper analyzes haplotype diversity and genetic associations in wheat breeding lines to understand polygenic trait architecture and breeding implications.