Diego Jarquin

Dr. Diego Jarquin is an Assistant Professor at the University of Florida, specializing in the integration of artificial intelligence (AI) and multi-omics data into plant breeding. His research focuses on developing interpretable AI methods and quantitative genetics approaches to address complex challenges in crop improvement, such as enhancing productivity and resistance to biotic/abiotic stresses. Key areas include genomic prediction, high-throughput phenotyping, and leveraging enviromics (environmental omics) for trait dissection.

His work emphasizes practical applications, such as improving wheat, soybean, maize, and cassava through advanced computational tools like CHiDO—a no-code genomic prediction software. He also investigates genotype-by-environment interactions and machine learning-driven solutions for crop adaptation to climate variability. Recent projects include UAV-based hyperspectral imaging for trait prediction, sparse testing designs for resource-efficient breeding trials, and genomic selection models for disease resistance.

Dr. Jarquin’s methodologies bridge data science and agriculture, aiming to accelerate genetic gains in crops critical to global food security. His interdisciplinary approach combines biostatistics, bioinformatics, and agronomy to tackle multifaceted problems in plant breeding.