Rapid detection of saffron (Crocus sativus L.) Adulterated with lotus stamens and corn stigmas by near-infrared spectroscopy and chemometrics

Abstract

Counterfeiting and adulteration have seriously affects the products quality. Saffron is the world’s most expensive medicinal plant, an excellent dye, and a high-grade spice. To reduce costs, it is often adulterated with dyed stamens of Nelumbo nucifera Gaertn. (lotus stamens) and stigmas of Zea mays L. (corn stigmas), which have a similar appearance to saffron. Therefore, the aim of this study was to identify and quantify these two adulterants in saffron using near-infrared (NIR) spectroscopy. A partial least squares discriminant analysis (PLS-DA) model was established to determine the authenticity of the saffron. A partial least squares (PLS) regression model was used to predict the adulteration level. The synergistic interval PLS (SI-PLS), competitive adaptive reweighted sampling (CARS), and Monte Carlo uninformative variable elimination variable (MC-UVE) selection methods were compared for correcting the regression models. For saffron adulterated with lotus stamens, the SI-PLS model effect was better than those of the other models. In the quantitative analysis of saffron adulterated with corn stigmas, the CARS-PLS model gave the best stability and predictability. The results showed that the variable selection methods improved the accuracy of the model. The NIR spectroscopy combined with chemometrics could effectively and rapidly identify and quantify adulteration of saffron with lotus stamens and corn stigmas without damaging the samples.