分析与检测

多元线性回归-分光光度法同时测定食用油中的邻苯二甲酸酯类物质

  • 李瑞月 ,
  • 钟山 ,
  • 张漓杉 ,
  • 符芬华 ,
  • 韦锃弦
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  • 1(桂林电子科技大学 生命与环境科学学院,广西 桂林,541004)
    2(桂林云璟科技有限公司,广西 桂林,541004)
第一作者:硕士研究生(钟山教授为通信作者,E-mail:11271947@qq.com)

收稿日期: 2022-09-28

  修回日期: 2022-11-18

  网络出版日期: 2023-11-20

基金资助

广西科技基地和人才专项(桂科AD19259005);桂林市科技重大专项(20190203-2)

Simultaneous determination of phthalates in edible oil by multiple linear regression and spectrophotometry

  • LI Ruiyue ,
  • ZHONG Shan ,
  • ZHANG Lishan ,
  • FU Fenhua ,
  • WEI Zengxian
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  • 1(School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China)
    2(Guilin Yunjing Technology Limited Company, Guilin 541004, China)

Received date: 2022-09-28

  Revised date: 2022-11-18

  Online published: 2023-11-20

摘要

该研究建立了多元线性回归分析(multiple linear regression,MLR)结合紫外-可见分光光度法同时测定食用油中邻苯二甲酸酯类(phthalic acid esters,PAEs)增塑剂的分析方法。样品经乙腈提取、Silica/乙二胺-N-丙基硅烷(primary-secondary amine,PSA)复合填料玻璃固相萃取柱净化浓缩等预处理后,用紫外-可见分光光度计进行波段扫描,多元线性回归分析模型定性定量。基于市场上食用油样品中PAEs含量的浓度分布范围及其与吸光度的线性关系建立PAEs预报模型A和PAEs预报模型B,分别应用于邻苯二甲酸二丁酯(dibutyl phthalate,DBP)、邻苯二甲酸二辛酯(dioctyl phthalate,DOP)、邻苯二甲酸丁苄酯(benzyl butyl phthalate,BBP)3种PAEs同时测定和DBP、DOP2种PAEs同时测定。该方法模型A对于DBP、DOP、BBP的定量限分别为0.125、0.100、0.150 mg/kg,回收率为93%~111%,相对标准偏差(relative standard deviation,RSD)为3.86%~7.09%;模型B中DBP、DOP的定量限分别为0.250、0.375 mg/kg,回收率为95%~103%,RSD为2.22%~4.17%。两模型可按不同类型食用油样品及不同测定需求进行选择,模型B所测DBP、DOP是塑料制品中最常用的2种增塑剂,且具有较高精度。该方法对食用油中DBP、DOP、BBP的含量进行分析测定结果与高效液相色谱法基本相近,相对误差(relative error,RE)均小于±8%。该研究方法重现性较好,精密度较高,无需使用大型仪器,快速、方便、简易的同时具有一定准确性。

本文引用格式

李瑞月 , 钟山 , 张漓杉 , 符芬华 , 韦锃弦 . 多元线性回归-分光光度法同时测定食用油中的邻苯二甲酸酯类物质[J]. 食品与发酵工业, 2023 , 49(20) : 300 -308 . DOI: 10.13995/j.cnki.11-1802/ts.033758

Abstract

A method was developed for the simultaneous determination of phthalic acid esters (PAEs) in edible oils by multiple linear regression (MLR) combined with UV-vis spectrophotometry. The samples were extracted by acetonitrile, cleaned up and concentrated by Silica/primary-secondary amine (PSA) composite packed glass solid phase extraction column and pretreated with UV-vis spectrophotometer for waveband scanning and multiple linear regression analysis models for qualitative quantification. The PAEs prediction model A and PAEs prediction model B were developed based on the concentration distribution range of PAEs in edible oil samples in the market and their linear relationship with absorbance, and applied to the simultaneous determination of three PAEs, dibutyl phthalate (DBP), dioctyl phthalate (DOP), and benzyl butyl phthalate (BBP), and two PAEs, DBP, and DOP, respectively. The limits of quantification of DBP, DOP, and BBP in model A were 0.125 mg/kg, 0.100 mg/kg, and 0.150 mg/kg, respectively, with the recoveries of 93%-111% and the relative standard deviations (RSDs) of 3.86%-7.09%. The limits of quantification of DBP and DOP in model B were 0.250 mg/kg and 0.375 mg/kg. The limits of quantification for DBP and DOP in model B were 0.250 mg/kg and 0.375 mg/kg, respectively, with recoveries of 95%-103% and RSDs of 2.22%-4.17%. The two models can be selected according to different types of edible oil samples and different determination needs. DBP and DOP measured by model B are the two most commonly used plasticizers in plastic products and have high accuracy. The analytical results of this method for the determination of DBP, DOP, and BBP in edible oil were similar to those of the high-performance liquid chromatography method, with a relative error (RE) of less than ±8%. The method has good reproducibility, high precision, no need to use large instruments, fast, convenient and easy while having certain accuracy.

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