Application of near infrared spectral fingerprinting and pattern recognition techniques for fast identification of Eleutherococcus senticosus

Eleutherococcus senticosus, a member of the Araliaceae family, has attracted the interest of many people due to its therapeutic properties. Consequent trading has impelled the development of analytical procedures for fast identification and counterfeit detection. For that purpose, a near-infrared spectroscopic procedure to obtain a fingerprint of E. senticosus has been developed using raw materials. The spectra were processed by using different pattern recognition procedures. General classification success rates of 84% and 92% were achieved by Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA), respectively. Tests on laboratory-made mixtures showed that it is possible to detect adulterations or counterfeits with about 5% foreign herbal material, depending on their closeness to the Araliaceae family. The sensitivity and specificity of constructed models were above 73%. The results suggest that NIR spectroscopy can be used to authenticate E. senticosus material.