Beattie Rene J, Bell Steven J, Farmer Linda J, Moss Bruce W, Patterson Desmond
School of Chemistry, Queens University of Belfast, Northern Ireland, UK.
Meat Sci. 2004 Apr;66(4):903-13. doi: 10.1016/j.meatsci.2003.08.012.
The potential of Raman spectroscopy for the determination of meat quality attributes has been investigated using data from a set of 52 cooked beef samples, which were rated by trained taste panels. The Raman spectra, shear force and cooking loss were measured and PLS used to correlate the attributes with the Raman data. Good correlations and standard errors of prediction were found when the Raman data were used to predict the panels' rating of acceptability of texture (R(2)=0.71, Residual Mean Standard Error of Prediction (RMSEP)% of the mean (μ)=15%), degree of tenderness (R(2)=0.65, RMSEP% of μ=18%), degree of juiciness (R(2)=0.62, RMSEP% of μ=16%), and overall acceptability (R(2)=0.67, RMSEP% of μ=11%). In contrast, the mechanically determined shear force was poorly correlated with tenderness (R(2)=0.15). Tentative interpretation of the plots of the regression coefficients suggests that the α-helix to β-sheet ratio of the proteins and the hydrophobicity of the myofibrillar environment are important factors contributing to the shear force, tenderness, texture and overall acceptability of the beef. In summary, this work demonstrates that Raman spectroscopy can be used to predict consumer-perceived beef quality. In part, this overall success is due to the fact that the Raman method predicts texture and tenderness, which are the predominant factors in determining overall acceptability in the Western world. Nonetheless, it is clear that Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of beef quality parameters.
利用一组52个熟牛肉样本的数据,研究了拉曼光谱法测定肉质属性的潜力,这些样本由经过训练的味觉小组进行评分。测量了拉曼光谱、剪切力和烹饪损失,并使用偏最小二乘法(PLS)将这些属性与拉曼数据进行关联。当使用拉曼数据预测小组对质地可接受性的评分时,发现了良好的相关性和预测标准误差(R(2)=0.71,预测剩余平均标准误差(RMSEP)占平均值(μ)的15%)、嫩度(R(2)=0.65,RMSEP占μ的18%)、多汁程度(R(2)=0.62,RMSEP占μ的16%)和总体可接受性(R(2)=0.67,RMSEP占μ的11%)。相比之下,机械测定的剪切力与嫩度的相关性较差(R(2)=0.15)。对回归系数图的初步解释表明,蛋白质的α-螺旋与β-折叠的比例以及肌原纤维环境的疏水性是影响牛肉剪切力、嫩度、质地和总体可接受性的重要因素。总之,这项工作表明拉曼光谱法可用于预测消费者感知的牛肉品质。总的来说,这一成功部分归因于拉曼方法能够预测质地和嫩度,而这是在西方世界决定总体可接受性的主要因素。尽管如此,很明显拉曼光谱法作为一种无损、快速测定牛肉品质参数的方法具有很大潜力。