Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques. Further identification was done by using HPLC, IR and MP. Pure Trigonelline was isolated from the seeds of Trigonella-foenum graecum excluding other alkaloid like choline. In this study, a new, fast and convenient method for isolation and purification of Trigonelline from fenugreek seeds has been established. Unlike other methods, this one excludes all the non-alkaloidal components from the fenugreek seeds extract.
الزكاة فريضة من فرائض الإسلام وعبادة من العبادات التي اقرها الشرع الإسلامي هذه الفريضة المالية التعبدية بالإضافة الى دورها المعنوي الذي يهدف الى إرساء قواعد العدالة الاجتماعية والقضاء على مشكلة الفقر في المجتمع الاسلامي وكما ينص عليها الدين الإسلامي فان لها ابعادها ووظائفها الكثيرة التي تخدم اليات العمل الاقتصادي في مجتمع يعمل وفق نظام اقتصادي أسلامي .
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... Show MoreThis article aims to determine the time-dependent heat coefficient together with the temperature solution for a type of semi-linear time-fractional inverse source problem by applying a method based on the finite difference scheme and Tikhonov regularization. An unconditionally stable implicit finite difference scheme is used as a direct (forward) solver. While by the MATLAB routine lsqnonlin from the optimization toolbox, the inverse problem is reformulated as nonlinear least square minimization and solved efficiently. Since the problem is generally incorrect or ill-posed that means any error inclusion in the input data will produce a large error in the output data. Therefore, the Tikhonov regularization technique is applie
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