• Journal of Aquaculture
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• v.21 no.4
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• pp.317-324
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• 2008

This study estimated the genetic parameters and breeding values for the growth-related traits of the 1st generation produced in 2005. The heritability of body weight, total length, body height, body shape and condition factor of 180 days old olive flounders Paralichthys olivaceus, the 1st generation of selection, was estimated as 0.564, 0.590, 0.588, 0.306 and 0.332, respectively. And reproductivity of genetic evaluation for crossing superior flounders and inferior ones was tested using the subsequent generation produced in 2006 based on the breeding values of 1st generation. In the least-squares means of body weight and total length for each group of crossing, the values of crossing group between superior flounders ($S{\times}S$) showed $145.6{\pm}1.8\;g$ and $22.4{\pm}0.1\;cm$, respectively. The values of crossing group between superior and inferior flounders ($S{\times}I$) showed $133.2{\pm}2.5\;g$ and $22.1{\pm}0.1\;cm$, respectively. The values of crossing group between inferior flounders ($I{\times}I$) showed $114.0{\pm}2.1\;g$ and $21.08{\pm}0.12\;cm$, respectively. In the results, flounders are determined as appropriate selective breeding fish with the high heritability of flounders in early ages at 180 days old, and the reproductivity of genetic evaluation was also high.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.217-223
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• 2008

Amylose and protein contents are important traits determining the edible quality of rice, especially in East Asian countries. Near-Infrared Reflectance Spectroscopy (NIRS) has become a powerful tool for rapid and nondestructive quantification of natural compounds in agricultural products. To test the practically of using NIRS for estimation of brown rice amylose and protein contents, the spectral reflectances ($400{\sim}2500\;nm$) of total 9,483 accessions of rice germplasm in Rural development Administration (RDA) Genebank ere obtained and compared to chemically determined amylose and protein content. The protein content of tested 119 accessions ranged from 6.5 to 8.0% and 25 accessions exhibited protein contents between 8.5 to 9.5%. In case of amylose content, all tested accessions ranged from 18.1 to 21.7% and the grade from 18.1 to 19.9% includes most number of accessions as 152 and 4 accessions exhibited amylose content between 20.5 to 21.7%. The optimal performance calibration model could be obtained from original spectra of brown rice using MPLS (Modified Partial Least Squares) with the correlation coefficients ($r_2$) for amylose and protein content were 0.865 and 0.786, respectively. The standard errors of calibration (SEC) exhibited good statistic values: 2.078 and 0.442 for amylose and protein contents, respectively. All these results suggest that NIR spectroscopy may serve as reputable and rapid method for quantification of brown rice protein and amylose contents in large numbers of rice germplasm.

• Journal of Animal Science and Technology
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• v.45 no.6
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• pp.923-932
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• 2003

This study was carried out to estimate the effects of breed and environment such as sex, test station, test year, test season, parity, initial and final weight on average daily gain, age at 90kg, backfat thickness, feed efficiency, lean percent and selection index on the basis of the performance data collected from 25,790 pigs of Duroc, Yorkshire and Landrace breeds which were performance-tested at the Korea Swine Testing Station from 1991 to 2002. The results obtained in the study are summarized as follows; 1. The means of the major economic traits were estimated as 959.95${\pm}$0.699g for average daily gain, 138.36${\pm}$0.072days for age at 90kg, 1.41${\pm}$0.001cm for backfat thickness, 2.33${\pm}$0.001 for feed efficiency, 56.71${\pm}$0.018% for lean percent and 221.65${\pm}$0.113 for selection index. 2. The effect of breed was statistically significant for all studied traits. Briefly, Duroc showed the best performance for the average daily gain and age at 90kg. Landrace had the best performances for the backfat thickness and lean meat percent. In feed efficiency and selection index, Yorkshire had a better score than other breeds. 3. The least-squares means of female and male for the traits studied were 923.05${\pm}$1.289g and 974.53${\pm}$0.856g for average daily gain, 139.74${\pm}$0.145days and 137.21${\pm}$0.097days for age at 90kg, 1.49${\pm}$0.002cm and 1.39${\pm}$0.002cm for backfat thickness, 2.43${\pm}$0.002 and 2.28${\pm}$0.002 for feed efficiency, 56.43${\pm}$0.034% and 56.81${\pm}$0.023% for lean percent and 211.37${\pm}$0.194 and 224.61${\pm}$0.129 for selection index. Therefore, males were superior to females for all traits examined. 4. The effect of test station was statistically significant for all traits except for selection index. Performances for age at 90kg, backfat thickness, feed efficiency and lean meat percent collected from Test station 2 were higher than those from Test station 1. However, Test station 1 showed better average daily gain. 5. The initial weight and final weight included as a covariate in this study had a significant influence on average daily gain, age at 90kg, backfat thickness, feed efficiency and selection index. From the absolute values of the estimated regression coefficients, it was inferred that the final weight had greater effect for the investigated traits than the initial weight.