AI Article Synopsis
- A study analyzed 98 fresh mutton samples from various provinces in China to evaluate tenderness using Fourier transform near infrared (FT-NIR) spectroscopy.
- A partial least squares (PLS) algorithm was employed to correlate the shear force values (a measure of tenderness) obtained from a texture machine with the FT-NIR spectra.
- Results showed that FT-NIR spectroscopy can effectively predict mutton tenderness, with a calibration correlation coefficient (r²) of 86.2% and strong agreement between measured and predicted values.
Article Abstract
Ninety eight representative fresh mutton samples from Neimeng, Ningxia, Gansu, Xinjiang province were selected for this study, the nondestructive measurement of the fresh mutton tenderness by Fourier transform near infrared (FT-NIR) spectroscopy was discussed. Partial least squares(PLS) algorithm was used to build the model between the shear force value of the fresh mutton tenderness measured by the texture machine and the FT-NIR spectra. The influence of different processing method of spectra, factors and wave regions on the determination coefficients (r2), root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) was studied. The result showed that the shear force value of ninety eight representative fresh mutton samples was 1.673-6.631 kg, and the shear force value above 75% samples was 2-5 kg, almost covering the fresh mutton tenderness of our country's sheep, the r2 of the calibration could reach 86.2% and the RMSECV was up to 0. 445 in the wave number range 11 995-5 446 cm(-1) and 4 601-4 246 cm(-1) with vector normalization when the PLS factors was ten. The correlation coefficient(R), RMSEP and average bias between value measured by the texture machine and predicted value of model based on validation samples were 0.87, 0.524 and 0.385 respectively. The result indicates that FT-NIR spectroscopy is capable of predicting tenderness value of fresh mutton.
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