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http://dx.doi.org/10.15429/jkomor.2018.18.2.83

Optimization of Mixing Ratio of Mulberry Leaf, Mulberry Fruit, and Silkworm for Amelioration of Metabolic Syndrome  

Kim, Min-Ju (Graduate School of Alternative Medicine, Kyonggi University)
Kim, Hyun-Sook (Department of Alternative Medicine, Graduate School of Kyonggi University)
Kim, Ae-Jung (Graduate School of Alternative Medicine, Kyonggi University)
Publication Information
Journal of Korean Medicine for Obesity Research / v.18, no.2, 2018 , pp. 83-95 More about this Journal
Abstract
Objectives: The aim of this study was optimized mixing ratio of mulberry leaf, mulberry fruit, and silkworm for amelioration of the metabolic syndrome by using response surface method (RSM). Methods: Antioxidant, antidiabetic and antihypertensive activities of fifteen mixed powder of mulberry leaf, mulberry fruit, and silkworm by RSM were measured as indicators of metabolic syndrome. Results: The optimal mixing ratio of mulberry leaves, mulberry fruits, and silkworm with the greatest antioxidant, antidiabetic and antihypertensive activities was as follows: 2.5890 of mulberry leaf (A), 0.1222 of mulberry fruit (B), 2.9999 of silkworm (C). At this time, it was predicted that the total polyphenol content was estimated to be 185.51 tannic acid equivalent mg/g, 1, 1-diphenyl-2-picrylhy drazyl radical scavenging activity 84.77%, 1-deoxynojirimycin content 415.66 mg/100 g, ${\alpha}-glucosidase$ inhibitory activity 64.31%, ${\gamma}-aminobutyric$ acid content 267.77 mg/100 g, potassium content 1,899.11 mg/100 g, and angiotensin-converting-enzyme inhibitory activity was estimated to be 73.78%. Conclusions: It was concluded that the significant effect of the mulberry leaf, mulberry fruit, and silkworm on the metabolic syndrome-related biological activity indices (antioxidant activity, antidiabetic activity and antihypertensive activity) was as follows: 2.5890 of mulberry leaf (A), 0.1222 of mulberry fruit (B), 2.9999 of silkworm (C).
Keywords
Mulberry leaf; Mulberry fruit; Silkworm; Metabolic syndrome; Optimization; Response surface methodology (RSM);
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