Raegan Hoefler

The research being by done our group is a wonderful mix of genetics, statistics, and plant breeding, and the outcomes are directly applicable to cereal breeding programs. Also, the people in the group are supportive and a pleasure to be around.

The theme of my research is to describe methodologies to increase the genetic gain of desired traits in barley and wheat multi-environment trials (METs) using fewer resources (i.e. land and time). Climate change is attributed as the cause of extreme weather patterns seen in recent years, and it is predicted that the increase in grain yield of economically important crops will slow or even stop. Therefore, it is important to develop and utilize tools that allow breeders to maximize genetic gain of selection in the changing climate while using less resources. The first chapter of my dissertation evaluates existing resource allocation strategies with minimal land requirements to account for plot-to-plot variation within wheat multi-environment trials (METs) which is necessary to produce unbiased estimates of treatment effects and make comparisons among treatments. The second chapter of my dissertation aims to develop and compare methods to allocate resources across environments in a large barley MET in the presence of genotype by environment interaction which needs to be exploited in order for breeders to make effective selections. The objective of the third chapter of my research is to compare strategies for phenotyping and envirotyping a large barley MET and incorporate them into a genomic selection model. The model will optimize both land and time resources as it will allow for the prediction of breeding values in environments where genotypes were not tested. Overall, my research in the development and comparison of resource allocation optimization methods has direct plant breeding applications and will have large implications on agronomic grain research.

Awards

2020-2021 Elwood and Lydia Brickbauer Research Award

Research Interests

• Experimental Design
• Plant Breeding
• Genomic Selection
• Quantitative Genetics

Selected Publications

Hoefler, R., Gonzalez-Barrios, P., Bhatta, M., Berro, I., Nalin, R.S., Borges, A., Covarrubias, E., Diaz-Garcia, L., Gutierrez, L.‡. 2020. Do spatial designs outperform classic experimental designs? Journal of Agricultural, Biological, and Environmental Statistics 10.1007/s13253-020-00406-2