Swedish University using Specim Hyperspectral to advance real-time crop monitoring
SLU moves crop nutrient testing out of the lab and into the paddock
Maintaining a precise understanding of crop nutrient levels is absolutely vital for driving sustainable, high-yield crop growth. However, the industry has long been held back by traditional laboratory testing, which is notoriously slow, destroys the sampled crops, and fails to give farmers a real-time look at how nutrient concentrations shift throughout the growing season.
An initiative called the Hyper-näring project is set to change this. Driven by researchers at the Swedish University of Agricultural Sciences (SLU), the project bridges the gap between complex agronomic science and cutting-edge technology. By deploying Specim’s hyperspectral imaging solutions, the team is successfully transitioning non-destructive nutrient analysis out of sterile laboratories and straight into live agricultural environments.
Historically, checking on crop health meant cutting down plant samples and waiting days for laboratory workflows to return data. While these conventional methods are accurate, their destructive nature makes them non-repeatable and their long cycle time makes frequent testing impossible. This leaves a blind spot when it comes to tracking how multiple nutrients interact over time.
The SLU team focused their research on breaking this cycle. Their goal was to create a reliable methodology for repeated, non-invasive crop scanning across every major growth stage, ensuring the data captured in a controlled greenhouse matches up perfectly with trials conducted out in open paddocks.
The engine behind this breakthrough is hyperspectral imaging, which scans plants across hundreds of narrow wavelength bands to collect rich spectral reflectance data. To build a robust workflow from the ground up, SLU integrated an ecosystem of distinct Specim hardware:
By utilising these systems together, the researchers can gather uniform, comparable datasets across entirely different environments, which is a crucial step for validating their models and turning raw science into practical farming tools.
"Specim’s hyperspectral systems allow us to monitor several nutrients simultaneously without destroying the plant material. This opens entirely new possibilities for understanding nutrient dynamics across growth stages," says Julianne Oliveira, Principal Investigator of the Hyper-näring project at SLU.
The project’s initial findings point to a bright future, successfully isolating specific spectral signatures linked to nutrient levels and tracking their evolution over the season. Because a single hyperspectral scan captures a massive, data-rich full spectrum rather than just measuring a single metric, the value of the data is future-proofed. Long after the physical plants are gone, scientists can revisit the exact same digital datasets to answer entirely new research questions.
Furthermore, this technology looks at the bigger picture of crop performance. The exact same spectral data can be leveraged to monitor broader indicators of plant health, including moisture or climate stress, early disease onset, and overall biomass development. This multi-layered insight makes hyperspectral imaging an incredibly versatile asset for precision agronomy.
While Hyper-näring is anchored in rigorous academic research, its ultimate goals are highly practical. By proving that hyperspectral imaging can transition seamlessly from indoor trials to the unpredictable conditions of a commercial farm, SLU is laying the groundwork for a new generation of smart, on-farm diagnostic tools and automated nutrient management systems.
Through every stage of this research-to-field journey, Specim’s hyperspectral imaging solutions provide the precision, portability, and adaptability needed to turn high-tech imaging into everyday agricultural reality.
Exploring hyperspectral imaging for your applications?
Whether your focus is crop research, precision agriculture, or plant phenotyping, Specim’s hyperspectral imaging solutions enable reliable, non-destructive analysis across environments, from laboratory studies to field deployment.
