Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study

Meat Sci. 2003 Nov;65(3):1107-15. doi: 10.1016/S0309-1740(02)00328-5.

Abstract

Color, instrumental texture, and sensory attributes of steaks from 24 beef carcasses at 2, 4, 8, 14, and 21 days post mortem were predicted by visible/near infrared (visible/NIR) reflectance spectroscopy in 400-1080 nm region. Predicting the Hunter a, b, and E* yielded the coefficient of determination (R(2)) in calibration to be 0.78-0.90, and R(2) was between 0.49 and 0.55 for tenderness, Hunter L, sensory chewiness and juiciness. The prediction R(2) for tenderness was in the range of 0.22-0.72 when the samples were segregated according to the aging days. Based on partial least square (PLS) model predicted tenderness, beef samples were classified into tender and tough classes with a correct classification of 83%. Soft independent modeling of class analogy of principal component analysis (SIMCA/PCA) model of measured tenderness showed great promise in the classification of tender and tough meats with over 96% success.