Rebecca Caroline Ulbricht Ferreira

This study uses genome-wide family prediction to identify markers associated with agronomic traits in Urochloa ruziziensis and links them to molecular mechanisms.

This paper develops the highest-density linkage map for hexaploid Urochloa humidicola, revealing genetic organization, apomixis, and polyploid origins using SNP markers.

This paper develops a joint learning approach to improve genomic prediction in polyploid grasses, achieving over 50% accuracy improvements over traditional methods.

This paper introduces an automated SNP-based method to identify contaminants in polyploid plant progenies using PCA, Mendelian segregation analysis, and clustering, validated on simulated and real data.