NIR spectroscopy-multivariate analysis for rapid authentication, detection and quantification of common plant adulterants in saffron (Crocus sativus L.) stigmas

Abstract The presented work discusses the development of a rapid and precise analytical protocol using near infrared spectroscopy combined with multivariate data analysis to authenticate, detect and quantify most of the commonly encountered plant adulterants used in fraud of saffron stigmas including safflower, pomegranate fruit peel, calendula flower, paprika, curcuma, hibiscus, saffron stamens and exhaustively-extracted saffron stigmas. A Soft Independent Modelling of Class Analogies (SIMCA) model was constructed for authentication of saffron stigmas with 100% sensitivity and a Partial Least Squares-Discriminant Analysis (PLS-DA) model was successfully utilized for correct discrimination of unadulterated and intentionally adulterated saffron samples as it showed 100% sensitivity and 99% specificity. Quantitation of the amount of each individual adulterant was achieved through construction of partial least squares regression (PLSR) models accompanied by variable importance to projection (VIP) method for variable selection which revealed that bands in the spectral ranges 6000-5800 cm−1 followed by 4600–4200 cm−1 and 5400-5000 cm−1 were the most important for correct prediction with detection limits as low as 1%. The models performance was tested using internal and external validation sets indicating their reliability in providing a useful quality assessment tool for saffron in an attempt to prevent its fraud.