Chen Qingmin, Xie Yunfei, Yu Hang, Guo Yahui, Yao Weirong
College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, China; School of Food Science and Technology, Jiangnan University, No. 1800 Lihu Avenue, Wuxi 214122, China; State Key Laboratory of Food Science and Technology, Jiangnan University, China.
School of Food Science and Technology, Jiangnan University, No. 1800 Lihu Avenue, Wuxi 214122, China; State Key Laboratory of Food Science and Technology, Jiangnan University, China.
Food Chem. 2023 Jul 1;413:135513. doi: 10.1016/j.foodchem.2023.135513. Epub 2023 Jan 19.
Freeze-thaw accelerated the colour deterioration of beef with the increase of colour b* and the decrease of colour a* values (P < 0.05). The maximum exudate loss reached 22 % after the seventh freeze-thaw. A strong correlation between the transversal relaxation time T and thawing loss may mean that T water contributed to the exudate loss during freeze-thaw. Afterwards, competitive adaptive reweighted sampling-partial least square (CARS-PLS) has the best prediction in thawing loss of frozen/thawed beef with correlation coefficients of prediction (R) of 0.971, and root mean square error of prediction (RMSEP) of 1.436. Besides, Uninformative variable elimination-partial least squares (UVE-PLS) showed good prediction effects on colour values (R = 0.932 - 0.994) and water content (R = 0.928, RMSEP = 0.582) of frozen/thawed beef. Therefore, this work demonstrated that Raman spectroscopy coupled with multivariate calibration has a good ability for non-destructive prediction in colour and water-related properties of frozen/thawed beef.
冻融加速了牛肉的颜色劣化,颜色b值增加而a值降低(P < 0.05)。第七次冻融后,最大渗出损失达到22%。横向弛豫时间T与解冻损失之间的强相关性可能意味着T2水导致了冻融过程中的渗出损失。之后,竞争性自适应重加权采样-偏最小二乘法(CARS-PLS)对冻融牛肉解冻损失的预测效果最佳,预测相关系数(R)为0.971,预测均方根误差(RMSEP)为1.436。此外,无信息变量消除-偏最小二乘法(UVE-PLS)对冻融牛肉的颜色值(R = 0.932 - 0.994)和水分含量(R = 0.928,RMSEP = 0.582)显示出良好的预测效果。因此,这项工作表明拉曼光谱结合多元校准对冻融牛肉的颜色和与水相关的特性具有良好的无损预测能力。