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Fast Methodology for Identification of Olive Oil Adulterated with a Mix of Different Vegetable Oils

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Abstract

This paper investigated the application of Fourier transform infrared spectroscopy (FTIR) with partial least squares regression algorithms (PLS) and variable selection methods for the rapid identification of extra virgin olive oil (EVOO) adulterated with different vegetable oils. For this purpose, a unique calibration model was proposed for the identification and quantification of adulteration independent of the adulterating oil. Calibration models were developed for simultaneous determination of the concentration of oleic, linoleic and linolenic fatty acids. Robust models were also developed for quantification of the percentage of adulteration in the samples, independent of the adulterating oil. The calibration set consisted of 68 adulterated EVOO samples, prepared by the addition of vegetable oils (soybean, sunflower, corn, and canola oil) at different levels (1 to 80%, v/v), and ten commercial samples of EVOO were used to validate the models. The mid-infrared spectra were recorded in the wave number range 3200 to 650 cm−1 for all samples. Chromatographic analysis was performed to determine the fatty acid profile of the samples from the calibration and prediction sets. PLS models were developed and different strategies were investigated during the preprocessing of the IR spectra. The results of the prediction were compared with those obtained from the conventional analysis, and RMSEP values of 4.44, 1.92, and 0.62% were obtained for oleic, linoleic, and linolenic acids, respectively. The proposed methodology allowed us to quantify the acids simultaneously in the samples and also demonstrated a good predictive power to identify the adulterated samples.

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Acknowledgments

The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

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Authors and Affiliations

  1. Programa de Pós-Graduação em Sistema e Processos Industriais, Santa Cruz do Sul, RS, 96815-900, Brazil

    Paula Freitas Filoda, Lucas Flores Fetter, Aline Teichmann & Adilson Ben da Costa

  2. Departamento de Química e Fisica, Santa Cruz do Sul, RS, 96815-900, Brazil

    Franccesca Fornasier, Rosana de Cassia de Souza Schneider & Adilson Ben da Costa

  3. Programa de Pós-Graduação em Tecnologia Ambiental, Santa Cruz do Sul, RS, 96815-900, Brazil

    Rosana de Cassia de Souza Schneider

  4. Departamento de Computação, Universidade de Santa Cruz do Sul, Santa Cruz do Sul, RS, 96815-900, Brazil

    Gilson Augusto Helfer

  5. Instituto de Ciência e Tecnologia de Alimentos, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 91501-970, Brazil

    Bruna Tischer

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  1. Paula Freitas Filoda
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  2. Lucas Flores Fetter
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Correspondence to Adilson Ben da Costa.

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Filoda, P.F., Fetter, L.F., Fornasier, F. et al. Fast Methodology for Identification of Olive Oil Adulterated with a Mix of Different Vegetable Oils. Food Anal. Methods 12, 293–304 (2019). https://doi.org/10.1007/s12161-018-1360-5

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