• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1741-1754
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• 2020

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and -0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.8
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• pp.1087-1092
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• 2003

As an experimental reference population, crosses between Korean native pig and Landraces were established and information on growth traits was recorded. Animals were genotyped for 24 microsatellite markers covering chromosomes 2, 6, and 7 for partial-genome scan to identify chromosomal regions that have effects on growth traits. quantitative trait loci (QTL) effects were estimated using interval mapping by the regression method under the line cross models with a test for imprinting effects. For test of presence of QTL, chromosome-wide and single position significance thresholds were estimated by permutation test and normal significance threshold for the imprinting test were derived. For tests against the Mendelian model, additive and dominance coefficients were permuted within individuals. Thresholds (5% chromosome-wide) against the no-QTL model for the analyzed traits ranged from 4.57 to 4.99 for the Mendelian model and from 4.14 to 4.67 for the imprinting model, respectively. Partial-genome scan revealed significant evidence for 4 QTL affecting growth traits, and 2 out of the 4 QTLs were imprinted. This study demonstrated that testing for imprinting should become a standard procedure to unravel the genetic control of multi-factorial traits. The models and tests developed in this study allowed the detection and evaluation of imprinted QTL.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• Food Science and Preservation
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• v.22 no.5
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• pp.683-689
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• 2015

Response surface methodology (RSM) is a statistical procedure frequently used for optimization studies. The purpose of this study was to determine the optimal spray drying condition for manufacturing Sikhye powder using RSM. Independent variables included the additive contents of maltodextrin (MD), inlet temperature, and velocity of sample feed velocity. The dependent variables were water uptake (g), solubility (%) and particle size (${\mu}m$). Regression models describing the changes of water uptake (g), solubility (%) and particle size (${\mu}m$) with respect to the independent variables were statistically significant with coefficients of determination, $R^2$, greater than 0.9. The results indicated that the inlet temperature of the spray dryer was the most important independent variable that affected the water uptake (g), while the additive content of MD and the sample feed velocity had maximum effects on the solubility (%) and particle size (${\mu}m$) of the Sikhye powder, respectively. The optimum final product was expected to have the lowest possible water uptake (g) and particle size (${\mu}m$) but the highest possible solubility (%). In conclusion, the best spray drying conditions were as follows: additive MD content, 22%; inlet temperature, $140^{\circ}C$ ; and spray dryer sample feed velocity, 51 mL/min.

• Korean Journal of Food Science and Technology
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• v.38 no.3
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• pp.337-341
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• 2006

The quality characteristics of a surimi-based product with sea tangle single cell detritus (SCD) were studied in order to utilize SCD from sea tangle as a food additive. Mixture design and regression models were applied to optimize the processing conditions and to investigate the interaction between surimi and the other ingredients. Surimi and SCD decreased hardness and cohesiveness of surimi gels, and then increased them. Water increased hardness and then decreased it, whereas cohesiveness was reversed. Surimi and water increased gumminess and brittleness of surimi gels, but SCD decreased them. SCD increased water retention ability (WRA) and whiteness of surimi gels, whereas water decreased it. Hardness and cohesiveness fitted nonlinear models by ANOVA, but gumminess, brittleness, WRA and whiteness fitted linear models. The response constraint coefficient showed that surimi influenced hardness and whitenessmore than water and SCD, whereas water influenced WRA more than surimi and SCD. Moreover, SCD influenced cohesiveness, gumminess and brittleness more than surimi and water. Hardness and cohesiveness fitted nonlinear models with interaction terms for surimi-SCD and surimi-water, respectively. Optimum mixed ratio values of surimi, water, and SCD were 36.80, 57.07 and 4.14%, respectively, by mixture model.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.739-748
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• 2003

The objective of this study was to estimate genetic parameters for test-day milk production and somatic cell score using field data collected by dairy herd improvement program in Korea. Random regression animal models were applied to estimate genetic variances for milk production and somatic cell score. Heritabilities for milk yields, fat percentage, protein percentage, solid-not-fat percentage, and somatic cell score from test day records of 5,796 first lactation Holstein cows were estimated by REML algorithm in single trait random regression test-day animal models. For these analyses, Legendre polynomial covariate function was applied to model the fixed effect of age-season, the additive genetic effect and the permanent environment effect as random. Homogeneous residual variance was assumed to be equal throughout lactation. Heritabilities as a function of time were calculated from the estimated curve parameters from univariate analyses. Heritability estimates for milk yields were in range of 0.13 to 0.29 throughout first lactation. Heritability estimates for fat percentage, protein percentage and solid-not-fat percentage were within 0.09 to 0.11, 0.12 to 0.19 and 0.17 to 0.23, respectively. For somatic cell score, heritabilities were within 0.02 to 0.04. Heritabilities for milk productions and somatic cell score were fluctuated by days in milk with comparing 305d milk production.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.9
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• pp.1237-1246
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• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• The Journal of Internal Korean Medicine
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• v.37 no.1
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• pp.47-64
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• 2016

Objectives: In the present study, a genetic analysis was conducted to investigate the association of the expression of SNPs of EDN1 gene polymorphism with the clinical phenotype in bronchial asthma patients with either excess or deficiency syndrome.Methods: Ninety-four healthy control subjects and 52 asthma patients were included in this study. The asthma patients were divided into two groups: those with deficiency syndrome and those with excess syndrome. We searched the exonic and promoter areas of the EDN1 gene in the NCBI website SNPs with <0.01 minor allele frequency (MAF) and <0.01 heterozygosity. Pro programs were performed to obtain the odds ratio, 95% confidence interval, and p-value. Multiple logistic regression models were conducted to analyze the genetic data.Results: In our genotype and allele analyses, there were significant differences in the codominant 2 model of the rs3087459 SNP genotype and also in the CGG haplotype between the control group and the asthma group. Genotype and allele analyses were conducted between the deficiency and excess syndrome group. There were significant differences in the dominant and log-additive model and also in the frequency of C-alleles of rs3087459 SNP genotype. There were significant differences in codominant 1, dominant and log-additive model and T-allele of rs5370 SNP genotype. The AGG haplotype also revealed significant differences.Conclusions: EDN1 SNPs (rs3087459, rs5370) showed a significant association with symptomatic excess syndrome in Korean asthmatic patients.

• Nutrition Research and Practice
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• v.18 no.4
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• pp.554-566
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• 2024

BACKGROUND/OBJECTIVES: Urban-rural inequities in health and mortality exist in Korea, a highly centralized developed country. The potential impact of multiple health-related lifestyle behaviors on mortality and difference between urban and rural areas is not fully understood. This study aimed to investigate the effect of high-risk health behaviors on all-cause mortality among residents living in urban and rural in Korea. SUBJECTS/METHODS: Cross-sectional analyses were conducted on 8,298 adults aged 40 yrs and older from the Korea National Health and Nutrition Examination Survey 2013-2015. High-risk behaviors were defined as having poor diet quality, current smoking, high-risk drinking, or insufficient physical activity. Mortality status was linked to the Cause of Death data followed up to December 31, 2019. The associations between all-cause mortality and high-risk behaviors were evaluated using Cox proportional hazard regression models adjusted for age, sex, education, income, and survey year. Population attributable fractions (PAFs) were calculated, and effect modification analysis was conducted. Participants were stratified by residential area (urban or rural). RESULTS: During the follow-up (median: 5.4 yrs), 313 deaths occurred. A higher proportion of rural residents than urban residents engaged in multiple high-risk behaviors (28.9% vs. 22.6%; P < 0.0001). As individual factors, a greater risk of mortality was associated with poor diet quality, current smoking, and inadequate physical activity, and these tendencies persisted in rural residents, especially for diet quality. Multiple high-risk behaviors were positively associated with a higher risk of mortality in Koreans living in urban and rural areas. PAF (95% confidence interval) was 18.5% (7.35-27.9%) and 29.8% (16.1-40.2%) in urban and rural residents, respectively. No additive or multiplicative effect of the region was observed. CONCLUSION: The higher prevalence of multiple high-risk lifestyle behaviors in rural residents may explain the higher mortality in rural areas compared to urban areas. Comprehensive public health policies to improve health-related behaviors in rural populations may be needed.