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Oat Mills

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.

 

Models available for

Unhulled Oats
Hulled Oats
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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

Our Technology

Our patented mirror design and high-resolution imaging technology can detect all defects and impurities visible to the human eye, making it a powerful substitute for manual grain grading. Each kernel is captured in a detailed image and analyzed using advanced ANN models, developed by image analysis experts in collaboration with grain specialists. 

The analyse provide comprehensive physical data, including width, length, volume, and color of each kernel while also detecting impurities. At the same time it provides sieving data - all in a single run. Designed for all types of small grains, our durable and user-friendly instrument is a favorite among customers for its reliability, precision, and ease of operation.