Hyperspectral Sensing Lab

The ILVO Hyperspectral Technology Facility enables advanced applications in agri-food processing, such as quality control, defect detection, grading, and sorting of (raw) products. By comparing spectral and spatial data to reference measurements, we build chemometric models capable of estimating product parameters in real time. The facility hosts a range of hyperspectral and multispectral devices, including spectrometers with customisable probes, hyperspectral cameras, and FTNIRS systems suited for both solid and liquid samples. Using these technologies across various wavelengths, we evaluate the feasibility of hyperspectral analysis for specific applications. Furthermore, data can be resampled to test and validate the performance of other multispectral devices in more challenging environments outside our lab. The facility supports a complete workflow from data collection to model output and offers support for integrating hyperspectral technology into new or existing machinery.

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Description

The ILVO Hyperspectral Technology Facility enables advanced applications in agri-food processing, such as quality control, defect detection, grading, and sorting of (raw) products. By comparing spectral and spatial data to reference measurements, we build chemometric models capable of estimating product parameters in real time. The facility hosts a range of hyperspectral and multispectral devices, including spectrometers with customisable probes, hyperspectral cameras, and FTNIRS systems suited for both solid and liquid samples. Using these technologies across various wavelengths, we evaluate the feasibility of hyperspectral analysis for specific applications. Furthermore, data can be resampled to test and validate the performance of other multispectral devices in more challenging environments outside our lab. The facility supports a complete workflow from data collection to model output and offers support for integrating hyperspectral technology into new or existing machinery.

What could be offered through this facility?

- Data acquisition in the lab, under the conveyor belt, and in the field with cameras, probes, and mobile units
- Pilot cases:
- Estimation of quantities:
Regression linked to (chemical, other) lab measurements (quality)
- Classification of samples
- Detection of anomalies, process control
- Linked reference measurements (internal or external depending on the case)
- Detection or irradiation, comparing light in different settings
- Consult for reliable experimental setups