AIM OF THE STUDY: The role of ethnobotany in drug discovery is huge but there are criticisms over such studies due to their qualitative nature. The present study is aimed at quantitatively abstracting the medicinal plant knowledge of the healers trained in traditional ways, in Mayiladumparai block of Theni District, Tamil Nadu, India.
MATERIALS AND METHODS: The interviews and field observations were carried out in all the 18 village panchayaths from January to June 2010, consisting of 148 field days. The interviews were conducted with 80 traditional healers, after obtaining prior informed consent. Successive free listing was used to interview the informants. The informant consensus factor (F(ic)) was calculated to estimate the use variability of medicinal plants. Fidelity index and Cultural importance index were also calculated to analyze the data.
RESULTS: This study recorded the ethno-medicinal usage of 142 ethno-species belonging to 62 families that were used to prepare 504 formulations. Jaundice had the highest F(ic) value than all the illness categories studied. Phyllanthus spp. was the highly cited medicinal plant to treat jaundice and had high fidelity index value. This was followed by Senna angustifolia and Terminalia chebula as laxatives. The highly cited medicinal plants in each group with high F(ic) value were Pongamia pinnata (antiseptic), Aerva lanata (antidote and snakebite), Blepharis maderaspatensis (cuts and wounds), Abutilon indicum (hemorrhoids), Ruta graveolens (spiritual medicine), Ocimum tenuiflorum (cough), and Solanum trilobatum (pulmonary ailments). Phyllanthus spp., was the most culturally significant species according to this index, followed by Borassus flebellifer.
CONCLUSION: The process of drug discovery has become highly expensive and post-approval and post-marketing withdrawal of drugs is continuing. In such scenario, reverse pharmacology is considered an attractive option. The medicinal plants enumerated in this study with high number of citations and high F(ic) values for illness categories might give some useful leads for further biomedical research.
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