Emerging 3D imaging and artificial intelligence technologies could revolutionise the way the beef industry measures carcase yield, providing producers, feedlots and processors with more accurate data than ever before.
That was the message from Cooper Carter, recipient of an Australian Wagyu Association Fellowship and Masters student at Texas Tech University, who presented his latest research at WagyuEdge’27 in April. Cooper is investigating how advanced imaging technologies can be used to more accurately predict retail meat yield in Wagyu and beef carcases.
Speaking to delegates, Cooper outlined how current yield grading systems were developed using measurements and production systems that look very different from those used today. While traditional grading methods provide an indication of expected yield, he believes modern technology offers an opportunity to significantly improve accuracy and deliver more meaningful information back to producers.
Rethinking Traditional Yield Prediction
Much of Cooper’s research focuses on the United States Department of Agriculture (USDA) yield grading system, which predicts the percentage of boneless, closely trimmed retail cuts from a carcase. The system relies primarily on eye muscle area, fat measurements and hot carcase weight.
However, Cooper highlighted research showing that while the system identifies broad trends across populations, it can be considerably less accurate when predicting yield on an individual animal basis. Research conducted at Texas Tech University demonstrated that some carcases graded as lower yielding actually outperformed those graded as higher yielding when true retail meat yield was measured.
This disconnect, he explained, comes from relying on a limited number of measurements to predict the composition of an entire carcase.
“We’re really seeing the limitations of using single-point measurements on a carcase to predict total red meat yield,” Cooper said.
Bigger Carcases, New Challenges
Another challenge facing existing grading systems is the ongoing increase in carcase weights.
Over recent decades, both the US and Australian beef industries have seen steady growth in average carcase size as producers work to improve efficiency and increase beef production. Yet heavier carcases do not always translate to better yields if additional weight is being deposited as fat rather than muscle.
Understanding the point at which animals stop efficiently producing muscle and begin depositing excess fat remains a key challenge for the industry.
“What’s the ideal weight to produce cattle to while maintaining high yield percentages?” Cooper asked delegates.
Looking Beyond the Eye Muscle
One of the key findings highlighted during the presentation was that eye muscle area alone may not be telling the complete story.
Research conducted on beef-on-dairy cattle in the United States found substantial variation in overall carcase muscling despite animals sharing similar genetics and exhibiting similar eye muscle measurements.
The findings suggest that while breeders have successfully selected for larger eye muscle area, there may be opportunities to capture additional information about muscling throughout the entire carcase, particularly in the hindquarter and forequarter.
“Rib eye area is very good for predicting some of the major cuts, but it doesn’t necessarily tell us what the rest of the carcase looks like,” Cooper explained.
The Potential of 3D Imaging
At the centre of Cooper’s research is the use of 3D imaging technology.
Using light detection and ranging (LiDAR) technology, similar to systems used in mapping and autonomous navigation, researchers can create highly detailed three-dimensional models of beef carcases. These models allow measurements of volume, shape, cross-sectional area and overall carcase conformation.
The technology is non-invasive and can be applied without physically altering the carcase, making it attractive for commercial processing environments.
Initial pilot studies involving 3D imaging and machine learning have already demonstrated promising results. While early research involved relatively small sample sizes, Cooper said expanding datasets and advances in artificial intelligence are expected to significantly improve predictive accuracy.
Researchers at Texas Tech have since expanded their database from an initial 40 head to approximately 500 cattle across multiple processing plants. Cooper said the goal is to achieve prediction accuracies well into the 90% range.
AI Unlocking New Opportunities
A major driver behind the technology’s potential is artificial intelligence.
Machine learning systems can analyse enormous numbers of data points generated from 3D scans and identify patterns that would be impossible to process manually. Researchers are also using data augmentation techniques, allowing algorithms to create additional virtual carcase models to strengthen predictive capability.
“AI is really what unlocks the power of this technology,” Cooper said.
Building the Future with CT Scanning
Alongside 3D imaging, Cooper discussed the use of computed tomography (CT) scanning, widely regarded as the gold standard for accurately determining muscle, fat and bone composition.
Researchers at Texas Tech have developed a mobile CT scanning unit that can be deployed at processing facilities. While the technology is not intended for commercial chain-speed grading, it provides highly accurate reference measurements that can be used to validate and refine predictive imaging systems.
The technology also creates exciting opportunities for future Wagyu research, particularly in evaluating intramuscular fat distribution and understanding the unique composition of Wagyu carcases.
Wagyu Collaboration Underway
As part of his Australian Wagyu Association Fellowship, Carter has already begun working directly with Australian Wagyu carcases.
During a recent visit to Australia, he completed 3D scans on approximately 130 Wagyu carcases, creating a valuable dataset that will contribute to future analysis and model development.
The long-term vision is to generate accurate red meat yield predictions that can be returned to producers and incorporated into breeding programs through future Wagyu Breeding Values (WBVs).
Such a tool could provide Wagyu breeders with a powerful new way to select cattle that not only excel in eating quality but also maximise carcase yield and production efficiency
Benefits Across the Supply Chain
Cooper emphasised that the impact of the technology extends well beyond seedstock production.
More accurate yield data could help feedlots better identify optimal feedlot exit points, assist processors in predicting carcase performance and improve the flow of information throughout the entire supply chain.
Ultimately, he believes technology-driven yield prediction has the potential to fundamentally reshape how beef is valued and produced.
“This could revolutionise how we produce beef cattle in both the United States and Australia,” Carter said.
For the Wagyu sector, the work represents an exciting step toward combining advanced technology, artificial intelligence and precision breeding to deliver greater value throughout the supply chain.