MOE Key Laboratory of Laser Life Science & Laboratory of Photonic Chinese Medicine, College of Biophotonics, South China Normal University, Guangdong 510631, China.
Laboratory of Laser Sports Medicine, South China Normal University, Guangdong 510631, China.
Molecules. 2019 May 16;24(10):1889. doi: 10.3390/molecules24101889.
The growing demand for whey protein supplements has made them the target of adulteration with cheap substances. Therefore, Raman spectroscopy in tandem with chemometrics was proposed to simultaneously detect and quantify three common adulterants (creatine, l-glutamine and taurine) in whey protein concentrate (WPC) powder. Soft independent modeling class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) models were built based on two spectral regions (400-1800 cm and 500-1100 cm) to classify different types of adulterated samples. The most effective was the SIMCA model in 500-1100 cm with an accuracy of 96.9% and an error rate of 5%. Partial least squares regression (PLSR) models for each adulterant were developed using two different Raman spectral ranges (400-1800 cm and selected specific region) and data pretreatment methods. The determination coefficients (R) of all models were higher than 0.96. PLSR models based on typical Raman regions (500-1100 cm for creatine and taurine, the combination of range 800-1000 cm and 1300-1500 cm for glutamine) were superior to models in the full spectrum. The lowest root mean squared error of prediction (RMSEP) was 0.21%, 0.33%, 0.42% for creatine, taurine and glutamine, and the corresponding limit of detection (LOD) values for them were 0.53%, 0.71% and 1.13%, respectively. This proves that Raman spectroscopy with the help of multivariate approaches is a powerful method to detect adulterants in WPC.
乳清蛋白补充剂的需求不断增长,这使得它们成为了被廉价物质掺假的目标。因此,本文提出了拉曼光谱与化学计量学相结合的方法,用于同时检测和定量乳清蛋白浓缩物(WPC)粉末中的三种常见掺杂物(肌酸、L-谷氨酰胺和牛磺酸)。基于两个光谱区域(400-1800cm 和 500-1100cm),建立了软独立建模分类类比(SIMCA)和偏最小二乘判别分析(PLS-DA)模型,以对不同类型的掺假样品进行分类。在 500-1100cm 光谱区域中,SIMCA 模型的效果最佳,准确率为 96.9%,错误率为 5%。使用两种不同的拉曼光谱范围(400-1800cm 和选定的特定区域)和数据预处理方法,为每种掺杂物开发了偏最小二乘回归(PLSR)模型。所有模型的决定系数(R)均高于 0.96。基于典型拉曼区域(500-1100cm 用于肌酸和牛磺酸,800-1000cm 和 1300-1500cm 组合用于谷氨酰胺)的 PLSR 模型优于全谱模型。肌酸、牛磺酸和谷氨酰胺的预测均方根误差(RMSEP)最低值分别为 0.21%、0.33%和 0.42%,对应的检测限(LOD)值分别为 0.53%、0.71%和 1.13%。这证明了在多元方法的帮助下,拉曼光谱是一种检测 WPC 中掺杂物的有效方法。