One of the most consistently important visual grading factors across crop types is broken kernels. Whether you’re evaluating wheat, lentils, or soybeans, broken kernels impact everything from processing efficiency to overall grade. 

“I really enjoy that I get to learn from both sides of the process,” she says. “One week I might be in the lab, learning about grain composition, and the next I’m working on annotations and understanding what different types of damage or characteristics look like in each crop.” 

As more technology enters this space, one thing we’ve learned is that conversations around grain quality sometimes misses an important distinction. Detection is not the same as grading. 

Bringing artificial intelligence into agriculture is exciting, but it also comes with real-world challenges. It is one thing to build powerful tools, and another to introduce them into an industry where experience, trust, and hands-on knowledge matter deeply. 

It’s a system designed to support the real demands of grading, not just automation for the sake of it, but a more efficient way to reach grading decisions faster, with less variability. 

Grain grading goes beyond just visual inspection—some of the most important quality factors lie beneath the surface. One of the most essential of these is moisture content, a key indicator that affects everything from marketability and storage to milling and processing efficiency

“Having worked in the grain industry for a long time, I knew the need for this kind of solution,” she shares. “When I first heard about what Ground Truth Ag was doing, I was really excited. I wanted to be involved in any way I could.” 

Jatin’s journey to Ground Truth Ag started long before he set foot in the lab. Back in India, he grew up on a farm where his family raised wheat, pulses, and vegetables. His dad, a farmer himself, passed down both knowledge and curiosity.

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.

Grain grading is a critical step in determining market value, processing quality, and end-use performance. Among the many grading factors assessed, Degree of Soundness (DOS), Hard Vitreous Kernels (HVK), and Wheats of Other Classes (WOOCs) play a crucial role across the entire grain supply chain—from farmers and grain handlers to millers and exporters. 

Bruno’s journey into AI-powered grain grading started with a deep passion for chemical analysis and real-time measurement technology. With a PhD in Chemistry from the University of Victoria, he specialized in developing analytical methods and integrating machine learning into chemical analysis—a skill set that perfectly positioned him for the work we do at Ground Truth Ag. 

While all grains contain some level of protein, the type and amount vary significantly based on genetics, environmental conditions, and agronomic practices. 

Grain quality is a key factor in determining market value, processing efficiency, and end-product performance. From farm to processors to destinations, we all rely on accurate and consistent grain grading to make informed decisions.

Nathaniel’s journey with Ground Truth Ag began at Saskatchewan Polytechnic’s Digital Integration Centre of Excellence (DICE), where he worked on an applied research project supporting our machine learning development.

Grain grading is one of the most critical yet complex processes in the agricultural supply chain.

Grain grading has always been a blend of science and skill, relying on measurable characteristics like moisture, protein content, and physical appearance to determine quality.

Grain grading is more than just a technical process—it’s an art that requires experience, skill, and a keen eye for detail. While science provides the framework, grain graders rely on visual assessment, comparisons, and judgment to determine quality.

We are excited to share that our benchtop MV/NIRS system now includes grading for red lentils and soybeans.

Meet Christian Miranda, a dedicated Grain Data Collector at Ground Truth Ag.

We’re excited to share some big news: We’ve partnered with CLEWS Management to bring our benchtop MV/NIRS grain grading technology to farmers and grain buyers across Canada.