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Detection of Lard in Ink Extracted from Printed Food Packaging Using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

机译:傅立叶变换红外光谱法和多元分析法检测食品包装印刷油墨中的猪油

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摘要

Fourier transform infrared (FTIR) spectroscopy combined with chemometrics was utilised to discriminate the presence of lard in extracted ink of printed food packaging. Two spectral regions (full spectra, 3999-649 cm(-1), and combination of two regions, 31102630 cm(-1) and 1940-649 cm(-1)) of lard, commercial gravure ink, and the blends of both were selected and used to develop a Soft Independent Modelling of Class Analogy (SIMCA) model. The score plots obtained from the Principal Component Analysis (PCA) revealed that the maximum number of factors (7 factors) was needed to explain 84% of the total variance. SIMCA was employed as the method to classify the samples into their specific groups. Si versus Hi plots showed that the calibration standards can be classified as lard-containing standards. Sample 2 was deduced to have the highest possibility of containing lard, while only samples 5 and 7 cannot be classified as lard-containing samples. These results demonstrated that FTIR spectroscopy, when combined with multivariate analysis, can provide a rapid method with no excessive sample preparation to detect the presence of lard in ink of foodstuff packaging.
机译:傅里叶变换红外(FTIR)光谱与化学计量学相结合,用于区分印刷食品包装中提取的油墨中猪油的存在。猪油,商业凹版油墨的两个光谱区域(全光谱,3999-649 cm(-1),以及两个区域的组合,31102630 cm(-1)和1940-649 cm(-1)),以及两种油的混合物选择并用于开发类比的软独立建模(SIMCA)模型。从主成分分析(PCA)获得的得分图显示,需要最多数量的因子(7个因子)来解释总方差的84%。采用SIMCA作为将样品分类为特定组的方法。 Si对Hi的图表明,校准标准品可以归类为含猪油的标准品。推断出样品2含有猪油的可能性最高,而只有样品5和7无法分类为含猪油的样品。这些结果表明,FTIR光谱与多变量分析相结合,可以提供一种快速的方法,而无需进行过多的样品前处理即可检测食品包装油墨中猪油的存在。

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