Rohit Kumar

This study improves genomic prediction of stalk lodging resistance in maize by integrating multi-environment data, showing that multi-environment models significantly enhance prediction accuracy for most traits.

This study identifies novel metabolic and genetic factors associated with leaf senescence in maize through temporal analysis of physiological and metabolic changes.

The paper identifies 11 intermediate phenotypes related to stalk lodging resistance in maize and develops a high-density phenotypic dataset to enable genetic analysis and improve resistance.

The paper identifies genetic factors influencing maize rind strength through divergent selection and transcriptome analysis, revealing key genes and pathways related to cell wall composition.