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Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection.
Food Chem. 2021 May 15; 344:128647.FC

Abstract

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.

Authors+Show Affiliations

Department of Chemistry, Sharif University of Technology, Tehran, Iran.Food and Drug Laboratory Research Center, Food and Drug Organization, Tehran, Iran.Food and Drug Laboratory Research Center, Food and Drug Organization, Tehran, Iran.Department of Toxicology and Pharmacology, School of Pharmacy, Shahid Beheshti University of Medical Science, Tehran, Iran.Department of Chemistry, Sharif University of Technology, Tehran, Iran. Electronic address: h.parastar@sharif.edu.

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

33229154

Citation

Amirvaresi, Arian, et al. "Comparison of Near-infrared (NIR) and Mid-infrared (MIR) Spectroscopy Based On Chemometrics for Saffron Authentication and Adulteration Detection." Food Chemistry, vol. 344, 2021, p. 128647.
Amirvaresi A, Nikounezhad N, Amirahmadi M, et al. Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection. Food Chem. 2021;344:128647.
Amirvaresi, A., Nikounezhad, N., Amirahmadi, M., Daraei, B., & Parastar, H. (2021). Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection. Food Chemistry, 344, 128647. https://doi.org/10.1016/j.foodchem.2020.128647
Amirvaresi A, et al. Comparison of Near-infrared (NIR) and Mid-infrared (MIR) Spectroscopy Based On Chemometrics for Saffron Authentication and Adulteration Detection. Food Chem. 2021 May 15;344:128647. PubMed PMID: 33229154.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection. AU - Amirvaresi,Arian, AU - Nikounezhad,Nastaran, AU - Amirahmadi,Maryam, AU - Daraei,Bahram, AU - Parastar,Hadi, Y1 - 2020/11/16/ PY - 2020/07/13/received PY - 2020/11/11/revised PY - 2020/11/11/accepted PY - 2020/11/25/pubmed PY - 2021/1/21/medline PY - 2020/11/24/entrez KW - Adulteration KW - Authentication KW - Chemometrics KW - Mid-infrared spectroscopy KW - Near-infrared spectroscopy KW - Saffron SP - 128647 EP - 128647 JF - Food chemistry JO - Food Chem VL - 344 N2 - 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. SN - 1873-7072 UR - https://www.unboundmedicine.com/medline/citation/33229154/Comparison_of_near_infrared__NIR__and_mid_infrared__MIR__spectroscopy_based_on_chemometrics_for_saffron_authentication_and_adulteration_detection_ DB - PRIME DP - Unbound Medicine ER -