Siraj Ismail Kayondo

The paper analyzes a cassava introgression from M. glaziovii, finding no direct effect on dry matter but segregation distortion and minor effects on vigor.

This study identifies genetic loci associated with branching traits in cassava, showing their genetic tractability and potential for genomic selection in breeding programs.

The paper evaluates a cassava crop growth model by calibrating it with multi-environment trial data, finding improved predictions but persistent biases in dry and wet environments.

The paper validates SNP markers for marker-assisted selection in cassava to improve carotenoid and dry matter content, showing high correlation for carotenoids but lower for dry matter.

This study performs a genome-wide association analysis on cassava to identify genetic loci associated with defensive, agro-morphological, and quality traits, uncovering 41 significant associations and candidate genes.

This study identifies genomic regions associated with CBSD resistance in cassava using genome-wide association mapping and genomic prediction models.

The paper evaluates genomic prediction models for Cassava Brown Streak Disease using transcriptomics and GWAS data, finding only marginal improvements in prediction accuracy.

This study evaluates genomic selection accuracy in cassava breeding across different prediction models and scenarios, finding that training population size significantly impacts accuracy.