Phytochemistry, traditional uses and cancer chemopreventive activity of Amla (Phyllanthus emblica): The Sustainer.

Ayurveda, which is the oldest health system in the world, appreciates and uses amla to treat a host of diseases and promote positive health. Amla [Emblica officinalis, or emblic myrobalan], is called amalaki in Sanskrit. It is extensively used as a rejuvenator in ayurveda. It is also used widely in combination with other two [chebulic and belleric] myrobalans [fruit-bearing plant species] as triphala. Amla is indeed, the key ingredient in the popular ayurvedic recipe, Chyavanaprasha. More than anything, it may be called as "King of Rasayana" [rejuvenation], owing to its multiple health benefits. Phyllanthus emblica or Indian gooseberry (Amla) possesses a vastethnomedical history and represents a phytochemical reservoir of heuristic medicinal value. It is one of the oldest oriental medicines mentioned in Ayurveda as potential remedy for various ailments. The fruit is rich in quercetin, phyllaemblic compounds, gallic acid, tannins, flavonoids, pectin and vitamin C and also contains various polyphenolic compounds. A wide range of phytochemical components including terpenoids, alkaloids, flavonoids, and tannins have been shown to posses’ useful biological activities. Many pharmacological studies have demonstrated the ability of the fruit shows antioxidant, anticarcinogenic, antitumour, antigenotoxic, antiinflammatory activities, supporting its traditional uses. In this review, we have focused our interest on phytochemistry, traditional uses, cancer chemopreventive activity of Phyllanthus emblica both in vivo and in vitro. In view of its reported pharmacological properties and relative safety, P. emblica could be a source of therapeutically useful products.

Estimation of rainfall-runoff using curve number: a GIS based development of Sathanur reservoir catchment.

A GIS based algorithm has been developed to estimate the rainfall-runoff relationship of Sathanur reservoir catchment based on Soil Conservation Service (SCS) model. The landuse and soil maps were prepared in Arc/Info 9.0 and an arc macro language (AML) programme was developed to assign curve number based on landuse and soil classification including hydrological condition of the area. The algorithm was executed successfully by rainfall data for computation of runoff depth in all the sub watersheds. The study is important for a watershed, which does not have runoff records and can be used for planning of various water conservation measures.