International Journal of Applied Research
Vol. 3, Special Issue 3, Part J (2017)
Morphotaxonomic study and phytochemical analysis by GCMS method of underestimated medicinal Grass: Cynodon dactylon (L.) Pers. (Poaceae)
Dr. Shubhangi Nagorao Ingole
The family Poaceae is one of the largest and most important families in plant kingdom. No other group of plants is more essential to the nutrition, well-being or even existence of man. Taxonomically grasses are very difficult group of plants and classified and identified on basis of morphological characters. They have great economical and ecological values with multiple uses including medicinal, but still are underestimated and overlooked from studies because of their difficult floral structures which are not showy.In present attempt, morphotaxonomic study and phytochemical analysis by GCMS method of Cynodon dactylon (L.) Pers. which is mentioned for its multiple medicinal uses in ancient literature to determine the phytochemical constituents to ascertain the rationale for its use in traditional medicine has been undertaken. Morphotaxonomic studies which not only found assisting its classification to respective tribe and its justification but also useful for its proper identification. Through GCMS analyzed results, 3 compounds were identified and reported as phthalic acid di ester, di-isocotyl phthalate, Bis (2-ethyl hexyl) phthalate which are known to possess antimicrobial and antifouling activity. GCMS analysis and the biological activity of each compound were discussed in present attempt. This was found helpful in proving medicinal importance of this grass also revealing the wisdom of our ancestors in ancient times. Present study suggests that grasses should be given due importance for identification and further studies along with their conservation
How to cite this article:
Dr. Shubhangi Nagorao Ingole. Morphotaxonomic study and phytochemical analysis by GCMS method of underestimated medicinal Grass: Cynodon dactylon (L.) Pers. (Poaceae). International Journal of Applied Research. 2017; 3(3S): 320-323.