Rodrigo Rampazo Amadeu

SimpleMating predicts and optimizes breeding crosses using genomic selection to maximize genetic gain while minimizing inbreeding in simulated maize breeding programs.

The paper develops a workflow to improve linkage map construction from GBS data by evaluating and selecting dataset-independent genotype calling and mapping methods.

This study identifies terpene volatiles as key contributors to blueberry aroma and consumer preference using metabolomics and sensory analysis.

This paper develops software for QTL mapping in tetraploid and diploid diallel populations, demonstrating its effectiveness in detecting QTLs and improving model fit through non-additive effects.

The paper develops a statistical framework for haplotype reconstruction in tetraploid F1 populations and implements it in the software PolyOrigin, demonstrating its effectiveness on a potato dataset.

This paper summarizes genomic prediction strategies for autotetraploid blueberry, showing the importance of model parametrization, sequence depth, and genotype calling for improving breeding efficiency.

The paper introduces fullsibQTL, an R package for QTL mapping in outcrossing species, which considers multilocus genetic maps and different segregation patterns.

This study creates a high-resolution linkage map for autotetraploid blueberry and identifies QTLs for machine harvest traits like firmness and detachment force.

This paper evaluates genomic prediction methods for autotetraploid blueberry using continuous genotyping and relationship matrices, finding marker-based models improve prediction accuracy and reduce computational time.