• Korean Journal of Fisheries and Aquatic Sciences
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• v.15 no.2
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• pp.123-136
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• 1982

We investigated the changes in protein and free amino acid compositions of the muscles, and amino acid composition of the muscle proteins during postmortem storage of dorsal white and lateral dark muscles of Yellowtail, Seriola quinqueradita, which were kept at $2^{\circ}C$. We present an extensive discussion on the relationship between the changes of freshness and those of protein compositions in the white and the dark muscle of the red-fleshed fish by analyzing polyacrylamide gel electrophoretograms of $NaDodSO_4-solubilized$ sarcoplasmic and myofibrillar proteins extracted from the both muscles. By assessing K-value, total volatile basic nitrogen and pH value as a criterion of freshness, we found that the dark muscle undergoes a more rapid decrease in its freshness compared to that of the white muscle. The contents of the sarcoplasmic and the myofibrillar protein were decreased with postmortem aging of the muscles while those of the residual intracellular protein were increased, and these changes were somewhat faster in the dark muscle than in the white muscle. From the analysis of the electrophoretograms and their densitograms, we found that the sarcoplasmic proteins of the white and the dark muscle were respectively composed of 16 and 12 components. The sarcoplasmic protein of the white muscle lapsed for 10 days showed an increase of 18,000 and 41,000 dalton components, and a gradual decrease of 23,000 and 23,500 dalton components, whereas the sarcoplasmic protein of the dark muscle lapsed for 9 days showed a decrease of 49,000 dalton component, an appearence of a newly formed component of 47,000 dalton, and a disappearance of 26,000 dalton component. The electrophoretograms of the myofibrillar proteins shelved that the white and the dark muscle were composed of 17 and 16 components, respectively. Depending on the lapsed time of postmortem under the controlled condition, the myofibrillar proteins of the white muscle showed an increase of 40,000 dalton component, a gradual decrease of 37,500 dalton component, an appearance of a newly forming component of 32,000 dalton and a disappearance of 26,000 dalton component. On the other hand, the myofibrillar proteins of the dark muscle showed an increase of 58,000 and 64,000 dalton bands, a disappearance of light chain-2 protein and an appearance of a newly forming protein of 32,000 dalton. These changes on the electrophoretic patterns in the dark muscle were more rapid than those in the white muscle. In almost all of the cases, we observed that the changes in the sarcoplasmic protein were faster than those in the myofibrillar protein. The analysis of amino acid of the both muscle proteins showed that the white muscle was rich in glutamic acid, aspartic acid, leucine, arginine, lysine, etc. but was poor in proline and tryptophan. No significant difference was found in the amino acid composition of protein of both the white and the dark muscles. The sample of white muscle lapsed for 10 days shows a remarkable decrease in glutamic and aspartic acids, while that of the dark muscle lapsed for 9 days shows an appreciable decrease in alanine, glycine and arginine. The free amino acid compositions of the white and the dark muscles are respectively characterized with $63\%$ of histidine and $67\%$ of taurine with respect to the total free amino acids of the yellowtail at-death, respectively. The white muscle lapsed for 10 days showed an increase of histidine, valine and taurine, and a slight decrease of alanine, leucine and glycine. The dark muscle lapsed for 9 days shelved an increase of taurine, phenylalanine and glycine, and a decrease of histidine, alanine and serine.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.2
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• pp.183-193
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• 1995

Assuming that fishing nets are porous structures to suck water into their mouth and then filtrate water out of them, the flow resistance N of nets with wall area S under the velicity v was taken by $R=kSv^2$, and the coefficient k was derived as $$k=c\;Re^{-m}(\frac{S_n}{S_m})n(\frac{S_n}{S})$$ where $R_e$ is the Reynolds' number, $S_m$ the area of net mouth, $S_n$ the total area of net projected to the plane perpendicular to the water flow. Then, the propriety of the above equation and the values of c, m and n were investigated by the experimental results on plane nettings carried out hitherto. The value of c and m were fixed respectively by $240(kg\cdot sec^2/m^4)$ and 0.1 when the representative size on $R_e$ was taken by the ratio k of the volume of bars to the area of meshes, i. e., $$\lambda={\frac{\pi\;d^2}{21\;sin\;2\varphi}$$ where d is the diameter of bars, 21 the mesh size, and 2n the angle between two adjacent bars. The value of n was larger than 1.0 as 1.2 because the wakes occurring at the knots and bars increased the resistance by obstructing the filtration of water through the meshes. In case in which the influence of $R_e$ was negligible, the value of $cR_e\;^{-m}$ became a constant distinguished by the regions of the attack angle $ \theta$ of nettings to the water flow, i. e., 100$(kg\cdot sec^2/m^4)\;in\;45^{\circ}<\theta \leq90^{\circ}\;and\;100(S_m/S)^{0.6}\;(kg\cdot sec^2/m^4)\;in\;0^{\circ}<\theta \leq45^{\circ}$. Thus, the coefficient $k(kg\cdot sec^2/m^4)$ of plane nettings could be obtained by utilizing the above values with $S_m\;and\;S_n$ given respectively by $$S_m=S\;sin\theta$$ and $$S_n=\frac{d}{I}\;\cdot\;\frac{\sqrt{1-cos^2\varphi cos^2\theta}} {sin\varphi\;cos\varphi} \cdot S$$ But, on the occasion of $\theta=0^{\circ}$ k was decided by the roughness of netting surface and so expressed as $$k=9(\frac{d}{I\;cos\varphi})^{0.8}$$ In these results, however, the values of c and m were regarded to be not sufficiently exact because they were obtained from insufficient data and the actual nets had no use for k at $\theta=0^{\circ}$. Therefore, the exact expression of $k(kg\cdotsec^2/m^4)$, for actual nets could De made in the case of no influence of $R_e$ as follows; $$k=100(\frac{S_n}{S_m})^{1.2}\;(\frac{S_m}{S})\;.\;for\;45^{\circ}<\theta \leq90^{\circ}$$, $$k=100(\frac{S_n}{S_m})^{1.2}\;(\frac{S_m}{S})^{1.6}\;.\;for\;0^{\circ}<\theta \leq45^{\circ}$$

• Magazine of the Korean Society of Agricultural Engineers
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• v.13 no.1
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• pp.2191-2205
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• 1971

In this research, Nong-rim No. 6 was adopted as a test variety of rice. Rice seedlings were transplanted on June 14, 1970. Roots were settled into soil on June 20 and a total number of days irrigated of $21cm{\times}21cm$ and an area of $9.9m^2$ for a test plot were accepted, planting 70 stumps of rice in a test plot. The soil in test plots are classified by soil test as oam, and its chemical contents are as shown in Table 3. Irrigation water was secured by pumping from the Sudun stream that originates at the Suho reservoir. Accordingly, the qualities of irrigation. water are considered to be the same as those of water stored in the Suho reservoir. There were 54 days of intermittent rainfalls in total during the whole 110-day period of irrigation. As a result, it is likely that the growth of rice plants was influenced by rainfall at a comparatively great degree. In order to measure the amounts of water consumption, infiltrometers, measuring devices for the decreases of water depths and lycimeters were provided. As a result of measurements, an average daily rate of infiltration was observed to be 14mm/day. It is expected from this research that the effect of increased yield will be secured by supplying optimum amounts of water for irrigation on proper times, and that the amounts of water consumption for irrigation can be saved by applying suitable irrigation methods. The test results obtained are summarized as follows: 1. Yields produced in the test plots of continuous irrigation are lower than those in the test plots of rotational irrigation, i.e., yields produced at the test plots irrigatied once in a period of 8 days are higher by 27% in average than those produced at test plots of continuous irrigation. 2. The amounts of irrigation water for test plots, which have a clay layer of 9cm in thickness and vynil diaphragm without holes, are saved by about 52% in comparison with ordinary test plots. 3. Ears are sprouted 5 days earlier at continuous irrigation plots as compared with other test plots. 4. It seems that there are growing stages of rice plants such as those of forming and sprouting of ears, in which the amounts of irrigation water are consumed more in comparison with the other stages. Therefore, it may be possible to increase of decrease the amount of irrigation water, according to the growing stage of rice plant, so as to save irrigation water.

• Asia pacific journal of information systems
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• v.23 no.3
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

• Journal of Distribution Research
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• v.16 no.2
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• pp.1-24
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• 2011

1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in