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Use of Visible and Near Infrared Spectroscopy to Predict Beef and Pork Quality
A method was developed for evaluation of meat quality with visible and near-infrared spectroscopy. An optimal method was developed for evaluation of the LM cross-section of ribbed beef carcasses with a high-intensity reflectance probe and that method was used to evaluate U.S. Select carcasses on-line during beef grading in two experiments (n = 292; n = 467). It was determined that carcasses could be sorted into groups that differed in mean LM slice shear force (SSF)at 2 and 14 d postmortem and the percentage of samples with LM SSF > 40 (2 d postmortem) or 25 kg (14 d postmortem). Although the system used in the previous experiments allowed for online tenderness prediction, it was not optimized for beef carcass evaluation. Additionally, a limitation to the commercial adoption of that system was that the predicted SSF value was affected by the length of time that the LM was exposed to air (bloomed) before evaluation. A commercial vendor optimized the technology hardware for carcass measurement. Because optimization included changes to the system, a new model had to be developed (n = 1,155) and it was proven to predict SSF without bias due to bloom time. That model was field tested (n = 4,204) and shown to work for both U.S. Choice and U.S. Select carcasses. Application to the ribeye during grading resulted in classes that differed in SSF for LM, gluteus medius, semimembranosus, biceps femoris, and adductor (P < 0.0001). This technology was applied to the ventral side of boneless pork loins (n = 901) and a model was developed that resulted in classes that differed in SSF at 14 d postmortem. Upon field testing (n = 1,208 from 4 plants) it was determined that reflectance at 822 nm was indicative of variation in tenderness both among and within plants. Predicted tenderness classes, based on reflectance at 822 nm, differed in mean LM SSF values at 15 d postmortem (P < 10‑26) and in the percentage of loins with SSF > 25 kg (P < 10‑16). This technology also effectively sorted pork loins with regard to intramuscular fat level and lean color stability.
Keywords: Tenderness, Near-Infrared, Prediction