Elesandro Bornhofen

The paper develops a semi-automated image analysis method for root phenotyping and estimates genomic breeding values for root traits in faba bean and white clover, showing genetic correlations with field yield.

This study predicts single cross performance in perennial ryegrass using genomic models, finding high predictive accuracy for dry matter yield and nutritive quality traits.

This study uses multi-omics data from grass hybrids to identify gene and metabolite networks associated with agronomic traits, finding conserved hubs but limited predictive power of network features.

This study uses random regression models to analyze spatio-temporal genomic data in ryegrass, finding improved prediction accuracy for nutritive quality traits but not dry matter yield.