应用主成分和判别分析的红外光谱法快速鉴别酸败植物油

周俊; 张军; 谢梦圆; 陈哲; 汪勇; 关贺元

doi:10.13386/j.issn1002-0306.2015.12.002

应用主成分和判别分析的红外光谱法快速鉴别酸败植物油

周俊^1,2,
张军^1,2,
谢梦圆^1,2,
陈哲^1,2,
汪勇³,
关贺元^1,2

1. 光电信息与传感技术广东普通高校重点实验室(暨南大学)
2. 暨南大学光电工程系
3. 暨南大学食品科学与工程系

基金项目:

国家自然科学基金项目(61177075,61275046,61475066,61405075)；广东省战略性新兴产业核心技术攻关项目(2012A032300016,2012A080302004)；广东省学科建设专项资金项目(2013CXZDA005)；广东省自然科学基金项目(2014A030313377)；中央高校基本科研业务费专项资金项目(21614313,21615307)；

详细信息

作者简介:
周俊 (1990-) , 男, 在读硕士研究生, 研究方向:光谱分析。;

张军 (1968-) , 女, 博士, 研究员, 研究方向:光谱分析, 光电检测。;

中图分类号: O657.33;TS227
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出版历程
- 收稿日期: 2014-09-23

Rapid authentication of rancid edible oil based on fourier transform infrared spectroscopy of principal component and discrimination analysis

Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Ji'nan University
Department of Optoelectronic Engineering, Ji'nan University
Department of Food Science and Engineering, Ji'nan University

摘要

摘要: 通过收集并分析40个合格植物油和44个酸败植物油的傅里叶变换红外光谱,选取25个合格植物油和39个酸败植物油组成训练集,利用主成分分析获得累积可信度95%的三个主成分及对应的1743¹710cm-1、1172¹130cm-1、2945²844cm-1、1728¹689cm-1、2987²840cm-1和1731¹660cm-1对植物油酸败最为敏感的光谱波数范围。在主成分分析的基础上,选取对植物油酸败敏感的波段,利用训练集建立鉴别植物油酸败判别分析模型。采用验证集20个样品验证判别分析模型,判别正确率达100%。主成分结合判别分析的红外光谱法能快速、准确、无损地区分合格植物油和酸败植物油。
- 植物油酸败鉴别 /
- 主成分分析 /
- 判别分析 /
- 傅里叶变换红外光谱
Abstract: 40 qualified edible oils and 44 rancid ones were collected and analyzed. 25 qualified edible oils and39 rancid ones were selected to compose training set. Principal component analysis (PCA) was used to compress thousands of spectral data into several variables and describe the body of spectra, the analysis suggested that the accumulate reliabilities of PC1, PC2 and PC3 (the first three principle components) were more than 95%and corresponding 1743¹710cm-1, 1172¹130cm-1, 2945²844cm-1, 1728¹689cm-1, 2987 ²840cm-1and1731 ¹660cm-1were the most sensitive bands for edible oil rancidity. The training set was used to build discrimination analysis (DA) model, and then the most sensitive bands were applied as DA model inputs. The model was validated by other 20 samples as validation set with the correct recognition rate of 100%, which showed this method could be used to distinguish the rancid edible oil rapidly, accurately and soundly.
- authentication of rancid edible oil /
- principal component analysis /
- discrimination analysis /
- FTIR

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参考文献(20)

[1]	代小容, 刘伯云.潲水油研究进展[J].粮食与油脂, 2008 (4) :36-37.
[2]	季祥, 蔡禄.鉴别食用油脂中地沟油的方法探讨[J].技术油脂工程, 2010, 21 (3) :32-34.
[3]	孙丽琴, 孙立君, 郑刚.不同的存放条件对油脂酸价和过氧化值的影响[J].粮油检测与加工, 2007 (2) :45-46.
[4]	郧海丽, 刘树彬.食用植物油的抗氧化研究进展[J].煤炭与化工, 2013, 36 (4) :31-34.
[5]	潘红红.食用植物油脂品质监测和预警指标的研究[D].成都:成都理工大学, 2012.
[6]	董文丽, 李德溥.包装对松仁油脂氧化酸败抑制的研究[J].包装工程, 2014, 35 (17) :53-56.
[7]	侯景芳, 李桂霞, 李奕然, 等.浅谈油脂酸败及储存[J].农产品加工, 2013 (6) :60-62.
[8]	穆昭, 王兴国, 刘元法.加热过程煎炸油品质分析[J].油脂工程, 2008 (2) :65-67.
[9]	黄西文.食用油脂的酸败指标检测研究[J].科技信息, 2013 (22) :418.
[10]	Rohman A, Che M Y, Yusof F.The use of FTIR spectroscopy and chemometrics for rapid authentication of extra virgin olive oil[J].J Am Oil Chem Soc, 2014 (91) :207-213.
[11]	王美美, 范璐, 钱向明, 等.3种植物油傅里叶变换红外光谱信息的判别分析研究[J].中国油脂, 2009, 34 (10) :72-74.
[12]	谢梦圆, 张军, 陈哲, 等.地沟油的近红外光谱分析鉴别[J].中国油脂, 2011, 36 (12) :80-83.
[13]	李沂光, 单杨.近红外光谱法定性检测餐桌废弃油脂的掺伪[J].食品工业科技, 2013 (20) :87-90.
[14]	Tay A, Singh R K, Krishnan S S, et al.Authentication of olive oil adulterated with vegetable oils using Fourier transform infrared spectroscopy[J].LWT-Food Science and Technology, 2002, 35 (1) :99-103.
[15]	Luna A S, da Silva A P, FerréJ, et al.Classification of edible oils and modeling of their physico-chemical properties by chemometric methods using mid-IR spectroscopy[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2013, 100:109-114.
[16]	刘玲玲.应用红外光谱技术进行食用油真伪及掺伪的快速鉴定[D].北京:北京林业大学, 2012.
[17]	毕艳兰.油脂化学[M].北京:化学工业出版社, 2005:1-7.
[18]	Rohman A, Man Y B.Fourier transform infrared (FTIR) spectroscopy for analysis of extra virgin olive oil adulterated with palm oil[J].Food Research International, 2010, 43 (3) :886-892.
[19]	潘剑宇, 尹平河.潲水油、煎炸老油与合格食用植物油的鉴别研究[J].食品科学, 2003 (8) :27-29.
[20]	刘玲玲, 武彦文.傅里叶变换红外光谱结合模式识别法快速鉴别食用油真伪[J].化学学报, 2012 (8) :995-1000.