Lycium barbarum Polysaccharide Inhibits Lipid Oxidation and Protein Degradation in Tan Sheep Meatballs during Frozen Storage.

The aim of the present study was to evaluate the effectiveness of Lycium barbarum polysaccharide (LBP) on lipid oxidation and protein degradation in Tan sheep meatballs during the frozen period. The meatballs were treated with LBP at 0.01%, 0.02%, and 0.03% and stored at -18±1°C for 0, 3, 6, 9, and 12 weeks. The effects of LBP treatment were investigated using the contents of total volatile basic nitrogen (TVB-N), texture profile (TP), thiobarbituric acid reactive substances (TBARS), colour, and pH values, compared with 0.02% butylated hydroxytoluene treatment and the blank control. The results showed that LBP treatment significantly decreased TBARS content compared with the control, which confirmed LBP to be a highly effective component in preventing lipid oxidation of Tan sheep meatballs during frozen storage, and protein degradation in Tan sheep meatballs had a significant inhibition effect because of TVB-N value reduction. In addition, the colour, TP and pH values of meatballs treated with LBP were improved dramatically. To further determine the quality changes of the blank control and all treated groups during storage, the comprehensive score evaluation equation based on principal component analysis was obtained: Y=0.51632Y1+0.29589Y2 (cumulative contribution rate=81.221%), and the 0.02% LBP-treated group had a higher comprehensive score than the other groups, and the quality of LBP-treated meatballs was better as well. In summary, LBP may reduce or inhibit lipid oxidation and protein degradation, and enhance overall quality and shelf-life in prepared meat products.

Predictability of carcass traits in live Tan sheep by real-time ultrasound technology with least-squares support vector machines.

This study aimed to investigate the performance of least-squares support vector machines to predict carcass characteristics in Tan sheep using noninvasive in vivo measurements. A total of 80 six-month-old Tan sheep (37 rams and 43 ewes) were examined. Back fat thickness and eye muscle area between the 12th and 13th ribs were measured using real-time ultrasound in live Tan sheep. All carcasses were dissected to hind leg, longissimus dorsi muscle, lean meat, fat, and bone to determine carcass composition. Multiple linear regression (MLR), partial least squares regression (PLSR), and least-squares support vector machines (LSSVM) were applied to correlate the live Tan sheep characteristics with carcass composition. The results showed that the LSSVM model had a better efficacy for estimating carcass weight, longissimus dorsi muscle weight, lean meat weight, fat weight, lean meat, and fat percentage in live lambs (R = 0.94, RMSE = 0.62; R = 0.73, RMSE = 0.02; R = 0.86, RMSE = 0.47; R = 0.78, RMSE = 0.63; R = 0.73, RMSE = 0.02; R = 0.65, RMSE = 0.03, respectively). LSSVM algorithm was a potential alternative to the conventional MLR method. The results demonstrated that LSSVM model might have great potential to be applied to the evaluation of sheep with superior carcass traits by combining with real-time ultrasound technology.

Determination of metmyoglobin in cooked tan mutton using Vis/NIR hyperspectral imaging system.

In this study, the ENVI 4.6 software was used to obtain the spectral reflection value of samples. The outlier samples were eliminated by the Monte Carlo method, and then SPXY (sample set partitioning based on be x-y distances) was used to divide the calibration set and prediction set. The spectral images were pretreated and characteristic wavelengths were extracted. The spectral models of full and pretreated spectra and characteristic bands were established by partial least squares regression (PLSR) and principle component regression (PCR), and the optimal modeling combination was selected. The results showed that the modeling effect of the original spectrum was the best. In full-PLSR model, the determination coefficient of the calibration set (Rc2 ), the determination coefficient of prediction set (Rp2 ), and the determination coefficient of interactive verification set (Rcv2 ) were 0.8804, 0.7375, and 0.7422, and root-mean-square error of calibration set (RMSEC), root-mean-square error of prediction (RMSEP), and root mean square error of interactive validation set (RMSECV) were 2.3630, 2.9607, and 3.4209, respectively. PLSR and PCR models were established to obtain the optimal models of CARS-PLSR and PCR-PLSR. In the CARS-PLSR model, the Rc2 , Rp2 , and Rcv2 were 0.9135, 0.7654, and 0.8171, respectively, while RMSEC, RMSEP, and RMSECV were 2.0275, 2.9306, and 2.9262, respectively. In the iRF-PCR model, Rc2 , Rp2 , and Rcv2 were 0.7952, 0.7372, and 0.7280, respectively, while RMSEC, RMSEP, and RMSECV were 3.0207, 2.8278, and 3.4288, respectively. This study has demonstrated that visible and near-infrared hyperspectral imaging system can rapidly predict the content of metmyoglobin in cooked tan mutton. PRACTICAL APPLICATION: This study has demonstrated that visible and near-infrared (Vis/NIR) hyperspectral imaging system can rapidly predict the content of MetMb in cooked tan mutton. With the advantages of nondestructive, rapid, real-time, Vis/NIR, hyperspectral imaging system can be widely expanded and applied to the detection of myoglobin in meat to evaluate the color of meat.