Authentication of barley-finished beef using visible and near infrared spectroscopy (Vis-NIRS) and different discrimination approaches

This study evaluated visible and near-infrared spectroscopy (Vis-NIRS) to authenticate barley-finished beef using different discrimination approaches. Dietary grain source (barley, corn, or blend-50% barley/50% corn) did not affect (P > 0.05) meat quality but influenced (P < 0.05) fatty acid profiles. The longissimus thoracis (LT) from barley-fed steers had lower n-6 fatty acid content and n-6/n-3 ratio compared to LT from corn and blended grain-fed steers. Vis-NIRS coupled with partial least square discriminant analysis (PLS-DA) and support vector machine in the linear (L-SVM) kernel classified with approximately 70% overall accuracy subcutaneous fat and intact LT samples, respectively, from barley, corn, and blended-fed cattle. When only barley and corn samples were considered, fat and intact LT samples were correctly classified with overall accuracy >94% with PLS-DA and radial/L-SVM, and approximately 90% with PLS-DA and L-SVM, respectively. Ground LT samples were classified with <= 70% overall accuracy. Vis-NIRS measurements on fat and intact LT have potential to discriminate between corn and barley-fed beef.

Automated summary

This study evaluated the use of Vis-NIRS to authenticate barley-finished beef and found that it can effectively distinguish between beef from barley and corn-fed cattle. The dietary grain source did not significantly affect meat quality, but did impact fatty acid profiles. The combination of Vis-NIRS with PLS-DA and SVM showed promising results in classifying different types of beef samples.