Insect infestations in stored grain can lead to significant economic losses. For grain storage operators, early detection is critical, but traditional methods are often slow or unreliable due to high sampling uncertainty and can’t detect hidden larvae inside the grain
The DODILOG project, co-funded by Interreg North-West Europe, is exploring how Near-Infrared Spectroscopy (NIRS) could offer a fast, non-destructive solution to detect insects in grain, including hidden forms, on a grain flow to increase the sample size and thus reduce sampling uncertainty. This innovative approach could help storage professionals make quicker decisions, reduce losses, and limit the spread of infested batches from one storage site to another.
What is being tested?
The pilot, led by ARVALIS in collaboration with partners across Europe, Belgium (Inagro), the Netherlands (Graansloot Kampen), and Germany (Weser Business Association), is conducting a multi-phase evaluation of NIRS technology, using a spectrometer from Polytec GmbH that enables online analysis directly on the grain flow.
Step 1: Building the detection model
The goal: develop a reliable model to classify grain samples as “infested” or “non-infested” based on their spectral signature. To this end, a calibration database of nearly 1,000 samples will be produced, with each sample described by its spectral signature and quantified in terms of infestation by ARVALIS technicians. A validation database will be created using nearly 150 samples from storage facilities in France, Belgium, the Netherlands and Germany. Each sample is also classified in terms of infestation and associated with a spectrum. This database of real samples will enable the performance of calibrations to be quantified.
Step 2: Validation in real-world conditions
Two 3-month test campaigns are planned at port facilities to assess the technology in operational environments, in partnership with Polytec GmbH, which provides spectrometers.
Where?
This study is being conducted at the ARVALIS station in Boigneville, France, at the experimental grain platform. The port of Zwolle (Netherlands) will also test this technology in real-world conditions.
Figure: Process for developing a model for the early detection of insects in cereals @ARVALIS
Why does it matter to grain storage operators?
If successful, this technology could:
- Enable rapid, non-invasive detection of insect infestations.
- Support earlier interventions, reducing treatment costs.
- Improve quality control of stored grain.
- Provide a decision-support tool for sorting, treating, or marketing grain batches.
Follow the results
The DODILOG project is still ongoing, and the results of the validation campaigns will be communicated at a later date. Grain storage professionals and stakeholders are encouraged to follow updates and outcomes on the official DODILOG website.
This initiative is
made possible through the collaboration of partners across North-West Europe,
with support from Interreg NWE.