首页> 外文期刊>CyTA Journal of Food >Identification and quantification of corncob as adulterant in corn dough and tortilla by MIR-FTIR spectroscopy and multivariate analysis.
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Identification and quantification of corncob as adulterant in corn dough and tortilla by MIR-FTIR spectroscopy and multivariate analysis.

机译:通过MIR-FTIR光谱和多变量分析鉴定和定量玉米芯和玉米粉圆饼中作为掺假品的玉米芯。

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Fourier Transform Infrared (FTIR) spectroscopy coupled to chemometrics was developed to detect and quantify the adulteration in white and blue corn dough and white and blue corn tortilla, with corncob. The classification model, soft independent modeling of class analogy (SIMCA), showed 100% correct classification rate for adulterated samples from unadulterated ones. The best quantitative chemometric calibration model was developed with the partial least square (PLS) algorithm showing coefficient of determination (R 2) between predicted and actual adulterant concentrations that range from 0.996 to 0.998 for all samples. Standard error of prediction (SEP) for the developed models ranged between 0.395 and 0.590 for all samples. The results showed that mid-infrared spectroscopy in conjunction with multivariate analysis can effectively be used to identify and quantify corncob in white and blue corn dough and in white and blue corn tortilla
机译:傅里叶变换红外(FTIR)光谱与化学计量学相结合,可以检测和量化玉米芯中白,蓝玉米面团和白,蓝玉米饼的掺假。分类模型,即类比法的软独立建模(SIMCA),显示出纯样品中的纯样品的正确分类率为100%。使用偏最小二乘(PLS)算法开发了最佳定量化学计量学校准模型,该算法显示了所有样品的预期掺假浓度和实际掺假浓度之间的测定系数(R 2 )。对于所有样本,已开发模型的标准预测误差(SEP)在0.395至0.590之间。结果表明,中红外光谱结合多变量分析可以有效地鉴定和定量白色和蓝色玉米面团以及白色和蓝色玉米饼中的玉米芯

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