Nicholas Santantonio

The paper analyzes historic wheat trials to show how vrn1 and Ppd1 alleles affect yield through environmental interactions, finding that vrn1 effects are more variable than Ppd1 effects.

This study demonstrates that genomic selection can predict glycosidic nitrile content in winter barley during the same growing season, enabling earlier breeding decisions.

This study uses multi-spectral imaging to estimate genetic parameters of biomass accumulation and model growth curve stability in alfalfa across different irrigation treatments and cultivars.

The paper improves genomic prediction of agronomic traits in maize by integrating spatio-temporal modeling of multi-spectral aerial images with genetic data.

The paper estimates the yield effects of awns in wheat under different environmental conditions over 12 years in the Southeast US, finding awns improve yield in heat-stressed environments.

The paper proposes a hybrid optimal contribution approach to balance short-term genetic gains with long-term sustainability in plant breeding programs.

The paper develops a subfunctionalization epistasis model to assess homeologous gene interactions in allopolyploid wheat and evaluates their contribution to genetic variation.

The paper introduces a low-resolution epistasis mapping method to detect chromosome arm interactions in allohexaploid wheat, finding significant epistatic interactions for 2% of tested pairs.

The paper presents a statistical framework to predict subgenome additive and interaction effects in allohexaploid wheat, showing reliable variance estimation and comparable predictive ability to existing methods.