June 02, 2008
UNL Research Focuses on Predicting Steaks' Tenderness
LINCOLN, Neb. — University of Nebraska-Lincoln scientists have developed a way to predict steak tenderness before the consumer takes that first bite. The technology could be a boon to the beef industry as it would allow retailers to charge a premium for a "guaranteed tender" label.
"Beef tenderness is a primary factor in consumer satisfaction," said Jeyamkondan Subbiah, the UNL food engineer who heads the research. "However, a sufficiently accurate, nondestructive method of on-line evaluation of tenderness continues to elude the beef industry."
Current U.S. Department of Agriculture grading standards classify beef carcasses into quality and yield grades but do not assess tenderness. Since carcasses are not priced on the basis of tenderness, producers don't have a financial incentive to supply a tender product.
The beef industry long has sought technology that could scan fresh meat at two to three days postmortem and predict its tenderness when cooked by the consumer about two weeks later.
"There is a growing recognition that beef tenderness must be incorporated into the USDA quality grading process if true, value-based marketing is to be developed," Subbiah and other authors wrote for a recent presentation on the issue.
UNL is developing that technology. Its approach uses a hyperspectral imaging, a novel technology that combines video image analysis and spectroscopy. The system consists of a digital video camera and spectrograph to capture the two key qualities that affect beef tenderness – muscle structure and biochemical properties.
In the research, 2-day aged, one-inch thick ribeyes were placed on a plate and scanned by the system, which captures multiple images at hundreds of wavelengths with regular intervals.
The combination of the video images and spectroscopy is key, Subbiah said. The video technology captures the muscle profile. Tender beef has fine muscle fibers, while tough beef has visibly coarser muscle fibers. The spectroscopy measures biochemical properties that indicate how much the steak will become tender during aging.
After scanning, the steaks were cooked and tested. Results so far are promising. The system predicted three tenderness categories – tender, intermediate and tough – with about 77 percent accuracy and two tenderness categories – acceptable and tough – with 93.7 percent accuracy.
"Beef is expensive. Consumers expect it to be tender. One bad experience can make them not buy beef for awhile," Subbiah said. "We think consumers are willing to pay a premium for a guaranteed-tender product."
Subbiah said that premium could be $1 to $2 per pound.
Hyperspectral imaging is not new. Previously it's been used to determine nutrient deficiency in plants, fecal contamination in chicken and fungal/bacterial contamination in fruit.
Researchers will continue to hone this process. Meantime, UNL is patenting the technology and hopes to identify a business interested in partnering on commercialization.
Critical to commercializing the technology will be finding a way "to take it from the lab to the plant," Subbiah said. The industry must be able to use it to evaluate a carcass, not individual steaks, and do it in about 10 seconds per carcass.
"It has to be done in the current mode of operation," without any additional, time-consuming steps, Subbiah added.
Such commercialization is likely two to three years away, he added.
The Nebraska Beef Council and The Beef Checkoff help fund this research, which is conducted through UNL's Agricultural Research Division.
IANR also includes UNL Extension and the College of Agricultural Sciences and Natural Resources. A 2007 study by an independent organization found IANR annually returns at least $15 in benefits to Nebraskans for every dollar of state support, making it a primary engine for economic and social sustainability (At Work for Nebraska).
6/2/08-DM Jeyamkondan Subbiah - Ph.D.
Biological Systems Engineering; Food Science and Technology Assistant Professor (402) 472-4944
 
Dan Moser IANR News & Photography Coordinator (402) 472-3007
Department:
Food Science and Technology
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