Automated Grain Grading for Milling: Enhancing Consistency and Efficiency
For millers, grain quality isn’t just a measurement—it’s the foundation of efficient processing, product consistency, and profitability. The ability to accurately assess grain before milling ensures predictable yields, fewer disruptions, and optimized flour quality. However, traditional grain grading methods introduce challenges that impact milling efficiency and outcomes.
Challenges in Traditional Grain Grading
Subjectivity remains a major concern, as different grain graders may assess the same sample differently, leading to inconsistencies.
Manual inspections rely on small sample sizes, increasing the risk of misclassification. Additionally, grading high-risk factors—such as fusarium, sprouted kernels, HVK (Hard Vitreous Kernels), and ergot—can be inconsistent, affecting quality assessments across the supply chain.
At Ground Truth Ag, we’ve designed an AI-powered automated grain grading system that delivers objective, comprehensive, and real-time assessments to help millers make data-driven decisions.
Real-Time, Actionable Grain Quality Insights
The benchtop MV/NIRS eliminates traditional grading limitations by analysing entire 1-2 kg samples, providing:
Comprehensive Kernel Quality Analysis – Identifies damaged kernels, disease, and contaminants such as fusarium, sprouting, frost or heat stress, ergot, and other grains.
Protein & Moisture Testing – Uses Near-Infrared Spectroscopy (NIRS) to measure key quality factors that impact flour performance and milling efficiency.
Streamlined Sample Processing – Unlike manual grading, which requires extensive handling, automated grading provides complete results in just minutes—just pour the grain into the unit and receive results in real time.
Ensuring Consistency Across Every Load
Grain quality fluctuates depending on factors such as supplier, origin, storage, transportation, and environmental exposure. Without standardized, repeatable grading, these variables introduce uncertainty into milling performance. The benchtop MV/NIRS provides clarity by:
Delivering a complete grain profile before milling begins, ensuring every shipment meets quality expectations.
Measuring key grading factors—including test weight, protein content, and defects—so mills can adjust milling settings accordingly.
Offering predictive processing adjustments, allowing millers to optimize flour yield and quality before inconsistencies arise.
With a standardized grading process, millers gain greater control over procurement and blending strategies. Supplier quality can be tracked over time, ensuring consistency from contract to contract. Seasonal trends and variations become easier to manage, allowing for proactive adjustments to milling strategies. Additionally, a clearer picture of grain characteristics helps maximize processing efficiency, reducing waste and improving overall flour performance.
Minimizing Subjectivity in Grain Grading
Even the most experienced graders assess samples differently, leading to variations in milling outcomes. Our benchtop MV/NIRS removes this subjectivity by applying consistent AI-driven grading models that ensure repeatable, unbiased assessments across all locations and users. By eliminating discrepancies, mills gain more predictable results, reducing inefficiencies caused by inconsistent raw material quality.
A More Transparent & Efficient Future for Milling
As milling operations demand more precision and predictability, AI-powered grain grading is transforming how millers evaluate, source, and process grain. With real-time quality insights, standardized grading, and objective assessments, millers can make informed sourcing and blending decisions, improving product consistency and reducing processing inefficiencies.
Want to see how automated grain grading can optimize your milling operation? Contact us today for a demo!