Reginaldo Massanobu Kuroshu

Multiomic insights into sucrose accumulation in sugarcane

This study uses multiomic approaches to identify genetic variants and genes associated with sucrose accumulation in sugarcane, providing insights for breeding and biotechnology.

A joint learning approach for genomic prediction in polyploid grasses

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

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

The paper uses machine learning to identify genomic regions associated with sugarcane brown rust resistance by analyzing SNP data from full-sib progeny.