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Blends of olive oil and seeds oils: Characterisation and olive oil quantification using fatty acids composition and chemometric tools. Part Ⅱ

机译:橄榄油和种子油的混合物:使用脂肪酸组成和化学计量工具进行表征和橄榄油定量。第二部分

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摘要

A method to verify the percentage of olive oil in a blend, in compliance with the Commission Regulation EU No. 29/2012, was developed by GC-FID analysis of methyl esters of fatty acids, followed by chemometric tools (PCA, TFA, SIMCA and PLS). First of all, binary blends of twelve olive oils and one sunflower oil were studied, in order to evaluate the variability associated to the fatty acids profile of olive oils (Monfreda, Gobbi, & Grippa, 2012). In this study, binary blends of twelve olive oils with four types of seeds oils (peanut, corn, rice and grape seed oils) were evaluated. These four groups of blends were analysed and processed separately, each group consisting of 36 samples with 40%, 50% and 60% of olive oil content. Chemometric tools were also applied to the global data set (180 samples, including those analysed in the previous paper). Outstanding results were achieved, showing that the proposed method would be capable to discriminate blends with a difference in concentration of olive oil lower than 5% (a standard error of prediction of 3.97% was obtained with PLS). Therefore blends containing 45% and 55% of olive oil were also analysed with the current method and added to the data sets for chemometric assessment with supervised tools. SIMCA still provided good models; however the best performance was achieved by processing each group of binary blends (consisting of 60 samples) separately, rather than applying SIMCA to the overall data set (300 samples). On the other hand PLS did not show significant improvements.
机译:通过对脂肪酸甲酯的GC-FID分析以及随后的化学计量工具(PCA,TFA,SIMCA)开发了一种符合欧盟法规29/2012的用于验证混合物中橄榄油含量的方法和PLS)。首先,研究了十二种橄榄油和一种葵花籽油的二元共混物,以评估与橄榄油的脂肪酸谱相关的变异性(Monfreda,Gobbi和Grippa,2012)。在这项研究中,评估了十二种橄榄油与四种种子油(花生,玉米,大米和葡萄籽油)的二元共混物。分别分析和处理了这四组共混物,每组共36个样品,橄榄油含量分别为40%,50%和60%。化学计量学工具也被应用于全球数据集(180个样本,包括先前论文中分析的样本)。取得了出色的结果,表明所提出的方法将能够区分橄榄油浓度差异低于5%的混合物(PLS的预测标准误为3.97%)。因此,还使用当前方法分析了含有45%和55%橄榄油的掺混物,并使用监督工具将其添加到化学计量评估数据集中。 SIMCA仍然提供了很好的模型;但是,通过分别处理每组二元混合(包含60个样本),而不是将SIMCA应用于整个数据集(300个样本),可以获得最佳性能。另一方面,PLS没有显示出明显的改进。

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