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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.