Seed quality is not just a technical matter – it defines the value of entire seed lots. At Siemen Forelia, X-ray imaging brings speed and accuracy to seed quality assessment, with a direct impact on both efficiency and end results.
A few kilometers outside Rovaniemi, in northern Finland, a seed center operates in a quiet, remote setting – yet its impact reaches far beyond. At the Imari facility, forest tree seeds are processed, stored and packed before being sent to nurseries and forest owners, and eventually into new forests.
“Our core work includes a bit of everything: packing seeds, running germination tests in the laboratory and X-ray imaging of the seeds,” says Anu Kyllönen, who works at the seed center.
Siemen Forelia is the leading producer of forest seeds in the Nordic region, and the quality of those seeds has a direct influence on forest regeneration outcomes.
Visible on the outside – unknown on the inside
Assessing seed quality is not straightforward. A seed may look good on the outside, while being empty or damaged inside. Without X-ray imaging, quality assurance relied largely on trusting the process, with results only visible later.
“The result was only confirmed through germination testing, which takes two to three weeks,” Kyllönen explains.
If there were issues in a seed lot, they only became visible with a delay – affecting both operational efficiency and final quality.
X-ray brings visibility inside the seed
The seed center had previously used X-ray equipment, but it had been taken out of operation due to breakage. When the system was upgraded and brought back into use with Innomentarium’s SeediX solution, the situation changed significantly.
“It was great to get the system back in use – it has made a big difference! Now we can see within minutes how well we have succeeded in our work,” Kyllönen says.
While the technology has brought speed to the process, part of the work still remains hands-on. Seeds are placed into Petri dishes or onto film sheets, and individual samples are carefully prepared before imaging. A single analysis can still involve handling hundreds of seeds. At the same time, a new perspective has been introduced – quite literally.
“Manual work has not disappeared, but using X-ray imaging, information about seed quality can be get within minutes. From the X-ray image, we can determine whether a batch meets the required quality or whether additional cleaning is needed,” Kyllönen explains.
Moving towards automated analysis
With X-ray imaging now in place, the next question is clear: can the analysis itself be automated? Artificial intelligence is seen as a promising future solution, particularly for repetitive and precision-driven tasks.
“If AI could calculate something like the germination rate, it would make our work much easier,” Kyllönen notes.
The idea is simple: reduce manual work and introduce more systematic analysis. As images are increasingly interpreted, seeds begin to generate data – and that data begins to guide decision-making.
Collaboration that supports daily work
Introducing new technology does not solve everything. Everyday work still determines success. When processes stop or something goes wrong, what matters most is how quickly things move forward again.
“It’s easy to get in touch with the Innomentarium team, and we always get help quickly,” Kyllönen says.
Collaboration with the Innomentarium team is visible in daily operations: from using the equipment to resolving issues and adopting new ways of working. Support does not stay in the background but becomes part of everyday work when needed.
When quality defines value
For seeds, quality is not just a technical characteristic – it has direct economic meaning. For example, the germination rate determines how a seed lot can be used and what value it holds. When quality can be assessed faster and more accurately, the impact extends across the entire value chain.
A seed may look small and simple from the outside, but its significance is far-reaching. When we can see inside it, decisions are based on certainty – and that value is ultimately realized where it matters most: in the forests.