Susanne Dreisigacker

A novel matrix multiplication framework for modeling genotype-by-environment interaction in genomic prediction

This paper introduces a matrix multiplication framework for genotype-by-environment interaction in genomic prediction, showing improved accuracy over traditional methods.

Homoeo-alleles of wheat GNI2 fuel grain yields across input environments

This study identifies GNI2 homoeo-alleles in wheat that improve grain yield by 5-15% across high- and low-input environments.

Development of a Next Generation SNP Genotyping Array for Wheat

The paper develops a high-density SNP genotyping array for wheat using whole genome skim sequencing and a novel optimization approach, showing improved performance in GWAS and CNV analysis.

ENVIROME-WIDE ASSOCIATIONS ENHANCE MULTI-YEAR GENOME-BASED PREDICTION OF HISTORICAL WHEAT BREEDING DATA

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

Regularized selection indices for breeding value prediction using hyper-spectral image data

The paper develops regularized selection indices to improve breeding value prediction using hyper-spectral image data, showing higher accuracy for grain yield than traditional methods.

Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

This study uses hyperspectral reflectance-derived relationship matrices in genomic selection to predict grain yield in wheat, showing improved accuracy when combined with marker and pedigree data.