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| Establishment of Predictive Models for Determination of Oleic Acid and Linoleic Acid Contents in Tan Sheep Meat by Near Infrared Spectroscopy |
| SA Miaomiao, LI Yalei, LUO Ruiming, ZHAO Junyi |
| School of Agriculture, Ningxia University, Yinchuan 750021, China |
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Abstract Predictive modelling was performed to determine oleic acid and linoleic acid contents in Tan sheep meat using near infrared spectroscopy combined with chemometrics. In this study, 138 samples of striploin, tenderloin, thick flank and belly from Tan sheep were collected. Near infrared reflectance spectra of minced meat samples were collected within the wavelength range of 900–2 500 nm. The contents of oleic acid and linoleic acid in the samples were determined by gas chromatography (GC) and the analytical data obtained were used as a reference to establish a partial least squares regression (PLSR) model. The performance of the model was optimized by reducing the dimension of the data using the interval random frog (IRF) algorithm. The results showed that the full-wavelength model for oleic acid developed through spectral preprocessing using standard normal variate (SNV) transformation combined with first derivative exhibited a higher correction coefficient of calibration (Rc) of 0.889 5 compared with any other spectral preprocessing method, with root mean square error of cross-validation (RMSECV) of 10.251 5, correlation coefficient of prediction (Rp) of 0.735 7, and root mean square error of prediction set (RMSEP) of 10.249 2. The Rc and Rp were both higher than those based on 92 characteristic wavelengths extracted using IRF. For linoleic acid, the full-wavelength model established with multiplicative scatter correction (MSC) presented the highest Rc of 0.874 7 with RMSECV of 1.051 2 but the Rp and RMSEP were lower. The model based on 102 characteristic wavelengths extracted by IRF showed greatly improved correlation, with the highest Rc of 0.991 2, as well as RMSECV of 0.011 8, Rp of 0.987 9, and RMSEP of 0.012 2. Therefore, near-infrared spectroscopy combined with IRF algorithm cannot well predict the oleic acid content of Tan sheep meat, but it has high predictive ability for the linoleic acid content.
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2020, Vol. 34 
