NEAR-INFRARED REFLECTANCE ANALYSIS FOR PREDICTING BEEF LONGISSIMUS TENDERNESS

Near-infrared reflectance spectra (1,100 to 2,498 nm) were collected o n beef longissimus thoracis steaks for the purpose of establishing the feasibility of predicting meat tenderness by spectroscopy. Partial le ast squares (PLS) analysis (up to 20 factors) and multiple linear regr ession (MLR) were used to predict cooked longissimus Warner-Brattier s hear (WBS) force values from spectra of steaks from 119 beef carcasses . Modeling used the combination of log(1/R) and its second derivative. Overall, absorption was higher for extremely tough steaks than for te nder steaks. This was particularly true at wavelengths between 1,100 a nd 1,350 nm. For PLS regression, optimal model conditions (R-2 = .67; SEC = 1.2 kg) occurred with six PLS factors. When the PLS model was te sted against the validation subset, similar performance was obtained ( R-2 = .63; SEP = 1.3 kg) and bias was small (< .3 kg). Among the 39 sa mples in the validation data set, 48.7, 87.7, and 97.4% of the samples were predicted within 1.0, 2.0, and 3.0 kg, respectively, of the obse rved Warner-Brattier shear force value. The optimal PLS model was able to predict whether a steak would have a Warner-Brattier shear force v alue < 6 kg with 75% accuracy. The R-2 of MLR model was .67, and 89% o f samples were correctly classified (< 6 vs > 6 kg) for Warner-Brattie r shear force. These data indicate that NIR is capable of predicting W arner-Brattier shear force values of longissimus steaks. Refinement of this technique may allow nondestructive measurement of beef longissim us at the processing plant level.