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AI Automation for Dal & Pulse Milling

Higher split ratio, fewer rejects, better export grade — AI transforms dal milling economics.

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The Dal Milling Challenge

India mills 25+ million tonnes of pulses annually. The milling process — cleaning, conditioning, dehusking, splitting, polishing — has multiple quality decision points where AI automation dramatically improves output quality and reduces waste. The average Indian dal mill recovers 68-72% dal from raw pulse; best-in-class mills achieve 78-82% with AI optimization.

  • ✓ Optical sorter AI — stone, discolored grain, and foreign material
  • ✓ Moisture conditioning AI — optimal moisture for dehusking yield
  • ✓ Emery roller pressure optimization — split ratio maximization
  • ✓ Grade classification AI — export vs domestic quality separation

Latur & Marathwada: Dal Capital of India

Latur and surrounding Marathwada districts produce and mill the majority of India's tur (arhar) dal — India's most consumed pulse. MNB Research has deep experience in the specific quality requirements and processing challenges of Marathwada dal mills, including the aflatoxin contamination risks in tur that mirror the groundnut problem in Gujarat.

Case Study: Latur Tur Dal Mill

A 200-tonne/day tur dal mill deployed MNB Research AI across sorting, conditioning, and grading operations.

Result: Dal recovery rate improved from 71% to 79%, export grade output doubled, energy cost per tonne reduced 19%

Technology Deployed

  • 🔬 NIR moisture analysis for optimal conditioning
  • 📷 AI optical sorter with grain-level classification
  • ⚙️ Emery roller speed and pressure AI control
  • 📊 Real-time yield dashboard and shift reporting

Ready to Maximize Your Dal Mill Output?

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