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Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection

Amirvaresi, A ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1016/j.foodchem.2020.128647
  3. Publisher: Elsevier Ltd , 2021
  4. Abstract:
  5. In this work, the potential of near-infrared (NIR) and mid-infrared (MIR) spectroscopy along with chemometrics was investigated for authentication and adulteration detection of Iranian saffron samples. First, authentication of one-hundred saffron samples was examined by principal component analysis (PCA). The results showed the NIR spectroscopy can better predict the origin of samples than the MIR. Next, partial least squares-discriminant analysis (PLS-DA) was developed to detect four common plant-derived adulterants (i.e., saffron style, calendula, safflower, and rubia). In all cases, PLS-DA classification figures of merit in terms of sensitivity, specificity, error rate and accuracy were satisfactory for both NIR and MIR datasets. The built models were then successfully validated using test set and also commercial samples. Finally, partial least squares regression (PLSR) was used to estimate the amount of adulteration. In this case, only NIR showed a good performance with regression coefficients (R2) in range of 0.95–0.99. © 2020 Elsevier Ltd
  6. Keywords:
  7. Authentication ; Food additives ; Least squares approximations ; Near infrared spectroscopy ; Spectrum analysis ; Chemometrics ; Figures of merits ; Mid-infrared spectroscopy ; Near infra red ; NIR spectroscopy ; Partial least squares discriminant analyses (PLSDA) ; Partial least squares regressions (PLSR) ; Regression coefficient ; Infrared devices ; Calendula ; Discriminant analysis ; Major clinical study ; Nonhuman ; Partial least squares regression ; Principal component analysis ; Rubia ; Safflower ; Sensitivity and specificity ; Chemistry ; Comparative study ; Information science ; Least square analysis ; Prevention and control ; Procedures ; Crocus ; Fraud ; Informatics ; Least-Squares Analysis ; Spectroscopy, Near-Infrared
  8. Source: Food Chemistry ; Volume 344 , 2021 ; 03088146 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0308814620325097