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Leaf of Adhatoda vasica (Vasaka) is an important drug of Ayurveda, prescribed as an expectorant. Quinazoline alkaloids present in the leaves are established as active principles. In Ayurveda, its leaf juice (Vasa swarasa) is incorporated in many formulations. Classical method for extracting the juice (swarasa) from the leaf is an elaborate process, which involves subjecting a bolus of crushed fresh leaf to heat followed by squeezing out the juice. Commercially, to prepare the juice of Vasaka, manufacturers have been adopting different methods other than the traditional method. In an effort to evaluate these modified processes phytochemically to identify the process which gives juice of the quality that is obtained by traditional method, in terms of its alkaloid content, we prepared the leaf juice by traditional Ayurvedic method, its modification by steaming of leaf to simulate the traditional method and other methods adopted by some manufacturers. These juice samples were evaluated for the total alkaloid content by spectrophotometric method and vasicine content by thin layer chromatography densitometric method using high performance thin layer chromatography. The high performance thin layer chromatography method was validated for precision, repeatability and accuracy. The total alkaloid content varied from 0.3 mg/ml to 5.93 mg/ml and that of vasicine content varied from 0.2 mg/ml to 5.64 mg/ml in the juice samples prepared by different methods. The present study revealed that steaming of fresh leaves under 15 lb pressure yielded same quantity of juice as the traditional bolus method (25 ml/100 g leaf) and its total alkaloid content and vasicine content (4.05±0.12 and 3.46±0.06 mg/ml, respectively) were very high when compared to the other methods, though the traditional method was found to give the best quality juice with highest amount of total alkaloids (5.93±0.55 mg/ml) and vasicine (5.64±0.10 mg/ml) content.

We applaud Ram Frost for highlighting the need for multicultural perspectives while developing universal models of visual word recognition. We second Frost's proposal that factors like lexical morphology should be incorporated besides purely orthographic features in modeling word recognition. In support, we provide fresh evidence from Hindi (written in Devanagari), an example of hitherto under-represented alphasyllabic orthographies, in which flexible encoding of aksara (character) position is constrained by the morphological structure of words.

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