• Applied Biological Chemistry
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• v.20 no.2
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• pp.188-204
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• 1977

The studies on the saponins of Korean ginseng, Panax ginseng C.A. Meyer, were performed according to the cultivating locations, sampling seasons, plant parts, and growing stages. The changes in saponin content in the course of manufacturing Red ginseng and Ginseng extract were observed. In this paper, a new method for the determination of the total and the individual saponin glucosides was proposed and applied to the samples under study. The method employing Digital Densitorol DMU-33C (Toyo electric Co., Japan) followed the separation of the saponins by means of a preparative thin layer chromatography. The saponin contents and their fractional distribution were summarized as follows: 1. The average concentrations(% plant dry weight) of semi-purified saponins in the roots of Korean ginseng planted in the various locations were 5.0%(Keumsan), 6.0% (Kimpo), and 5.4% (Pocheon), respectively. 2. There were 3.3% saponins in White ginseng(Rhizome) and 12.7% saponins in Ginseng tail (Fibrous root). 3. Regarding the year of growth, the contents of saponins were 90.3mg (2-year-old ginseng), 254.4mg (3-year-old ginseng), 404.2mg (4-year-old ginseng). 999.6mg (5-year-old ginseng), and 1377.1mg (6-year-old ginseng) respectively, and the saponin factions containing panaxatriol as an aglycone increased. 4. Thin layer chromatography revealed that Red ginseng yielded many saponins which Shibata et al. designated as $ginsenoside-Rb_1$ (22.1%), $-Rb_2(15.4%)$, -Rc(12.6%), -Re (15.7%), and $-Rg_1$, (9.3%). 5. 29.9% of crude saponins were isolated from ethanolic extract of Panax ginseng fibrous root and their extraction yield was 94.2% of fibrous root saponin.

• Knowledge Management Research
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• v.22 no.3
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• pp.151-172
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• 2021

The government's implementation of customer-friendly financial policies, such as lowering commission fees for credit card merchants and lowering the maximum interest rate, put the specialized credit finance companies in a crisis of lowering profitability. In this unfavorable situation, the efficiency study of specialized credit finance companies is meaningful. Accordingly, this study measured the efficiency of 34 specialized credit finance companies through Data Envelopment Analysis (DEA) and meta-frontier analysis. For meta-frontier analysis, specialized credit finance companies were divided into two groups (card companies and non-card companies) by industry or three groups (AA0 and above, AA-, and A+ or below) by credit rating. The results of the analysis will provide general insight into the efficiency of specialized credit finance companies. The results of this study are as follows. First, the average meta-efficiency of card companies was analyzed higher than that of non-card companies. Second, 80% of non-card's decision-making units (DMUs) were inefficient by pure technology rather than by scale. Third, decision-making units (DMUs), which account for 62.5% of the credit card company group and 80% of the 'AA-' credit rating group, are in non-economic areas of scale. Fourth, there was no statistically significant difference in meta-efficiency values (TE and PTE) by industry (card companies, non-card companies) and credit rating (AA0 or higher, AA-, A+ or lower). The contribution of this study will provide strategic initiatives for establishing management strategies to improve inefficiency by measuring the efficiency level of companies under an unfriendly business environment for specialized credit finance companies.