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Detection of adulteration in Iranian saffron samples by 1H NMR spectroscopy and multivariate data analysis techniques

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Abstract

Introduction

The high market value of saffron (Crocus sativus L.) has made it an attractive candidate for adulteration. Safflower (Carthamus tinctorius L.) and tartrazine are among the most common herbal and synthetic foreign materials that may be added to pure saffron for the purpose of adulteration. In spite of encouraging advances achieved in the identification of adulteration in saffron samples, the lack of a simple method with sufficient power for discrimination of pure high grade saffron from meticulously adulterated saffron samples persuaded us to perform this study.

Objectives

In this work, we show that 1H NMR spectroscopy together with chemometric multivariate data analysis methods can be used for the detection of adulteration in saffron.

Methods

Authentic Iranian saffron samples (n = 20) and adulterated samples that were prepared by adding either different quantities of natural plant materials such as safflower, or synthetic dyes such as tartrazine or naphthol yellow to pure saffron (n = 22) composed the training set. This training set was used to build multivariate Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) models. The predictive power of the PLS-DA model was validated by testing the model against an external dataset (n = 13).

Results

PCA and PLS-DA models could both discriminate between the authentic and adulterated samples, and the external validation showed 100% sensitivity and specificity for predicting the authenticity of suspicious samples. Peaks specific to authentic and adulterated samples were also characterized. Proximity of samples with unknown adulteration status to the samples adulterated with known compounds in the PCA provided insight regarding the identity of the adulterant in the suspicious samples. Furthermore, the authentic samples could be distinguished based on their cultivation site.

Conclusion

The present study demonstrates that the application of 1H NMR spectroscopy coupled with multivariate data analysis is a suitable approach for detection of adulteration in saffron specimens. Outstanding sensitivity and specificity of the PLS-DA model in discriminating the authentic from adulterated samples in external validation confirmed the high predictive power of the model. The advantage of the present method is its power for detecting a wide spectrum of adulterants, ranging from synthetic dyes to herbal materials, in a single assay.

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Acknowledgements

This study was supported by the Armstrong Chair in Molecular Cancer Epidemiology Research (to HJV), which in turn is funded by the Alberta Cancer Foundation. RD was supported by the Faculty of Pharmacy and the Research Council of Tehran University of Medical Sciences.

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Authors and Affiliations

  1. Department of Biological Sciences, Bio-NMR-Centre, University of Calgary, Alberta, Canada

    Reza Dowlatabadi & Hans J. Vogel

  2. Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran

    Reza Dowlatabadi, Zohreh Zare & Morteza Pirali

  3. Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Alberta, Canada

    Farshad Farshidfar & Hans J. Vogel

  4. Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Farshad Farshidfar

  5. Food and Drug Control Laboratory Research Centre, Food and Drug Organization, Tehran, Iran

    Morteza Pirali & Maryam Rabiei

  6. Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Khoshayand

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  1. Reza Dowlatabadi
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  2. Farshad Farshidfar
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  7. Hans J. Vogel
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Correspondence to Hans J. Vogel.

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Dowlatabadi, R., Farshidfar, F., Zare, Z. et al. Detection of adulteration in Iranian saffron samples by 1H NMR spectroscopy and multivariate data analysis techniques. Metabolomics 13, 19 (2017). https://doi.org/10.1007/s11306-016-1155-x

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