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. 2020 Jul 16;9(7):944.
doi: 10.3390/foods9070944.

The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools

Pamela Galvin-King  1 , Simon A Haughey  1 , Christopher T Elliott  1
Affiliations

The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools

Pamela Galvin-King et al. Foods. .

Abstract

The spice paprika (Capsicum annuum and frutescens) is used in a wide variety of cooking methods as well as seasonings and sauces. The oil, paprika oleoresin, is a valuable product; however, once removed from paprika, the remaining spent product can be used to adulterate paprika. Near-infrared (NIR) and Fourier transform infrared (FTIR) were the platforms selected for the development of methods to detect paprika adulteration in conjunction with chemometrics. Orthogonal partial least squares discriminant analysis (OPLS-DA), a supervised technique, was used to develop the chemometric models, and the measurement of fit (R2) and measurement of prediction (Q2) values were 0.853 and 0.819, respectively, for the NIR method and 0.943 and 0.898 respectively for the FTIR method. An external validation set was tested against the model, and a receiver operating curve (ROC) was created. The area under the curve (AUC) for both methods was highly accurate at 0.951 (NIR) and 0.907 (FTIR). The levels of adulteration with 100% correct classification were 50-90% (NIR) and 40-90% (FTIR). Sudan I dye is a commonly used adulterant in paprika; however, in this study it was found that this dye had no effect on the outcome of the result for spent material adulteration.

Keywords: Fourier transform infrared; chemometrics; economically motivated adulteration; near-infrared; paprika.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Near-infrared (NIR) (A) and Fourier transform infrared (FTIR) (B) raw spectral data of paprika and spent paprika.
Figure 1
Figure 1
Near-infrared (NIR) (A) and Fourier transform infrared (FTIR) (B) raw spectral data of paprika and spent paprika.
Figure 2
Figure 2
NIR (A) principal component analysis (PCA) (Unsupervised) and (B) OPLS-DA (Supervised) classification models for paprika and spent material.
Figure 3
Figure 3
FTIR (A) PCA (Unsupervised) and (B) orthogonal partial least squares discriminant analysis (OPLS-DA) (Supervised) classification models for paprika and spent material.
Figure 4
Figure 4
Receiver operating curves (ROC) and Youden index for NIR (A) and FTIR (B) test methods.
Figure 5
Figure 5
OPLS-DA models (left) and predicted 100% and 50% spent paprika spiked with Sudan I dye ranging from 0–5% (right) on NIR (A) and FTIR (B).
See this image and copyright information in PMC

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