Pork Chop Studio improves accuracy of pork quality data to drive genetic progress and deliver the ideal eating experience.
Hendersonville, TN – Wed., May 13, 2026 – Today’s consumers expect high-quality, flavorful protein options in an increasingly competitive marketplace. Meeting that expectation starts with better data and PIC’s new Pork Chop Studio is designed to deliver it. Using advanced imaging and artificial intelligence, the new technology analyzes pork quality traits with unprecedented precision, consistency and efficiency, while laying the groundwork for technology that could someday predict consumer preference.
“Meat quality, as a key driver of demand, continues to come up in industry conversations,” says Justin Holl, PIC Product Development Senior Director. “The timing couldn’t be better to develop a tool that drives genetic progress in meat quality and optimizes pork on the dinner plate.”
Improving Accuracy in Meat Quality Measurements
For years, PIC has analyzed loin samples for quality attributes. Expert-trained evaluators manually look at each loin to assign a marbling score. It not only requires a specialized skillset, but also introduces subjectivity, which can cause variability in results.
In addition to marbling, employees manually measure pH, color and tenderness using specialized tools that allow for objective measurement but are still time consuming.
“PIC’s Applied Meat Science Team saw an opportunity with Pork Chop Studio to remove subjectivity, reduce variability and improve efficiency across the meat quality evaluation process,” says Eric Psota, PIC Digital Innovation Senior Manager.
Removing Human Variability with Pork Chop Studio
PIC’s Digital Phenotyping Team developed Pork Chop Studio – a custom imaging station –using computer vision and deep learning to automatically evaluate pork quality traits.
“At its core, Pork Chop Studio is a high-end camera system with studio lighting that captures 4K images at the touch of a button,” said Psota. “These images reveal extremely fine details, like muscle fiber striations and other characteristics not easily visible to the human eye.”
Once captured, images are sent to a server where an AI model predicts a marbling score. To train the system, three PIC experts manually scored nearly 1,300 loin images. A consensus average of those scores was then used to train the AI neural network.
Like the human brain, neural networks learn by identifying patterns and improve over time with more data. Unlike the human brain, they deliver results without emotion or distraction.
“The neural network provides an expert-level score every time,” he said. “If you gave the same loin image to a human scorer 10 minutes apart, you could easily get different results depending on mood, focus or fatigue.”
Going Beyond Marbling Scores
Eliminating manual marbling scoring was the initial goal. Now, the technology is being trained to streamline other aspects of meat quality evaluation.
“With the level of detail in these images, we can also measure loin height, width and circumference – things that are incredibly difficult to measure manually,” said Psota.
PIC has also captured more than 5,000 images of loins with pH measurements and is training the neural network to predict pH from images alone.
“Previously, a pH meter was our only option,” Psota said. “Now, we’re seeing the system pick up on visual cues – perhaps surface moisture or reflectance – that correlate to pH.”
The same is true for loin color.
“We’re eliminating the need for specialized labor and tools like pH meters or colorimeters,” he said. “All employees need to do is place a pork chop on the studio platform, press a button, remove the chop and move on to the next one.”
Realized labor savings have been redirected to higher-value tasks, such as capturing repeat images after 12 days of aging to further improve data accuracy and exploring new quality attributes altogether.
Driving Genetic Progress for a Better Eating Experience
Accurate data is only the first step. The real value comes from using that data to drive genetic progress in meat quality.
“With Pork Chop Studio, we’ve increased data accuracy, improved consistency across plant locations and maintained the real-time speed needed to feed data right back into our selection index,” said Holl. “That enables faster, more reliable genetic progress.”
“Our commitment to meat quality really allows us to shape genetics in a way that benefits everyone – from producer to packer to consumer,” said Brandon Fields, PIC Applied Meat Sciences Global Director. “If technology ultimately helps us select for better meat quality and encourages more pork consumption globally, that’s a win across the entire value chain.”
Predicting Consumer Preference
Pork Chop Studio could someday predict consumer preference.
“We intend to conduct trained taste panel evaluations where we have images of pork before it’s cooked along with human taste responses,” said Fields. “With the data, we plan to train the system to identify the most flavorful piece of pork before it’s ever cooked and given to the tasting panel. That’s our ultimate pursuit.”
“We’re not just focused on consumer acceptance,” he said. “We’re focused on optimizing pork quality to increase demand and deliver the ideal eating experience.”
Read the full Pork Chop Studio abstract.
About PIC
PIC (Pig Improvement Company) is the global leader in swine genetics. PIC provides genetically superior breeding stock to pig producers and supports them with technical services to help them realize genetic potential. PIC is a subsidiary of Genus, a UK-based company with a vision to pioneer animal genetic improvement to help nourish the world. www.pic.com
Contact:
McKenna Kent, mckenna.kent@genusplc.com
Jana McGuire, Look East Strategic Communications, janam@lookeast.com
