• Journal of Animal Science and Technology
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• v.66 no.4
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• pp.682-701
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• 2024

This study estimated the heritabilities (h²) and genetic and phenotypic correlations between reproductive traits, including calving interval (CI), age at first calving (AFC), gestation length (GL), number of artificial inseminations per conception (NAIPC), and carcass traits, including carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) in Korean Hanwoo cows. In addition, the accuracy of genomic predictions of breeding values was evaluated by applying the genomic best linear unbiased prediction (GBLUP) and the weighted GBLUP (WGBLUP) method. The phenotypic data for reproductive and carcass traits were collected from 1,544 Hanwoo cows, and all animals were genotyped using Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The genetic parameters were estimated using a multi-trait animal model using the MTG2 program. The estimated h² for CI, AFC, GL, NAIPC, CWT, EMA, BF, and MS were 0.10, 0.13, 0.17, 0.11, 0.37, 0.35, 0.27, and 0.45, respectively, according to the GBLUP model. The GBLUP accuracy estimates ranged from 0.51 to 0.74, while the WGBLUP accuracy estimates for the traits under study ranged from 0.51 to 0.79. Strong and favorable genetic correlations were observed between GL and NAIPC (0.61), CWT and EMA (0.60), NAIPC and CWT (0.49), AFC and CWT (0.48), CI and GL (0.36), BF and MS (0.35), NAIPC and EMA (0.35), CI and BF (0.30), EMA and MS (0.28), CI and AFC (0.26), AFC and EMA (0.24), and AFC and BF (0.21). The present study identified low to moderate positive genetic correlations between reproductive and CWT traits, suggesting that a heavier body weight may lead to a longer CI, AFC, GL, and NAIPC. The moderately positive genetic correlation between CWT and AFC, and NAIPC, with a phenotypic correlation of nearly zero, suggesting that the genotype-environment interactions are more likely to be responsible for the phenotypic manifestation of these traits. As a result, the inclusion of these traits by breeders as selection criteria may present a good opportunity for developing a selection index to increase the response to the selection and identification of candidate animals, which can result in significantly increased profitability of production systems.

• Journal of Life Science
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• v.20 no.6
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• pp.825-830
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• 2010

Two diallelic markers at candidate gene loci, the prolactin receptor 3 (PRLR3) gene and the retinol-binding protein 4 (RBP4) gene were evaluated for their association with growth and litter size traits in Berkshire. Genetic evaluation was conducted for 5,919 pigs with pedigree information, which included 3,480 growth performance records and 775 litter size records of 224 sows. From the same herd, genotyping was carried out on 144 and 156 animals for PRLR3 and RBP4, respectively. After assigning a genotype to subjects in which both parents had a homozygous genotype, numbers of genotyped animals increased to 474 and 338, for the PRLR3 gene and RBP4 gene, respectively. The genotype effects of two markers were estimated with breeding values of the genotyped animals. The additive effects of total number of piglets born and number of piglets born alive in the PRLR3 locus were -0.28 and -0.13, respectively. The dominance effect of the RBP4 locus on average daily gain was -10.58 g. However, the polymorphism of the RBP4 locus in total number of piglets born and number of piglets born alive has shown -0.34 and -0.33 of the additive genetic effects. In view of the results, MAS (marker-assisted selection) favoring B alleles of RBP4 and PRLR3 loci could potentially accelerate the rate of the genetic improvement in the litter size traits.

• Journal of Embryo Transfer
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• v.18 no.3
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• pp.249-255
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• 2003

These studies were performed to improve the reproductive efficiency of gilts and we investigated the effects of puberty periods, first mating time and backfat thickness and will adapt to these results for early selection of excellent gilts. The main results were as follows; 1. First heats on birth season were showed 194.14 day, 163.25 day, 160.25 day and 157.92 day at birth of spring, summer, autumn and winter, respectively and birth of spring was significantly latest among other seasons (p<0.01). 2. First service on birth season were revealed 222.05 day in spring, 193.00 day in summer, 199.20 day in autumn and 190.11 day in winter. birth of spring was significantly latest among others (p<0.01). 3. First heat period of cadidated gilt had 13∼16 mm backfat thickness was 180.32 day, 171.24 day in 17∼20 mm and 162.20 day in 21∼23 mm and was showed delay in thin backfat gilts. There was no differences among backfat thickness. 4. First service of cadidate gilt had 13∼16mm backfat thickness was 211.12 day, 202.43 day in 17∼20 mm and 195.43 day in 21∼23 mm and was showed delay in thin backfat gilts. There was no differences among backfat thickness. 5. The litter size were 9.64 in gilts under 160 day of first heat, 10.14 in 161∼180 day, 9.56 in 181∼200 day and 9.13 in over 201 day. There showed the largest litter size in 161∼180 day of first heat but was no differences. 6. The litter size in gilts under 180 day of first service was 9.13, 9.75 in 181∼200 day, 10.13 in 201∼220 day and 9.45 in over 221 day. There showed the largest litter size in 201∼220 day of first service but was no differences. 7. The litter size of gilt had 13∼16 mm backfat thickness on first service was 9.33, 9.81 in 17∼20 mm and 10.17 in 21∼23 mm and was showed delay in thin backfat gilts. There was no differences among backfat thickness.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.3-36
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• 2015

As of end of 2014, the population engaging in aviation activities for leisure has reached approximately 13 million, where approximately 356 cases involve a general aircraft, 200 cases involve light aircraft, and 636 cases involve an ULM. The industry for leisure has become a very promising industry in line with rapidly rising living standards which are expected to further increase in the future. The demand for such services is expected to increase over time. The purpose of this paper is to review the development and site selection of airfields in anticipation of these developments in the industry. While the government also has experience in the review of airfield location and candidate sites, it is not the government that carries out the actual construction. As such, the feasibility of the site needs to be verified in terms of actual construction. This study identified factors for Site Selection of factors through a review of related documents and existing research reports. A questionnaire was also used to collect the views of experts in the field, which was then analyzed. The Research model was confirmed in the layered form for an AHP analysis. The factors for Site Selection were identified as the technical / operational factors and economic / political elements for a two-stage configuration. The third step consisted of technical and operational elements. The final step is was constructed a total of 11 elements (weather, surface conditions, obstacle limitation surface, airspace conditions, operating procedures, noise problems, environmental issues, availability of facilities, construction and investment costs, contribution to the local economy, accessibility, demand / the proximity of demand). The surveys are conducted for more than 10 General and light aircraft pilots, professionals, and instructor. The analysis results showed a higher level in the technical / operating elements (73.2%) in the first step, while the next step sawa higher level of the operational elements (30.9%) than the other. The factors for Site Selection were any particular elements did not appear high, the weather conditions (17.5%), noise problems (19.8%), the proximity of demand (6%), accessibility (5.7%), environmental issues (11.1%), availability of facilities (8%), airspace conditions (7.9%), obstacle limitation surface (12%), construction and investment costs (4.2%) and to operating procedures (4.9%), contribution to the local economy (3.8%).

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.41-41
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• 2015

BSA-seq technologies, combined Bulked Segregant Analysis (BSA) and Next-Generation Sequencing (NGS), are making it faster and more efficient to establish the association of agronomic traits with molecular markers or candidate genes, which is the requirement for marker-assisted selection in molecular breeding. Clubroot disease, caused by Plasmodiophora brassicae, is a serious threat to Brassica crops. Even we have breed new clubroot resistant varieties of Chinese cabbage (B. rapa ssp. pekinesis), the underlying genetic mechanism is unclear. In this study, an $F_2$ population of 340 plants were inoculated with P. brassicae from Xinye (Pathotype 2 on the differentials of Williams). Resistance phenotype segregation ratio for the populations fit a 3:1 (R:S) segregation model, consistent with a single dominant gene model. Super-BSA, using re-sequencing the parents, extremely R and S DNA pools with each 50 plants, revealed 3 potential candidate regions on the chromosome A03, with the most significant region falling between 24.30 Mb and 24.75 Mb. A linkage map with 31 markers in this region was constructed with several closely linked markers identified. A Major QTL for clubroot resistance, CRq, which was identified with the peak LOD score at 169.3, explaining 89.9% of the phenotypic variation. And we developed a new co-segregated InDel marker BrQ-2. Joint BSA-seq and traditional QTL analysis delimited CRq to an 250 kb genomic region, where four TIR-NBS-LRR genes (Bra019409, Bra019410, Bra019412 and Bra019413) clustered. The CR gene CRq and closely linked markers will be highly useful for breeding new resistant Chinese cabbage cultivars.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.12
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• pp.1649-1659
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• 2012

Crosses between Korean and Landrace pigs have revealed a large quantitative trait loci (QTL) region for fat deposition in a region (89 cM) of porcine chromosome 4 (SSC4). To more finely map this QTL region and identify candidate genes for this trait, comparative mapping of pig and human chromosomes was performed in the present study. A region in the human genome that corresponds to the porcine QTL region was identified in HSA1q21. Furthermore, the LMNA gene, which is tightly associated with fat augmentation in humans, was localized to this region. Radiation hybrid (RH) mapping using a Sus scrofa RH panel localized LMNA to a region of 90.3 cM in the porcine genome, distinct from microsatellite marker S0214 (87.3 cM). Two-point analysis showed that LMNA was linked to S0214, SW1996, and S0073 on SSC4 with logarithm (base 10) of odds scores of 20.98, 17.78, and 16.73, respectively. To clone the porcine LMNA gene and to delineate the genomic structure and sequences, including the 3'untranslated region (UTR), rapid amplification of cDNA ends was performed. The coding sequence of porcine LMNA consisted of 1,719 bp, flanked by a 5'UTR and a 3'UTR. Two synonymous single nucleotide polymorphisms (SNPs) were identified in exons 3 and 7. Association tests showed that the SNP located in exon 3 (A193A) was significantly associated with weight at 30 wks (p<0.01) and crude fat content (p<0.05). This association suggests that SNPs located in LMNA could be used for marker-assisted selection in pigs.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.5
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• pp.359-366
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• 2014

For an efficient and reasonable management scheme for protecting the soil environment, a soil ecological risk assessment (ERA) method should be developed prior to utilization, based on the contemporary uses and situations of each country. The Korean environmental policy focusing on soil protection is currently accelerating the development of the soil ecological risk assessment method. The soil ERA requires toxicological data on various trophic levels in the soil environment, and ultimately uses PNEC (Predicted No Effect Concentration), which is derived from collected toxicological data. Therefore, test species that are used to generate toxicity data are essential for conducting reliable ERA. This study aimed to select domestic test species for potential use in a reliable Korean ERA. Copper (Cu) and Nickel (Ni) were identified as target substances, with toxicity data (Cu, Ni) and standard test methods being collected to determine candidate species. The candidate species were first classified by soil trophic level, and then sorted into final domestic species. Forty out of 166 domestic species were determined as potential standard test species, whereas 17 out of 120 species were determined as potential Cu and Ni test species. Finally, this study presented potential soil test species based on the characteristics of the domestic soil environment, and established a preliminary step toward developing a reliable Korean soil ERA method.

• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.111-124
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• 2010

This study has intended to develop an evaluation model to select suitable locations of recreation forests in accordance with their types, and to apply the models to the feasibility study of selecting suitable recreation forest locations of candidate sites. To reach this goal, this study employed a Delphi expert survey method and Analytic Hierarchy Process (AHP) for the whole process of model building. And the followings are what this study has found during model building and application process. First, the assessment criteria for classifying recreation forests and selecting suitable locations were initially identified through justification process with two rounds of expert review, after broken down into 2 categories, and then further divided into 6 items and 12 indicators accompanying with hierarchical structure. Second, in the third phase of Delphi expert survey, the relative weights of the assessment criteria were derived by employing AHP. Through overlaying two evaluation categories including resource and usability, 4 types of recreation forest were presented. In the forth phase of the Delphi survey, this study has developed an evaluation model to select suitable locations of recreation forests in accordance with their types using relative weights of the selected indicators through. This study has applied the models to the feasibility study of selecting suitable recreation forest locations of candidate sites, and found that the usability of recreation forest was severely affected by the distance from the capital region, that the closer the locations of natural recreation forests from the capital region, the more advantageous. The developed model can be used to designate recreation forests in accordance with their types.