Literature DB >> 14518936

Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using Raman spectroscopy and chemometrics.

E Consuelo López-Díez1, Giorgio Bianchi, Royston Goodacre.   

Abstract

The authentication of extra virgin olive oil and its adulteration with lower-priced oils are serious problems in the olive oil industry. In addition to the obvious effect on producer profits, adulteration can also cause severe health and safety problems. A number of techniques, including chromatographic and spectroscopic methods, have recently been employed to assess the purity of olive oils. In this study Raman spectroscopy together with multivariate and evolutionary computational-based methods have been employed to assess the ability of Raman spectroscopy to discriminate between chemically very closely related oils. Additionally, the levels of hazelnut oils used to adulterate extra virgin olive oil were successfully quantified using partial least squares and genetic programming.

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Year:  2003        PMID: 14518936     DOI: 10.1021/jf034493d

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  5 in total

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2.  Quantification and classification of corn and sunflower oils as adulterants in olive oil using chemometrics and FTIR spectra.

Authors:  Abdul Rohman; Y B Che Man
Journal:  ScientificWorldJournal       Date:  2012-02-01

3.  A rapid method to authenticate vegetable oils through surface-enhanced Raman scattering.

Authors:  Ming Yang Lv; Xin Zhang; Hai Rui Ren; Luo Liu; Yong Mei Zhao; Zheng Wang; Zheng Long Wu; Li Min Liu; Hai Jun Xu
Journal:  Sci Rep       Date:  2016-03-18       Impact factor: 4.379

4.  Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey.

Authors:  Shuhan Hu; Hongyi Li; Chen Chen; Cheng Chen; Deyi Zhao; Bingyu Dong; Xiaoyi Lv; Kai Zhang; Yi Xie
Journal:  Sci Rep       Date:  2022-03-02       Impact factor: 4.379

Review 5.  A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends.

Authors:  Xihui Bian; Yao Wang; Shuaishuai Wang; Joel B Johnson; Hao Sun; Yugao Guo; Xiaoyao Tan
Journal:  Foods       Date:  2022-08-13
  5 in total

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