A system designed by US Department of Agriculture (USDA) scientists to predict superior beef tenderness is just as effective at predicting tenderness in pork and colour stability in meat.
The non-invasive tenderness prediction system was developed in the 1990s by scientists at the Agricultural Research Service (ARS) Roman L. Hruska U.S. Meat Animal Research Center (USMARC) to identify US Select beef carcasses with outstanding tenderness in the ribeye/strip loin muscle. The technology is based on visible and near-infrared reflectance spectroscopy, and can be used without destroying any product from the carcass.
ARS is USDA's chief intramural scientific research agency, and this research supports the USDA priority of promoting international food security.
Food technologists Steven Shackelford, Andy King and Tommy Wheeler, who work in the USMARC Meat Safety and Quality Research Unit, invented the system and have tested it on more than 4,000 beef carcasses and 1,800 boneless pork loins.
In collaboration with the National Cattlemen's Beef Association, they demonstrated how the technology could be applied on the ribeye during carcass grading at commercial processing facilities, and to individual cuts of meat after aging. They also partnered with the National Pork Board to successfully predict tenderness of boneless pork loins during the boning and trimming process.
Some steaks and chops turn brown quicker than others and often have to be sold at a discount or thrown away. Scientists were able to modify the system to predict colour stability. They looked at environmental factors such as lighting and oxygen consumption by simulating a retail display case to mimic conditions steaks go through in a traditional supermarket.
They also studied variations in genetics from a pedigree of 500 animals, and found considerable differences in colour stability among those animals. That finding suggests colour stability might be improved through genetic selection.
Scientists continue to assess the many applications of the system, which has shown to be efficient and cost-effective in predicting tenderness and colour stability in beef and pork.
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