期刊
JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION
卷 13, 期 1, 页码 697-706出版社
SPRINGER
DOI: 10.1007/s11694-018-9982-2
关键词
Momordica balsamina Linn; Response surface methodology; Artificial neural networking; SEM; GC/MS
The present research work appraises the effect of different enzyme formulations (zympex-014, kemzyme dry-plus and natuzyme) under optimized set of experimental conditions such as time (30-90min), temperature (25-75 degrees C), pH (6-9) and solid/enzyme ratio (0.5-6.5%) following central composite design (CCD) on extraction of phenolic bioactives from Momordica balsamina fruit (balsam apple). Out of enzyme complexes employed in this study, zympex-014 offered maximum extraction yield (42.6g/100g) at optimized conditions including time (60min), temperature (50 degrees C), pH (7.5) and enzyme concentration (6.5%) using CCD. Artificial neural network (ANN) was trained computationally based on the experimental data to predict the optimum BAF extract yield for zympex-014. Significant morphological changes in the cell wall of balsam apple fruit (BAF) were elucidated by scanning electron microscopy (SEM) before (control) and after enzymatic treatment. Relatively a superior antioxidant activity was exhibited by extracts from enzyme-treated BAF relative to the control. GC/MS profiling authenticated the presence of ferulic acid (2.30), quercitin (1.48), benzoic acid (0.41) and gallic acid (0.26g/mL) as major potent phenolic bioactives in zympex-014 -assisted BAF extract. While p-coumaric (0.05), m-coumaric acid (0.03) and sinapic acid (0.01g/mL) were found in lesser amount. The results of the present study indicated that the devised RSM-based optimized enzyme-assisted extraction, using zympex-014 among others, had significant positive effect on liberation of bound phenolics and thereby enhancing antioxidant potential of BAF extracts.
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