Michael J. Burns

This study identifies compositional and morphological traits of maize kernels that predict pericarp retention during nixtamalization using stain-based scoring and correlation analysis.

This paper improves simulation accuracy for digital breeding by integrating GWAS-derived genetic architecture into trait simulations, achieving high concordance with empirical data.

This study shows nixtamalization moisture content can be selected early in maize breeding using genomic prediction and NIR spectroscopy, with no significant correlation to yield.