Diana Solarte

The paper evaluates long-term genomic selection outcomes in Brazilian cassava breeding programs, showing genetic gains and changes in diversity across four selection cycles.

This study compares single-trait and multi-trait genomic prediction models for cassava yield traits, showing that multi-trait models improve predictive accuracy and reduce phenotyping burden.

This study identifies genomic regions associated with carotenoid and dry matter content in cassava using GWAS models, finding six SNPs explaining most of the phenotypic variance.

The paper identifies four genetic variants associated with post-harvest physiological deterioration in cassava using GWAS and links them to genes involved in PPD pathways.