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

Liu, Y., Lyon, B.G., Windham, W.R., Realini, C.E., Pringle, T.D.D., Duckett, S.
Meat science 2003 v.65 no.3 pp. 1107
beef, steaks, meat aging, rigor mortis, beef quality, cooking quality, shear strength, meat tenderness, sensory properties, color, meat juices, classification, prediction, ultraviolet-visible spectroscopy, near-infrared reflectance spectroscopy, least squares, principal component analysis
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 (R2) in calibration to be 0.78-0.90, and R2 was between 0.49 and 0.55 for tenderness, Hunter L, sensory chewiness and juiciness. The prediction R2 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.