Elena A. Dzyubenko

This study evaluates MTME genomic prediction models for Miscanthus sacchariflorus, finding they improve prediction for some traits but not all, depending on the cross-validation scenario.

This study evaluates sparse testing designs for genomic prediction in Miscanthus breeding to reduce phenotyping costs while maintaining predictive accuracy.

This study optimizes genomic prediction in Miscanthus sacchariflorus by incorporating weather data to improve model performance across different locations.

The paper evaluates cross-validation schemes for genomic selection in perennial Miscanthus species, showing improved predictive ability by incorporating genotype-by-environment interactions.