基于拉曼光谱的三组分食用调和油快速定量检测

刘燕德; 靳昙昙; 王海阳

doi:10.3788/OPE.20152309.2490

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基于拉曼光谱的三组分食用调和油快速定量检测

现代应用光学 | 更新时间：2020-08-12

- 基于拉曼光谱的三组分食用调和油快速定量检测
- Rapid quantitative determination of components in ternary blended edible oil based on Raman spectroscopy
- 光学精密工程 2015年23卷第9期页码：2490-2496
- 作者机构：
  
  华东交通大学光机电技术及应用研究所,江西南昌,330013
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目资助(No.61178036,No.31160250)();江西省光电检测工程技术研究中心资助项目(No.赣科发财字[2012]155号)()
- DOI：10.3788/OPE.20152309.2490
  中图分类号： O657.373;TS225.1
- 收稿日期：2015-03-07，
  
  修回日期：2015-05-21，
  
  纸质出版日期：2015-09-25
- 稿件说明：
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刘燕德, 靳昙昙, 王海阳. 基于拉曼光谱的三组分食用调和油快速定量检测[J]. 光学精密工程, 2015,23(9): 2490-2496

LIU Yan-de, JIN Tan-tan, WANG Hai-yang. Rapid quantitative determination of components in ternary blended edible oil based on Raman spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2015,23(9): 2490-2496
刘燕德, 靳昙昙, 王海阳. 基于拉曼光谱的三组分食用调和油快速定量检测[J]. 光学精密工程, 2015,23(9): 2490-2496 DOI： 10.3788/OPE.20152309.2490.

LIU Yan-de, JIN Tan-tan, WANG Hai-yang. Rapid quantitative determination of components in ternary blended edible oil based on Raman spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2015,23(9): 2490-2496 DOI： 10.3788/OPE.20152309.2490.

摘要

应用激光拉曼光谱技术结合化学计量学方法实现了三组分食用调和油中菜籽油、花生油和芝麻油的快速定量检测。分别采用标准正态变量变换(SNV)+去趋势(de-trending)算法和正交信号校正(OSC)算法对600～3 000 cm

-1

波段的原始拉曼光谱进行预处理。建立了基于非线性支持向量机(SVM)和线性偏最小二乘(PLS)回归算法的定量分析模型

并采用19个预测集通过外部交叉验证法对模型进行验证。实验结果显示: 对含有菜籽油、花生油和芝麻油的三组分食用调和油

以OSC预处理后建立的线性PLS模型预测效果最好

其验证集决定系数

分别为0.990 4

0.965 8

0.977 1

均方根误差(RMSEP)分别为0.018 8

0.037 9

0.026 2。研究结果表明

利用激光拉曼光谱结合化学计量学方法快速定量检测三组分食用调和油中菜籽油、花生油和芝麻油的含量具有可行性

并获得了较高的预测精度。

Abstract

The rapeseed oil

peanut oil and sesame oil contents in ternary blended edible oil were measured quantitatively by laser Raman spectroscopy combined with the chemometric resolution method. Two kinds of pretreatment methods called Standard Normal Variate(SNV)+de-trending and Orthogonal Signal Correction(OSC) were used to process the original Raman spectra at 600—3 000 cm

-1

respectively. The quantification calibration models based on nonlinear Support Vector Machine(SVM) and linear Partial Least Squares (PLS) for the rapeseed oil

peanut oil and sesame oil were established

and nineteen prediction samples were predicted using the external cross-validation to verify the accuracy of these models. The results show that linear PLS model after the OSC spectral processing obtains the best result for ternary blended edible oil containing rapeseed oil

peanut oil and sesame oil. The determination coefficients(

)of the prediction are 0.990 4

0.965 8

0.977 1 and Root Mean Square Error of Prediction (RMSEP) are 0.018 8

0.037 9

0.026 2

respectively. The research results indicate that laser Raman spectroscopy combined with chemometric resolution method can be used for the determination of the contents for rapeseed oil

peanut oil and sesame oil in ternary blended edible oil

and can achieve excellent prediction precision.

关键词

Keywords

references

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