A cutting-edge computer vision system utilizing high-resolution microscopy and deep learning to non-invasively classify plant ploidy. This system offers high-throughput, cost-effective ploidy detection without the need for tissue sampling, enabling efficient crop improvement.
The AI-driven profiling system presents a groundbreaking method for non-invasive ploidy detection in plants, specifically designed for hexaploid wheat DH populations. Utilizing high-resolution microscopy paired with advanced deep learning algorithms, this technology classifies plant ploidy based on cell size, density, leaf thickness, and stomatal characteristics. By generating a "Ploidy Probability Score," the system enables high-throughput and cost-efficient sorting of thousands of samples daily, eliminating the need for traditional tissue sampling and extraction processes.
Key features:
This system is at TRL 9, having completed all development stages and achieved high recall rates (>95%) for detecting 2N lines. It is ready for widespread adoption and integration into agricultural imaging pipelines, offering a reliable and efficient tool for crop improvement.
Hampton University is a mid‑sized private, historically Black university in coastal Virginia that combines research activity with strong professional preparation. Industry collaborators engage co‑located clinical capabilities through a campus‑based proton therapy institute and applied laboratories that support prototyping, testing, and validation. The campus sits within the Hampton Roads innovation corridor, offering proximity to major federal research laboratories, shipbuilding and port operations, and a dense network of aerospace and defense contractors for internships, joint development, and rapid piloting. Research is supported by competitive federal funding, including awards from agencies such as NSF, NIH, DoD, and NASA. A dedicated technology transfer office provides IP management, industry contracting, and startup support.