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Redefining Grain Analysis System for Oat Mills Industries - Agriculture
FromCgrain AB
Cgrain’s advanced AI models use high-resolution imaging and machine learning to evaluate each oat kernel. The system classifies and quantifies a wide range of parameters critical to oat processors.
Most popular related searches
crop seed
industrial agriculture
grain analysis
grain quality monitoring
sprout damage
seeding
agriculture industry
seed crop
chaff
cereal
Traditional visual inspection methods are time-consuming and subjective. With AI-powered ocular analysis, you gain reproducability, objectivity, and traceability—kernel by kernel. Cgrain can meassure a range of parameters, here are an example of some of them:
- Unhulled Oats : Sound, shriveled, dark, insect-damaged, sprouted
- Hulled Oats : Sound, shriveled, dark, insect-damaged, sprouted
- Additional categories : Broken Hulled Oats, Double/Triple Oats, Hull in Hull
- Other Cereals : Wheat, barley, rye
- Organic Material : Weed seeds, impurities, chaff, ergot, insects, other crop seed
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