PHOENIX LX4‑B4 Series High‑End Intelligent Visual Sorter Single‑layer Belt Model

Single‑layer belt model custom‑built for IQF frozen raspberry sorting, engineered to the highest hygiene standards. Powered by AI‑enhanced ultra‑high‑resolution RGB camera system, it accurately rejects surface defects and foreign materials, with sorting accuracy continuously improved via deep‑learning iteration.

Sorting IQF frozen raspberries presents unique challenges distinct from fresh berries. Raspberries feature soft texture and fine surface trichomes; fruits tend to crack under low‑temperature conditions. Manual sorting brings heavy labor intensity, while finger contact causes thawing and sticking, resulting in high escape rates. Surface frost and inter‑fruit ice adhesion obscure critical defects such as dark‑red spots, mildew, softening and collapse, which are barely identifiable by conventional vision technologies. In addition to frozen clumps and stuck defective fruits (e.g. double fruits, fragment agglomerates) further complicate sorting. Traditional solutions show clear limitations: manual sorting suffers low efficiency and inconsistent quality in cold working environments; air separation and gravity sorting only work on size, weight and density, and cannot detect color deviations, surface damage, calyx residues or foreign contaminants.

The PHOENIX LX4‑B4 Series is an intelligent visual sorting system custom‑tailored for industrial‑grade sorting and quality control of premium IQF frozen raspberries, built to top‑tier hygiene specifications. Equipped with ultra‑high‑resolution RGB imaging and self‑developed AI algorithms, it adapts to the physical properties of bulk IQF raspberries. Even under frost‑obscured conditions, deep‑learning models reliably identify raspberry‑specific dark‑red mildew spots, partial softening and flesh breakages. Morphology, texture and edge feature analysis distinguishes same‑color foreign matter such as leaves and stems, and intelligently detects frozen clumps and adhered defective produce. Through high‑speed visual inspection and precise ejection, the system efficiently sorts out color variations, surface damages, foreign contaminants and clumped berries, improving the uniformity and purity of finished products. It delivers a more efficient, reliable and quantifiable solution for IQF frozen raspberry processing.

AI‑powered surface defect recognition algorithms are trained on real‑world production datasets via deep learning for continuous sorting‑accuracy enhancement. They help processors upgrade product quality, boost throughput and cut labor costs to sustain competitive advantages in the marketplace.

• Industrial‑grade visual sorting system custom‑designed for IQF frozen raspberries
  • Compact single‑layer belt sorting unit with quick‑install design
  • Multiple high‑performance waterproof vibratory feeder options, customizable for raspberry varieties (red, black, yellow raspberries) and fruit sizes. It ensures uniform single‑layer material distribution and minimizes overlapping as well as crush‑caused damage.
  • Food‑grade stainless‑steel construction. Sealed sorting chamber and electrical cabinet withstand frequent high‑pressure washing and sanitization cycles.
  • Quick‑release belt and round‑tube frame eliminate sanitary dead corners, enabling convenient daily maintenance and cleaning to meet stringent food‑safety requirements.
  • Built‑in humidity control system stabilizes equipment operation and reduces downtime.
  • 1200 mm and 1800 mm belt‑width variants offer great flexibility to match diverse throughput requirements for processors.
• AI‑empowered ultra‑precision surface‑defect inspection system
  • Self‑developed AI algorithms strengthen surface‑defect detection. Model retraining based on real production data enables continuous sorting‑accuracy optimization via deep learning.
  • Ultra‑High‑Resolution RGB (UHR‑RGB) imaging captures subtle discoloration, softening blemishes and trichome loss on raspberry surfaces, achieving detection sensitivity beyond human eyesight.
  • High‑brightness LED illumination guarantees sharp and consistent imaging.

Ultra‑high‑precision visual inspection for multiple defects on IQF frozen raspberries based on surface characteristics:

• Color defects: discoloration, dark‑red mildew spots, partial browning, rot
• Morphological defects: malformation, softening & collapse, breakage, fragmentation, undersized fruits, double fruits
• Surface damage: abrasion, indentation, freeze cracks, calyx residues, juice exudation
• Biological contaminants: insect infestation, leaf/stem residues, residual fragments of other berries, soil particles
• Foreign‑body inclusions: stones, plastic/rubber fragments, wood chips, packaging threads

• High‑performance pneumatic ejector system
  • Optimized design balancing durability, response speed and air‑consumption efficiency
  • Delicate ejection suitable for fragile raspberries, maintaining accurate rejection and stable performance under high‑throughput operation
  • Greatly reduces false‑reject rate and lowers overall operating costs
• 15‑inch industrial touch‑screen control system
  • Intuitive HMI with multi‑language support
  • One‑click parameter switching for different raspberry varieties
  • Comprehensive remote‑support suite
    • Remote access & real‑time monitoring
    • Performance data dashboard
    • Online expert diagnostics
    • Interactive troubleshooting