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The chemometrics approach applied to FTIR spectral data for the analysis of rice bran oil in extra virgin olive oil

机译:化学计量学方法应用于FTIR光谱数据分析特级初榨橄榄油中的米糠油

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Among eleven studied vegetable oils, rice bran oil (RBO) has the close similarity to extra virgin olive oil (EVOO) in terms of FTIR spectra, as shown in the score plot of first and second principal components. The peak intensities at 18 frequency regions were used as matrix variables in principal component analysis (PCA). Consequently, the presence of RBO in EVOO is difficult to detect. This study aimed to use the chemometrics approach, namely discriminant analysis (DA) and multivariate calibrations of partial least square and principle component regression to analyze RBO in EVOO. DA was used for the classification of EVOO and EVOO mixed with RBO. Multivariate calibrations were exploited for the quantification of RBO in EVOO. The combined frequency regions of 1200-900 and 3020-3000 cm~(-1) were used for such analysis. The results showed that no misclassification was reported for the classification of EVOO and EVOO mixed with RBO. Partial least square regression either using normal or first derivative FTIR spectra can be successfully used for the quantification of RBO in EVOO. In addition, analysis of fatty acid composition can complement the results obtained from FTIR spectral data.
机译:如第一和第二主要成分的分数图所示,在11种研究过的植物油中,米糠油(RBO)与特级初榨橄榄油(EVOO)具有相似的FTIR光谱。在主成分分析(PCA)中,将18个频率区域的峰强度用作矩阵变量。因此,很难检测到EVOO中存在RBO。这项研究旨在使用化学计量学方法,即判别分析(DA)和偏最小二乘和主成分回归的多元校准来分​​析EVOO中的RBO。 DA被用于EVOO的分类以及与RBO混合的EVOO。利用多变量校准对EVOO中的RBO进行定量。分析使用了1200-900和3020-3000 cm〜(-1)的组合频率区域。结果表明,没有报告关于EVOO和EVOO与RBO混合的分类错误。使用正态或一阶FTIR光谱进行的偏最小二乘回归可成功用于EVOO中RBO的定量。此外,脂肪酸组成的分析可以补充从FTIR光谱数据获得的结果。

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