Near-infrared reflectance analysis for predicting beef longissimus tenderness.

Abstract

Near-infrared reflectance spectra (1,100 to 2,498 nm) were collected on beef longissimus thoracis steaks for the purpose of establishing the feasibility of predicting meat tenderness by spectroscopy. Partial least squares (PLS) analysis (up to 20 factors) and multiple linear regression (MLR) were used to predict cooked longissimus Warner-Bratzler shear (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 tender steaks. This was particularly true at wavelengths between 1,100 and 1,350 nm. For PLS regression, optimal model conditions (R2 = .67; SEC = 1.2 kg) occurred with six PLS factors. When the PLS model was tested against the validation subset, similar performance was obtained (R2 = .63; SEP = 1.3 kg) and bias was small (<.3 kg). Among the 39 samples 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 observed Warner-Bratzler shear force value. The optimal PLS model was able to predict whether a steak would have a Warner-Bratzler shear force value < 6 kg with 75% accuracy. The R2 of MLR model was .67, and 89% of samples were correctly classified (< 6 vs > 6 kg) for Warner-Bratzler shear force. These data indicate that NIR is capable of predicting Warner-Bratzler shear force values of longissimus steaks. Refinement of this technique may allow nondestructive measurement of beef longissimus at the processing plant level.