Discrimination of Adulterated Milk Based on Infrared Spectroscopy and K-OPLS

YANG Yan-rong1; YANG Ren-jie1; ZHANG Zhi-yong1; DONG Gui-mei1; YANG Shi-chun2

doi:10.3788/OPE.20132110.2549

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Discrimination of Adulterated Milk Based on Infrared Spectroscopy and K-OPLS

更新时间：2020-08-12

- Discrimination of Adulterated Milk Based on Infrared Spectroscopy and K-OPLS
- Optics and Precision Engineering Vol. 21, Issue 10, Pages: 2549-2556(2013)
- 作者机构：
  
  1. 天津农学院农业分析测试中心天津,300384
  2. 天津农学院机电工程系天津,300384
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132110.2549
  CLC： O657.33
- Received：22 April 2013，
  
  Revised：08 June 2013，
  
  Published Online：19 October 2012，
  
  Published：15 October 2013
- 稿件说明：
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杨延荣杨仁杰张志勇董桂梅杨士春. 红外光谱结合核隐变量正交投影法判别掺杂牛奶[J]. 光学精密工程, 2013,21(10): 2549-2556

YANG Yan-rong YANG Ren-jie ZHANG Zhi-yong DONG Gui-mei YANG Shi-chun. Discrimination of Adulterated Milk Based on Infrared Spectroscopy and K-OPLS[J]. Editorial Office of Optics and Precision Engineering, 2013,21(10): 2549-2556
杨延荣杨仁杰张志勇董桂梅杨士春. 红外光谱结合核隐变量正交投影法判别掺杂牛奶[J]. 光学精密工程, 2013,21(10): 2549-2556 DOI： 10.3788/OPE.20132110.2549.

YANG Yan-rong YANG Ren-jie ZHANG Zhi-yong DONG Gui-mei YANG Shi-chun. Discrimination of Adulterated Milk Based on Infrared Spectroscopy and K-OPLS[J]. Editorial Office of Optics and Precision Engineering, 2013,21(10): 2549-2556 DOI： 10.3788/OPE.20132110.2549.

摘要

为了快速、准确地检测掺杂牛奶，采用基于核隐变量正交投影（K-OPLS）法分析了掺杂牛奶的光谱。选用高斯函数作为核函数，内部交叉验证均方根（RMSECV）最小值作为评价指标，优选了核函数中的核宽度以及Y正交成分数。配置含四环素牛奶（0.01~0.3 gL-1）、三聚氰胺牛奶（0.01~0.3 gL-1）和葡萄糖牛奶（0.01~0.3 gL-1）各36个，采集纯牛奶及掺杂牛奶样品的红外光谱，采用K-OPLS建立各掺杂牛奶与纯牛奶的判别模型。利用这些模型对未知样品进行判别，结果显示对掺杂四环素、三聚氰胺、葡萄糖牛奶的判别正确率分别为100%、100%、95.8%。建立了同时判别3种掺杂牛奶与纯牛奶的K-OPLS模型，该模型对未知样品的判别正确率为93.1%；同时，与偏最小二乘判别PLS-DA方法的预测结果进行了比较，结果表明：K-OPLS建模方法对于复杂的牛奶体系具有较好的预测能力。

Abstract

To detect adulterated milk rapidly and accurately

the discrimination models for adulterated milk were established based on the method of Kernel Orthogonal Projection to Latent Structure (K-OPLS). By using the Gaussian radial basis function as the kernel function and the minimum value of Root Mean Square Errors of Cross-validation (RMSECV)as an evaluation index

the width of the Gaussian kernel

the minimum value of the RMSECV

and the number of Y-orthogonal components (scalar) were selected in a optimization. 36 samples with different concentrations of tetracycline (0.01-0.3 gL-1)

melamine (0.01-0.3 gL-1) and glucose (0.01-0.3 gL-1) in milk were prepared

respectively. Then the infrared absorption spectra of all samples were measured. K-OPLS models for tetracycline-tainted milk

melamine-tainted milk and glucose-tainted milk were constructed. The results show that its classification accuracy for tetracycline-tainted milk

melamine-tainted milk and glucose-tainted milk are 100%

100%

95.8%

respectively. The K-OPLS model was used to classify the above three kinds of adulterated milk and pure milk and its classification accuracy for unknown samples is 93.1%. Compared with Partial Least Square Discriminant Analysis (PLS-DA)

K-OPLS methods show higher accuracy. The results indicate that the K-OPLS model has good prediction ability for complex milk systems.

关键词

Keywords

references

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江西农业大学工学院/生物光电及应用重点实验室

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