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  • Wheat Sorting Comparison Test | RGB vs. NIR vs. AI – Performance Review Wheat Sorting Comparison Test | RGB vs. NIR vs. AI – Performance Review
    Aug 15, 2026
    In wheat processing, impurities come in many forms – transparent crushed glass, off-color wheat kernels, black and white stones, long and short straws, and wheat husks are all stubborn contaminants that are difficult to remove completely. They directly affect final product quality and market value.   In this test, we used a uniform set of test materials to conduct a side-by-side comparison of three color sorters with different technological approaches, giving you a clear look at their sorting capability.   Impurity List for This Test   2026 / 08 / 15 Impurity Type Characteristics Transparent crushed glass Colorless and transparent, different material from wheat Black stones Deep black, highly contrasting with wheat White stones Whitish, different shape and material from wheat Black rice Deep black, similar shape to wheat Brown wheat Darker color, same shape and material as wheat Long straws Elongated, yellowish in color Short straws Short straw pieces, different shape and material from wheat Wheat husks Similar size and color to wheat, different material   Test Rules   2026 / 08 / 15   RGB standard model & NIR model: Equal quantities of impurity samples were added. AI HD intelligent model: More impurities were added overall – with transparent crushed glass quantity doubled compared to the other two machines – to increase sorting difficulty. Hardware differences: RGB and NIR models are equipped with SD cameras; the AI model features an HD recognition camera.   Technology Principle & Test Results   2026 / 08 / 15 RGB       RGB Standard Color Sorter (SD camera) Relies on color and shape features to identify impurities. In this test, it successfully removed all impurities, meeting basic production standards. However, due to limited imaging resolution of the SD camera, for impurities with similar appearance to wheat (such as short straws and brown wheat), the judgment threshold had to be widened to ensure removal, resulting in a slightly higher carryover ratio. NIR       NIR Near-Infrared Color Sorter (SD camera + NIR) Adds near-infrared technology to RGB, enabling not only surface color impurity sorting but also identification of materials with internal defects. NIR adds a material property dimension, allowing more accurate recognition of "same-color, different-material" impurities without needing to expand the color threshold – achieving a lower carryover ratio. AI       AI HD Intelligent Color Sorter (HD camera + AI algorithms) As a next-generation high-end model, it is equipped with an HD imaging camera. In this test, we increased the difficulty by doubling the amount of glass impurities – yet it still removed all impurities with precision, demonstrating strong anti-interference capability. The HD camera provides clearer images, and AI algorithms deliver more accurate judgments, with a clear boundary between impurities and acceptable products – making it suitable for most production lines.     All three models deliver complete impurity removal with clean, uniform wheat output. The key differences are in carryover ratio and hardware — pick the one that fits your needs. Welcome for free sample testing — let us customize your ideal sorting solution! ✨
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