Resolving identification issues of Saraca asoca from its adulterant and commercial samples using phytochemical markers
Satisha Hegde1, Harsha Vasudev Hegde2, Sunil Satyappa Jalalpure3, Malleswara Rao Peram4, Sandeep Ramachandra Pai5, Subarna Roy2
1 Regional Medical Research Centre, Indian Council of Medical Research; KLE Academy of Higher Education and Research (KLE University), Belagavi, Karnataka, India
2 Regional Medical Research Centre, Indian Council of Medical Research, Belagavi, Karnataka, India
3 Dr. Prabhakar Kore Basic Science Research Centre, KLE University; Department of Pharmacognosy, KLE University's College of Pharmacy, Belagavi, Karnataka, India
4 Dr. Prabhakar Kore Basic Science Research Centre, KLE University, Belagavi, Karnataka, India
5 Regional Medical Research Centre, Indian Council of Medical Research; Amity Institute of Biotechnology, Amity University, Mumbai, Maharashtra, India
Sandeep Ramachandra Pai
Amity Institute of Biotechnology, Amity University, Mumbai - 410 206, Maharashtra
Regional Medical Research Centre, Indian Council of Medical Research, Belagavi - 590 010, Karnataka
Source of Support: None, Conflict of Interest: None
Saraca asoca (Roxb.) De Wilde (Ashoka) is a highly valued endangered medicinal tree species from Western Ghats of India. Besides treating cardiac and circulatory problems, S. asoca provides immense relief in gynecological disorders. Higher price and demand, in contrast to the smaller population size of the plant, have motivated adulteration with other plants such as Polyalthia longifolia (Sonnerat) Thwaites. The fundamental concerns in quality control of S. asoca arise due to its part of medicinal value (Bark) and the chemical composition. Phytochemical fingerprinting with proper selection of analytical markers is a promising method in addressing quality control issues. In the present study, high-performance liquid chromatography of phenolic compounds (gallic acid, catechin, and epicatechin) coupled to multivariate analysis was used. Five samples each of S. asoca, P. longifolia from two localities alongside five commercial market samples showed evidence of adulteration. Subsequently, multivariate hierarchical cluster analysis and principal component analysis was established to discriminate the adulterants of S. asoca. The proposed method ascertains identification of S. asoca from its putative adulterant P. longifolia and commercial market samples. The data generated may also serve as baseline data to form a quality standard for pharmacopoeias.
Abbreviations used: HPLC: High Performance Liquid Chromatography; RP-HPLC: Reverse Phase High Performance Liquid Chromatography; CAT: Catechin; EPI: Epicatechin; GA: Gallic acid; PCA: Principal Component Analysis.