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Title: Enzyme-assisted Extraction and Characterization of Phenolic Bioactives in Selected Medicinal Plants from Pothohar Region.
Authors: Qadir, Rahman
Keywords: Physical Sciences
Analytical Chemistry
Issue Date: 2019
Publisher: University of Sargodha, Sargodha.
Abstract: Enzyme-assisted extraction as a part of biotechnological means is a potential bioprocess, recently explored for the extraction of plant phenolics offering optimum yield of extractable components. The present research work was mainly aimed to extract and characterize phenolic antioxidants in the leaves/fruits from enzymatically hydrolysed medicinal plants namely Morus alba, Momordica balsamina, Capparis spinosa, Pongamia pinnata and Peganum hermala indigenous to Pothoharic region of Pakistan. Enzyme cocktails such as kemzyme dry-plus, natuzyme and zympex-014 were employed for enzyme-assisted extraction of phenolic bioactives from selected medicinal plants The influence of four parameters such as time (30-90 min), temperature (25-75°C), pH (6-9) and solid/enzyme ratio (0.5-6.5%) was investigated under optimized set of experimental conditions using central composite design (CCD). Artificial neural network (ANN) model was trained computationally to calculate and predict the optimum yield of extractable components. Out of enzyme complexes employed in this study, zympex-014 offered maximum extraction yield (30.00, 28.00, 34.00 and 42.60 g/100g) at optimized conditions for M. alba, P. pinnata, P. hermala and M. balsamina, respectively. However, in case of C. spinosa, maximum extract yield was obtained by kemzyme dry-plus (42.00 g/100g). ANOVA was applied to verify the robustness of models employed. Surface and contour plots demonstrated the relationship between response (extract yield) and independent variables. Overall, it was noted that enzyme concentration had a strong positive effect on extraction yield as compared to other variables. Architecture of ANN model was generated to predict phenolic extract yield from selected medicinal plants. ANN predicted values were found to be quite close to the experimental values which demonstrated the applicability of ANN model. Significant structural changes in the cellular walls of medicinal plants residues were expounded by scanning electron microscopy (SEM) before (control) and after enzymatic treatment. Overall, zympex-014 based extracts from M. alba, P. pinnata, P. hermala and M. balsmaina contained higher quantities of phenolic and flavonoid contents with optimized bioactivities (antimicrobials, thrombolytic, biofilms inhibition and haemolytics). Though, C. spinosa fruit offered optimized TPs, TFs and extents of antioxidant activities were in kemzyme dry-plus assisted extracts. FTIR analysis of the extracts also revealed the presence of various functional groups such as alcohols, xx aromatics and alkane supporting the presence of natural phenolics. RP-HPLC was employed to detect the major quantities of phenolics in selected medicinal plants that were found to be gallic acid (95-164), benzoic acid (11-14), m-coumaric acid (11-19) and cinnamic acid (28-35 µg/g). Phenolic acids and flavonols in the selected medicinal plants were further analysed and authenticated by GC-MS after derivatization into silyl esters. The present results revealed that optimized enzyme-assisted extraction facilitated the recovery of phenolic bioactives from medicinal plant parts. Generally, the plants selected in this research work were explored for their phenolic contents and consumption as daily food ingredient that support the use in bioactivities and thus leading to explore their position in functional food and nutraceuticals industries. Conversely, surveys on the profiling of other nutraceuticals coupled with appraisal of in-vivo bioactivities of these residues is furthermore suggested to establish the potential usages of tested medicinal plants for specific nutra-pharmaceutical applications
Gov't Doc #: 21354
Appears in Collections:PhD Thesis of All Public / Private Sector Universities / DAIs.

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