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        검색결과 3

        1.
        2004.06 KCI 등재 구독 인증기관 무료, 개인회원 유료
        This study was conducted to examine contents of total acid and free amino acids in the Demi-glace with added quantity of Omija extracts. Firstly, The level of Total acid content of Demi-glace sauces was 1.08~1.89% and Omija extracts was 2.77~7.24%. The more Omija extracts added, there was the higher total acid contents. Sauces and extracts of 5% Omija was the highest. Secondly, Total free amino acids contents of control was 2518.52mg%, and Omija sauces was 2261.52~2894.14mg%. 2% Omija sauces was the highest among them. Hydroxyproline of total 34 free amino acids was the highest, and Glutamic acid 158.42mg%, Proline 78.90mg% was next in order. Arginine was the highest with 27.40~34.40mg% among 9 essential amino acids contents. Glutamic acid was the highest contents with 123.18~158.42mg%. Compared to control's(0.41mg%), Omija added group was 20.63~27.82mg% and it was the highest increase. While other 15 amino acid was analyzed, Hydroxyproline was the highest contents with 1,737.22~2,205.80mg%. Compared to control group(15.63mg%), proline was 57.01~78.90mg% Omija added group and it was increased with the highest contents. In essential amino acid, flavor enhancing amino acid and other amino acid were increased and the highest contents with 2% added Omija sauce. Thirdly, sensory characteristics of Demi-glace sauces based on overall preference, It was find that 2% added Omija was the best. 2% added was the best for color, flavor, taste, texture, overall acceptability(P〈.001). In terms of Demi-glace sauces' gender preference, male and female people liked 2% added Omija color, flavor, taste, texture, overall acceptability. It was find that there was no significant differences between male and female.
        4,200원
        2.
        1989.06 KCI 등재 구독 인증기관 무료, 개인회원 유료
        The compositions of total and free amino acids in parts of Omija were investigated. The most abundant amino acids in fruits, endocarps, and seeds were arginine (50.80%), lysine (14.37%), glutamic acid (14.22%), respectively. Since the amino acid scores of fruits, endocarps, and seeds were 9.4, 11.9, and 16.7, respectively, the limiting amino acid of each part were S-compound amino acids. In the composition of free amino acids, contents of lysine were highest one such as 51.78, 57.00 and 32.88% in fruits, endocarps and seeds, respectively. The contents of histidine from free amino acids were 23.62% in fruits, 22.37% in endocarps, and 26.41% in seeds.
        3,000원
        3.
        2011.03 KCI 등재 서비스 종료(열람 제한)
        This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration (R2 ) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low(R2 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.