Al-Jowder O, Defernez M, Kemsley E K, Wilson R H
Institute of Food Research, Norwich Research Park, Colney, Norwich, United Kingdom.
J Agric Food Chem. 1999 Aug;47(8):3210-8. doi: 10.1021/jf981196d.
Mid-infrared (MIR) spectroscopy is used to address certain issues connected with the authentication of beef and ox kidney and liver: is it possible to distinguish muscle from offal tissue; does the condition, cut of meat, or type of offal influence the distinction; can pure minced beef be distinguished from that adulterated with offal? Using partial least squares (PLS) and canonical variate analysis, predictive models are developed to identify MIR spectra of beef, kidney, and liver. Using modified SIMCA, the pure beef specimens are modeled as a single class; this model identifies spectra of unadulterated beef as such, with an acceptable error rate, while rejecting spectra of specimens containing 10-100% w/w kidney or liver. Finally, PLS regressions are performed to quantify the amount of added offal. The prediction errors obtained (+/-4.8 and +/-4.0% w/w, respectively, for the kidney and liver calibrations) are commensurate with the detection limits suggested by the SIMCA analysis.
中红外（MIR）光谱法用于解决与牛肉、牛肾和牛肝鉴别相关的某些问题：能否区分肌肉组织和内脏组织；肉的状态、切块或内脏类型是否会影响这种区分；能否区分纯牛肉末和掺有内脏的牛肉末？使用偏最小二乘法（PLS）和典型变量分析，开发预测模型以识别牛肉、肾脏和肝脏的MIR光谱。使用改进的软独立建模类比法（SIMCA），将纯牛肉样本建模为单一类别；该模型以可接受的错误率识别出未掺假牛肉的光谱，同时拒绝含有10 - 100%重量/重量肾脏或肝脏的样本光谱。最后，进行PLS回归以量化添加内脏的量。获得的预测误差（肾脏和肝脏校准分别为±4.8%重量/重量和±4.0%重量/重量）与SIMCA分析建议的检测限相当。
