This intelligent rice color sorter is specially designed to detect internal defects in rice. It adopts advanced SHD Ultra-HD Imaging Technology and Internal Microscopic Identification Technology, combined with a dedicated rice internal quality analysis large model, enabling efficient and precise identification and removal of internally sprouted grains, diseased grains, moldy grains, immature grains, as well as brown rice, yellow rice and other discolored grains.

The machine is widely used in grain trading, warehousing management and rice processing. A single sorting pass meets the quality standards for warehousing and brown rice processing.

Equipped with hundreds of professional image recognition algorithms and the 3rd-generation multispectral confocal imaging technology, the equipment conducts all-round, multi-dimensional accurate scanning and analysis of materials.

The system intelligently learns and precisely identifies color, shape, texture, area, weight, hardness and other multi-dimensional attributes. It excels in conventional sorting and accurately captures subtle differences under complex backgrounds, greatly improving the detection of discolored, deformed and defective grains.

With continuously optimized recognition models, it adapts to paddy and rice of different varieties, origins and processing stages, meeting diversified production needs and helping enterprises achieve refined quality control.

Based on a massive sample database and powerful computing platform, the equipment quickly builds and continuously optimizes deep learning-based sorting models.

The system automatically learns and memorizes the optical, structural and defect characteristics of different materials, effectively solving complex foreign matter and defect recognition challenges that traditional algorithms struggle with — such as tiny mold, translucent lesions and local discoloration.

As usage data accumulates, the sorting model iterates and upgrades, improving both accuracy and efficiency. It maintains outstanding performance for diversified, high-volume and high-precision production, greatly reducing manual re-inspection costs and enhancing line automation and intelligence.

An open cloud interactive storage platform integrates rich sorting data and industry solutions, forming an ever-expanding cloud shared knowledge base.

Users can access the latest sorting models, process parameters and application cases in real time via the cloud, realizing cross-region and cross-equipment knowledge sharing and technical collaboration.

The system supports remote diagnosis, online upgrade and data retrospective analysis, helping users unlock production data value, optimize sorting processes and improve operational efficiency. The continuous growth of the cloud knowledge base boosts single-machine performance and supports the intelligent transformation of the entire industry.

Leveraging multi-level and multi-dimensional image processing and the cloud data system, the system completes image recognition modeling for complex scenarios and continuously optimizes algorithm performance via a powerful open data chain.

Fusion modeling effectively handles challenging working conditions including lighting changes, material overlapping and background interference, ensuring stable performance in harsh environments.

Through multi-source data fusion and model collaboration, the system adaptively adjusts recognition strategies, accurately distinguishing normal grains from defective ones and significantly reducing false and missed rejection rates. It easily handles high-impurity raw grain sorting and high-precision finished rice purification, providing users with stable and reliable sorting assurance.

The Z Series Rice Color Sorter is suitable for various rice processing enterprises, as well as grain collection & storage, trade circulation and seed selection.

It supports flexible switching of multiple sorting modes to meet customers’ diverse requirements for accuracy, output and cost. A one-time investment delivers long-term benefits, helping users enhance product added value, strengthen market competitiveness, and achieve both economic benefits and brand value growth.