Byron Evers

This study uses high-throughput phenotyping and genomic prediction to assess and improve barley yellow dwarf resistance in wheat.

Genotyping of gene bank collections of diploid A-genome relatives of wheat uncovered relatively higher genetic diversity and unique evolutionary relationships which gives insight to the effective use of these germplasm for wheat improvement.

This study evaluates the economic benefits of genomic selection in a winter wheat breeding program by analyzing prediction accuracy, genotyping costs, and heritability levels.

This paper uses deep learning to score wheat morphology and flowering time from field images, revealing novel genetic interactions and heritable flowering rates.