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利用傅里叶变换红外光谱和化学计量学对原生和回收聚苯乙烯泡沫塑料容器进行快速分类

Rapid classification of virgin and recycled EPS containers by Fourier transform infrared spectroscopy and chemometrics.

作者信息

Song Xue-Chao, Lin Qin-Bao, Zhang Yi-Cai, Li Zhong, Zeng Yu, Chen Zhi-Feng

机构信息

a Key Laboratory of Product Packaging and Logistics , Packaging Engineering Institute, Jinan University , Zhuhai , China.

b Chemical Analysis Laboratory , Zhuhai Border Inspection and Quarantine Bureau , Zhuhai , China.

出版信息

Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2018 Nov;35(11):2220-2229. doi: 10.1080/19440049.2018.1515502. Epub 2018 Oct 10.

Abstract

A rapid and sensitive method for classification of virgin and recycled expanded polystyrene (EPS) food containers was developed using Fourier transform infrared spectroscopy (FTIR) and chemometrics. This method includes preparing a transparent film by dissolution, examining by FTIR and developing classification models. The degradation of EPS containers occurring during the recycling process was reflected by the carbonyl region of the infrared spectrum which was used as variables for multivariate data analysis. PCA was used to reduce the data dimension and view the sample similarities. Soft independent modelling of class analogy (SIMCA), partial least squares-discrimination analysis (PLS-DA) and linear discrimination analysis (LDA) were applied to construct three classification models. The best discrimination results were obtained by an LDA model, with all samples correctly classified. PLS-DA and SIMCA could not classify the recycled EPS samples with low levels of adulteration. When applying this method to commercially available EPS containers, about 45% of samples were shown to contain recycled polystyrene resins. It is concluded that the carbonyl region of the infrared spectra coupled with chemometrics could be a powerful tool for the classification of virgin and recycled EPS food containers.

摘要

采用傅里叶变换红外光谱(FTIR)和化学计量学方法,开发了一种快速灵敏的方法用于区分原生和回收的发泡聚苯乙烯(EPS)食品容器。该方法包括通过溶解制备透明薄膜、用FTIR进行检测以及建立分类模型。红外光谱的羰基区域反映了回收过程中EPS容器发生的降解情况,该区域用作多变量数据分析的变量。主成分分析(PCA)用于降低数据维度并查看样品的相似性。应用类相关软独立建模(SIMCA)、偏最小二乘判别分析(PLS-DA)和线性判别分析(LDA)构建了三种分类模型。LDA模型获得了最佳判别结果,所有样品均被正确分类。PLS-DA和SIMCA无法对低掺假水平的回收EPS样品进行分类。将该方法应用于市售EPS容器时,约45%的样品被证明含有回收的聚苯乙烯树脂。结论是,红外光谱的羰基区域结合化学计量学可成为区分原生和回收EPS食品容器的有力工具。

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