Bringing Seed Analysis into the Digital Age with Spectral Imaging

While agriculture often conjures images of drones and driverless tractors, one of the most meaningful innovations is happening at the laboratory bench. Thanks to Videometer’s spectral imaging technology, even the traditionally manual process of seed analysis is entering a new, digital era.

A recent study from Aarhus University and TystofteFonden, driven by Ph.D. Candidate, Martin Himmelboe, explored how artificial intelligence (AI) combined with multispectral imaging can transform how we assess seed quality. Today, trained analysts rely on magnifying glasses, lamps, and years of experience to sort seeds, identify defects, and detect impurities. It’s meticulous work that demands high precision—and often, a lot of time.

Videometer’s technology is designed to augment that expertise. Our spectral imaging captures detailed visual and chemical information from seeds across multiple wavelengths. When paired with AI, this data enables models to accurately classify seeds, identify weed species, and highlight anomalies—all while maintaining the objectivity and repeatability that manual methods can struggle to match.

In practical terms, this means seed analysts can use our technology as a powerful decision-support tool. It helps reduce fatigue from repetitive tasks, acts as a second opinion for uncertain classifications, and allows laboratories to scale up their operations without compromising accuracy.

Himmelboe’s study also points to exciting future possibilities—such as detecting early signs of disease or genetic variation—all from the same imaging data. And with Denmark being one of the world’s top exporters of grass seed, ensuring reliable, high-quality seed analysis isn’t just a technical upgrade—it’s a competitive advantage.

As this field evolves, Videometer remains committed to empowering laboratory professionals with tools that make their work easier, faster, and more impactful. Seed by seed, we’re helping to build the foundation for a smarter agricultural future.