Ismail Yusuf Rabbi

This study shows that monoculture selection captures most intercrop yield gains in cassava, but targeted testing with cowpea varieties is still needed for effective intercropping breeding.

This study evaluates UAV-derived canopy traits in cassava to assess their repeatability and heritability across two growing seasons, finding high repeatability but variable heritability among traits.

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.

This paper uses bivariate genome-wide association study to investigate the genetic architecture of the negative covariance between total carotenoid and dry matter contents in cassava, finding polygenic mediated pleiotropy rather than genetic linkage.

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.

The paper develops genomic mate selection criteria for outbred species, demonstrating accurate prediction of genetic variances and covariances in cassava to improve breeding outcomes.

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.

The paper identifies genetic loci associated with cyanide content in cassava, finding two major genes contributing to HCN levels and developing markers for breeding.

This study uses image analysis and genome-wide association to identify QTLs for cassava root shape and size traits, finding lower predictive accuracy compared to other traits but promising for high-throughput methods.

The paper identifies beneficial introgressed alleles from M. glaziovii in modern cassava germplasm, showing they improve traits like yield and disease tolerance and are under balancing selection.

This study compares univariate and multivariate genomic prediction models for cassava traits, finding that multivariate models improve prediction accuracy in both single and multi-environment evaluations.

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

This paper identifies genetic markers for dry matter and carotenoid content in cassava, finding physical linkage rather than pleiotropy explains their negative correlation.

The paper constructs a cassava haplotype map to evaluate deleterious mutations, finding increased fixed deleterious variants, limited purging due to low recombination, and masking of harmful mutations in breeding.