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Chemometric classification and quantification of cold pressed grape seed oil in blends with refined soybean oils using attenuated total reflectance–mid infrared (ATR–MIR) spectroscopy

机译:用衰减总反射 - 中红外线(ATR-MIR)光谱法与精制大豆油混合物中冷压制葡萄籽油的化学计量分类和定量

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摘要

Of the cold pressed edible oils, grape seed oil (GSO) is one of the highest quality and, consequently the most expensive oil. Because of that, adulteration by mixing GSOs up with lower price edible oils is frequently seen. The classification and determination of adulterant concentration for GSO is hence a focus of great interest. The aim of this study was to investigate the feasibility of ATR–MIR spectroscopy coupled with the multivariate methodology for qualitative and quantitative analyses of cold pressed GSO adulteration with refined soybean oil (SBO), by using characteristic wavenumber regions. Thirty three pure oils and ninety six blends were analyzed using ATR–MIR spectroscopy in combination with PCA, LDA, SIMCA and PLSR analysis. SIMCA models provided an excellent classification for pure GSO and other samples. The classification limits by ATR–MIR spectroscopy was also below 5%. Quantitative analyses were performed by minimization of RMSE of cross-validation values, which resulted in excellent predictions (R2?>?0.99). The prediction parameters for the sample sets were: the RMSEC were in the range 0.59–2.09% and, RMSECV were in the range 0.92–5.60%, hence on the basis of the PLSR models, quantification of adulterant could be determined at levels 0.59%.
机译:冷压可食用油,葡萄籽油(GSO)是最高品质之一,因此是最昂贵的油。因此,经常看到通过用较低价格食用油混合GSO的掺假。 GSO的掺杂剂浓度的分类和测定是非常兴趣的焦点。本研究的目的是研究ATR-MIR光谱与多变量分析通过使用特征波数区域与精制大豆油(SBO)的质定量和定量分析的多变量分析的可行性。使用ATR-MiR光谱与PCA,LDA,SIMCA和PLSR分析组合使用ATR-MiR光谱分析了三十三种纯油和九十六个混合物。 SIMCA模型为纯GSO和其他样品提供了出色的分类。 ATR-MIR光谱的分类限制也低于5%。通过最小化交叉验证值的RMSE进行定量分析,这导致了优异的预测(R2?> 0.99)。样品集的预测参数是:RMSEC在0.59-2.09%的范围内,RMSECV在0.92-5.60%的范围内,因此基于PLSR模型,可以在水平下测定掺假剂的定量。 0.59%。

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