Beef grading systems continue to evolve

 

By Natalie Jones, Other News

via Farm and Dairy (OH) - November 7, 2019

 

Jones is Certified Angus Beef fall intern

 

WOOSTER, Ohio — When you enjoy a great steak, it’s largely because of those little flecks of intramuscular fat.

 

“Marbling is like butter in the pan of potatoes,” said Dale Woerner, Texas Tech meat scientist addressing the recent Feeding Quality Forum in Amarillo. “The more marbling in the beef, the more flavor and performance we get.”

 

He reviewed the history of USDA beef grades, Prime, Choice, Select and Standard, wherein a combination of marbling and maturity determine quality grade. The measure of maturity has evolved from a study of chine bone ossification to dentition in 2017, with somewhat greater accuracy in the prediction of eating quality.

 

The U.S produced a fair amount of Choice and Prime 50 years ago but in the 1990s, dietary consensus may have moved demand toward leaner beef.

 

“Fortunately for all of us, the times have changed,” Woerner said. We have research that supports fat as part of a healthy diet and consumers demanding high-quality beef. So what we have seen in the last 20 to 25 years is a rebound of grade because of increased emphasis on genetics, Angus genetics perhaps.”

 

That started in 1978 when the Certified Angus Beef ®  brand “came in and changed the game” in the establishment of premium Choice.

 

Yield grades often miss the mark on individuals but work overall and serve as an estimate of red-meat yield in carcasses, 1 being leanest and 5, the fattest, lowest yielding cattle. While many cattle no longer receive a USDA yield grade, the same formula still determines premiums or discounts for cutability.

 

Since approval in 2006, camera grading systems have added consistency in most major packing plants, Woerner said.

 

Camera systems have evolved to calculate yield and quality grades, ribeye area and marbling scores from millions of pixels in a digital image, segregated into red or white (lean or fat), amounts measured by pixel size.

 

“It’s really not much different than predicting the weather,” Woerner said. “We utilize algorithms, or what the modern folk are calling ‘artificial intelligence’ to turn a machine into a human grader. But machines don’t wake up in a bad mood or with a hangover or a personal issue with the one working next to them.”

 

In 800 nanoseconds — one of those is a billionth of a second — these systems calculate everything they are asked to do, ready for the next on the line. That’s happening now. What’s next?

 

“X-ray vision and x-ray technology is definitely coming our way,” Woerner said.

 

Danish and Australian systems have used it for...

 

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