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Application of Fourier Transform Infrared (FT-IR) Spectroscopy Combined with Chemometrics for Analysis of Rapeseed Oil Adulterated with Refining and Purificating Waste Cooking Oil

机译:傅里叶变换红外光谱(FT-IR)与化学计量学结合用于分析精制提纯食用​​油的菜籽油

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摘要

Currently, the detection of rapeseed oil (RSO) adulterated with refining and purificating waste cooking oil (WCO) is an attractive work for researchers in accordance with food safety all over the world particularly in China. There is a rapid increasing requirement for more accurate and sensitive detection method to cope the more subtle adulterations in edible oils. For this reason, Fourier transform infrared (FT-IR) spectroscopy in the combination with chemometrics was developed for detection and quantification of WCO as adulterants in RSO. The quantification of WCO was carried out by using multivariate calibrations of partial least squares (PLS) and principle component regression (PCR). PLS with first derivative FT-IR spectra was more suitable compared with PCR for quantification purposes with coefficient of determination (R 2) higher than 0.998 and root mean square error of calibration (RMSEC) of 0.494 % (v/v). The PLS model was further used to predict the levels of WCO in independent samples for validation/prediction purpose. The proposed methodology is a useful tool to authenticate RSO adulterated with used WCO.
机译:目前,根据世界各地(尤其是中国)的食品安全性,检测掺入精制和净化废食用油(WCO)的菜籽油(RSO)对于研究人员而言是一项有吸引力的工作。对于更准确和灵敏的检测方法以应对食用油中更细微的掺假的需求迅速增长。因此,开发了傅里叶变换红外(FT-IR)光谱与化学计量学相结合的方法,用于检测和定量分析RSO中作为掺杂物的WCO。通过使用偏最小二乘(PLS)和主成分回归(PCR)的多元校准对WCO进行定量。与PCR相比,具有一阶导数FT-IR光谱的PLS更适合用于定量目的,测定系数(R 2)高于0.998,并且校准的均方根误差(RMSEC)为0.494%(v / v)。 PLS模型还用于预测独立样本中的WCO水平,以进行验证/预测。所提出的方法是验证用过的WCO掺入的RSO的有用工具。

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