Michael C. Tross

This study uses 3D reconstruction from 2D images to measure phyllotaxy in sorghum, showing its feasibility for genetic analysis and breeding.

The paper uses image analysis models to quantify seed color in sorghum, finding they outperform human assessment and identify more genomic signals linked to seed color genes.

This study uses data-driven methods to analyze hyperspectral leaf reflectance data from maize plants, identifying genetic markers correlated with reflectance patterns and chlorophyll content.

The paper uses a transformer model to predict gene expression patterns across plant organs and identifies regulatory regions in maize and sorghum genomes.

The paper predicts grain yield using non-yield traits and shows that a trait-based model performs comparably to genomic prediction models in cross-environment settings.

This study identifies genetic loci in sorghum that influence human gut microbiome composition through in vitro fermentation of grain.