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Food Qual Safet
Research Articles     
近红外光谱和化学计量学技术结合检测特级初榨橄榄油掺假
Detection of the adulteration of extra virgin olive oil by near-infrared spectroscopy and chemometric techniques
Nick Vanstone,*,** Andrew Moore,** Perry Martos** and Suresh Neethirajan*
*BioNano Laboratory, School of Engineering, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1, Canada, **Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, 95 Stone Road West, Guelph, Ontario N1G 2Z4, Canada
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摘要:

前言和目标:特级初榨橄榄油(EVOO)的较高的价值导致其掺假成为行业重要问题,从而产生了对快速且廉价的鉴伪测试的需求。与许多当前的食品鉴伪检测方法相比,近红外光谱(NIRS)通过最小化样品制备和测量时间,其价格低且操作方便。在本研究中,我们开发了一种方法,使用NIRS和化学计量学来检测EVOO掺假,不需要样品制备并且可以在不到10分钟内完成。

方法、结果和讨论:首先,EVOO中掺入玉米油的比例从2.7%至25%(w / w)。测量未掺杂样品及其掺杂对应物的光谱。主成分分析(PCA)得分图显示掺假混合物与未掺杂样品之间的区别,这表明如果提供了其他食用油的未掺杂样品,所开发的方法检测可低至2.7w / w。为了检测掺假而没有未掺杂样品供参考条件下,测量了未掺杂的样品和掺有玉米、向日葵、大豆和菜籽油的样品光谱。使用无监督模式建模的PCA进行掺假检测,发现玉米、向日葵、大豆和菜籽油的掺假检测下限分别为约20%、20%、15%和10%。

结论:结果表明,所开发的方法可用于快速筛选掺假橄榄油。

关键词: 橄榄油掺假光谱学化学计量学近红外光谱主成分分析    
Abstract:
Introduction and Objectives: Due to the value of extra virgin olive oil (EVOO), adulteration has become an important issue in the industry, which has created demand for quick and inexpensive fraud detection testing. In contrast to many current food fraud detection methods, near-infrared spectroscopy (NIRS) can be inexpensive and convenient by minimizing sample preparation and measurement times. In this study, we developed a method using NIRS and chemometrics to detect adulteration of EVOO with other edible oil types that does not require sample preparation and can be completed in less than 10 min.
Methods, Results, and Discussions: First, a single EVOO was adulterated with corn oil from 2.7% to 25% w/w. Spectra for the unadulterated sample and its adulterated counterparts were measured. A principal component analysis (PCA) scores plot showed separation between the adulterated mixtures and the unadulterated sample, which demonstrated that the developed method could
detect as low as 2.7% w/w adulteration if an unadulterated sample of the oil in question is provided. To study adulteration detection without an unadulterated sample for reference, the spectra of unadulterated samples and samples adulterated with corn, sunflower, soybean, and canola oils were measured. A PCA with soft independent modelling of class analogy was used for adulteration detection. Lower limits of adulteration detection for corn, sunflower, soybean, and canola oils were found to be approximately 20%, 20%, 15%, and 10%, respectively.
Conclusions: These results demonstrate that the developed method can be used to rapidly screen for adulterated olive oils.
Key words: olive oil adulteration    spectroscopy    chemometrics    NIR    principal component analysis
收稿日期: 2017-11-15 出版日期: 2018-11-07
通讯作者: Nick Vanstone, Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, 95 Stone Road West, Guelph, Ontario N1G 2Z4, Canada.     E-mail: vanstonn@uoguelph.ca
作者简介: Nick Vanstone, Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, 95 Stone Road West, Guelph, Ontario N1G 2Z4, Canada. E-mail: vanstonn@uoguelph.ca
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引用本文:

Nick Vanstone, Andrew Moore, Perry Martos and Suresh Neethirajan. Detection of the adulteration of extra virgin olive oil by near-infrared spectroscopy and chemometric techniques. Food Qual Safet, 10.1093/fqsafe/fyy018.

链接本文:

http://www.zjujournals.com/fqs/CN/10.1093/fqsafe/fyy018        http://www.zjujournals.com/fqs/CN/Y2018/V2/I4/189

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