Seed phenotyping
For model and crop plants
NMBU hosts a high‑throughput seed phenotyping instrument based on RGB and NIR technology for non‑destructive analysis and sorting of crops including wheat, barley, oats, peas, and faba beans. At UiO, a high‑precision seed imaging and analysis system enables rapid, non‑destructive phenotyping of model plants and can accurately sort and dispense seeds into tubes, agar plates or multi-well formats. These complementary platforms expand opportunities in genetics research, grain quality assessment, and studies of seed‑borne diseases.
Partners and services
UiO
- High‑precision seed imaging and analysis unit for fast, non‑destructive phenotyping and sorting.
- High‑resolution RGB imaging of individual seeds, enabling accurate measurement of morphological traits such as area, length, width, shape and color.
- Fluorescence sensor for detection of fluorescent proteins in mature seeds.
- Automated planting of seeds onto growth media for precise and repeatable experimental setups.
- Size range 80µm to 3mm
Boxeed
Precision automated seed sorting with high‑quality imaging for phenotyping small seeds, such as for instance Arabidopsis. Developed by Labdeers
RGB and Fluorescence
Imaging of seeds from different angles and detection of Red Fluorescent Protein -marker of CRISPR constructs.
Automated precise seeding to media
Boxeed offer sorting in to predefined tubes, growth medium and multi-well plates
Request service:
NMBU
- High‑throughput seed phenotyping and sorting instrument
- Non‑destructive, single‑kernel analysis using RGB imaging, NIR technology, and machine‑learning algorithms
- Trait detection available for multiple crops:
- Barley: colour, moisture, protein
- Faba beans: colour
- Green peas: colour
- Groats: colour
- Oats: colour, geometry
- Wheat: colour, fusarium damage, geometry, hardness, moisture, protein
Qsorter® Explorer
A high‑throughput phenotyping and sorting system combining RGB, NIR, and machine‑learning analysis for single seeds. for more items. Developed by QualySense.