At The Rocinante Lab, we integrate cutting-edge technologies, including molecular genomics, phenomics, physiology, pathology, statistics, and breeding, to develop innovative strategies for creating superior crop varieties. Our research emphasizes genomic prediction and selection, association mapping, and the characterization of allelic diversity. Expanding our global perspective, leverage advanced machine learning and artificial intelligence methodologies to enhance the accuracy and efficiency of our breeding programs. By focusing on optimizing the selection and mating of individuals, we aim to accelerate genetic gains and improve trait performance across diverse environments.
Our work encompasses a variety of crops, including small grains, sunflower, and berries, reflecting our commitment to addressing global food security challenges through interdisciplinary and data-driven approaches.
