The development of fast, non-destructive, and green methods with adequate sensitivity for saffron authentication has important implications in the quality control of the entire production chain of this precious spice. In this context, the highly suitable sensitivity of a spectroscopic method coupled with chemometrics was verified. A total number of 334 samples were analyzed using attenuated-total-reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy; the collected spectra were processed by partial-least-squares discriminant analysis (PLS-DA) to evaluate the feasibility of this study for the discrimination between compliant saffron (fresh samples produced in 2020) and saffron samples adulterated with non-fresh stigmas produced in 2018 and 2016. PLS-DA was able to classify the saffron samples in accordance with the aging time and to discriminate fresh samples from the samples adulterated with non-fresh (legally expired) stigmas, achieving 100% of both sensitivity and specificity in external prediction. Moreover, PLS regression was able to predict the adulteration level with sufficient accuracy (the root-mean-square error of prediction was approximately 3-5%). In summary, ATR-FTIR and chemometrics can be employed to highlight the illegal blending of fresh saffron with unsold stocks of expired saffron, which may be a common fraudulent practice not yet considered in the scientific literature.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821794PMC
http://dx.doi.org/10.3390/molecules28010033DOI Listing

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The development of fast, non-destructive, and green methods with adequate sensitivity for saffron authentication has important implications in the quality control of the entire production chain of this precious spice. In this context, the highly suitable sensitivity of a spectroscopic method coupled with chemometrics was verified. A total number of 334 samples were analyzed using attenuated-total-reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy; the collected spectra were processed by partial-least-squares discriminant analysis (PLS-DA) to evaluate the feasibility of this study for the discrimination between compliant saffron (fresh samples produced in 2020) and saffron samples adulterated with non-fresh stigmas produced in 2018 and 2016.

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