Post-Harvest Prediction of Tenderness in Pork
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As variation in pork tenderness has increased, identification of tenderness has become an industry need. This study consisted of 1208 pork loins randomly selected to test the efficacy of four automated grading techniques. Visible and near-infrared spectroscopy (VVNIR) (350-1830 nm wavelengths), bioelectrical impedance (EI) (resistance, reactance, phase angle, and partial capacitance), pH, and CIE L*, a* and b* color space values were used to predict chemical moisture and lipid, pH, Warner-Bratzler shear force (WBSF), and Slice shear force (SSF) on 13 d aged pork loins. The means and standard deviations for WBSF were (22.95 and 5.16) and SSF were (165.49 and 58.15). Prediction was based on stepwise linear regression and partial least squares regression. VNIR, pH, and color, when in combination, had the highest R^2 (0.19 and 0.21) for the prediction of WBSF and SSF, respectively. Partial least squares regression (PLSR) was used to remove autocorrelation between VNIR values. By using PLSR, with an R ^2 value of 0.49, 100 percent of the "tender" chops were correctly classified, 93 percent of the "intermediate" chops were correctly classified, and 92 percent of the "tough" chops were correctly classified into its category for WBSF. However, SSF was much lower (R^2 = 0.24) with only correctly placing 62 percent of the "tender" chops and only 48 percent of the "intermediate" and "tough" chops. Electrical impedance, alone or in combination with other technologies, either did not improve predictability of linear regression equations (increase R^2) or of PLSR models (increase R^2). Equations and models that included EI values had low R^2. When adding EI to the regression equation involving all variables, R^2 increased slightly from 0.19 to 0.21 in predicting WBSF, and from 0.21 to 0.25 for SSF. When pH or CIE L* color space values were included in linear regression or PLSR models to predict WBSF and SSF, R^2 values increased from 0.14 to 0.19 for WBSF, and 0.14 to 0.21 for SSF. pH played a large role in predicting WBSF and SSF, along with CIE L*. Thus, for an on-line situation, use of VNIR, pH, and color could be used to predict tenderness. Utilization of VNIR alone could be effective in predicting pork tenderness (WBSF). Using EI alone, or in combination with VNIR, would not provide acceptable prediction of WBSF or SSF. Use of VNIR with pH and color would improve the ability to predict tender and intermediate pork WBSF and SSF, but the additional improvement in accuracy may not be warranted based on the cost and additional time needed when using more than one technology.
Segner, Kyle (2011). Post-Harvest Prediction of Tenderness in Pork. Master's thesis, Texas A&M University. Available electronically from