CASNR will work in collaboration with researchers at Colorado State University, Fort Collins, Colo., and the United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) to evaluate the use of new mass spectrometry technology to determine tenderness, flavor and juiciness of beef in real time.

Dale Woerner, associate professor at Texas Tech and the Cargill Endowed Professor in Meat Science in the Department of Animal & Food Sciences (AFS), will lead the research project.

The goal is to develop REIMS as a real-time method for classifying the quality of beef products by evaluating REIMS' ability to predict beef sensory and tenderness, identify changes in beef flavor and tenderness as it ages and characterize the effect of extended aging on palatability.

"We are very excited to collaborate on this effort aimed at discovering the potential of a very unique technology to differentiate the quality of beef products," Woerner says. "This technology, among others, is the future of differentiating quality and safety attributes of agricultural products intended for food."

Collaborating with Woerner on the project are Jerrad Legako, assistant professor; Mark Miller, a professor and San Antonio Livestock Show and Rodeo Chair in Meat Science; and professor Chance Brooks, all part of AFS and the International Center for Food Industry Excellence (ICFIE) at Texas Tech. The study also is supported by the National Cattlemen's Beef Association, Centennial, Colo.

REIMS uses time-of-flight mass spectrometry to provide in-situ, molecularly resolved information in real time by ionizing biological samples without having to prepare the sample for examination. Utilizing both domestic and exported beef samples with a wide variety of aging days, researchers will use REIMS to repeatedly measure beef flavor, tenderness and juiciness.

They then will develop prediction models, including multiple machine-learning processes, in an attempt to understand the ability of REIMS to measure and predict these changes depending on the time beef has aged. If successful, this would allow these characteristics to be predicted in real-time and produce optimum cuts of meat in regards to tenderness, flavor and juiciness.