Ripoll G, Albertí P, Panea B, Olleta J L, Sañudo C
Unidad de Tecnología en Producción Animal, CITA de Aragón, Avda, Montañana, 930, E-50059 Zaragoza, Spain.
Meat Sci. 2008 Nov;80(3):697-702. doi: 10.1016/j.meatsci.2008.03.009. Epub 2008 Mar 16.
The aim of this study was to assess near-infrared reflectance (NIR) spectroscopy as a tool for determining sensory and texture characteristics of beef. Chemical, instrumental, texture and sensory characteristics were predicted by near-infrared reflectance spectroscopy carried out on longissimus dorsi muscle samples from 190 young bulls. The use of first derivative gave best predictions together with NIR spectra, except for myoglobin and water holding capacity, which had an R(2) of prediction of 0.91 and 0.82, respectively, using visible and NIR spectra. Tenderness was the best-predicted variable (R(2)=0.98) demonstrating the potential of NIR spectroscopy in the prediction of sensory variables. Chemical composition variables and Warner-Bratzler shear force were predicted with an R(2) of prediction of around 0.7, but protein was not predicted with accuracy.
本研究的目的是评估近红外反射光谱法作为一种测定牛肉感官和质地特性的工具。通过对190头年轻公牛的背最长肌样本进行近红外反射光谱分析，预测其化学、仪器、质地和感官特性。除了肌红蛋白和持水能力外，一阶导数与近红外光谱结合使用时预测效果最佳，使用可见光谱和近红外光谱时，肌红蛋白和持水能力的预测决定系数（R²）分别为0.91和0.82。嫩度是预测效果最好的变量（R² = 0.98），这表明近红外光谱法在预测感官变量方面具有潜力。化学成分变量和沃纳-布拉茨勒剪切力的预测决定系数约为0.7，但蛋白质的预测不准确。
