• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.6
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• pp.767-771
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• 2002

Breeding efficiencies were compared among three population schemes: a single population, a population with two subpopulations and a population with three sub-populations. A simulation experiment of selection was carried out for 10 generations with 20 replications each by comparing average breeding values and inbreeding coefficients among the three population schemes. Phenotypes of three traits were generated with a model comprising 36 loci, each with additive genetic effects and residuals distributed normally. Among the three population schemes, the single population scheme was definitely superior to the other two with regards to selection response and inbreeding. The multiple sub-population scheme was, however, considered to be an alternative population scheme when the difference in economic weights of the traits was small among the sub-populations, assuming moderate inbreeding depression for traits and crossbreeding. The scheme with two sub-populations had a higher genetic value than that with three subpopulations; however, the genetic values of the schemes were comparable when maternal heterosis was taken into account. The choice of population schemes may depend on the cost-sharing policy between the breeding population and the commercial population rather than just the breeding efficiency.

• Animal Bioscience
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• v.35 no.12
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• pp.1839-1849
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• 2022

Objective: The study aims to uncover the genetic diversity and unique genetic structure of the Min pig conserved population, divide the nucleus conservation population, and construct the molecular pedigree. Methods: We used KPS Porcine Breeding Chip v1 50K for SNP detection of 94 samples (31♂, 63♀) in the Min pig conserved population from Lanxi breeding Farm. Results: The polymorphic marker ratio (PN), the observed heterozygosity (Ho), and the expected heterozygosity (He) were 0.663, 0.335, and 0.330, respectively. The pedigree-based inbreeding coefficients (F_PED) was significantly different from those estimated from runs of homozygosity (F_ROH) and single nucleotide polymorphism (F_SNP) based on genome. The Pearson correlation coefficient between F_ROH and F_SNP was significant (p<0.05). The effective population content (Ne) showed a continuously decreasing trend. The rate of decline was the slowest from 200 to 50 generations ago (r = 0.95), then accelerated slightly from 50 to 5 generations ago (1.40

• Animal Bioscience
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• v.36 no.10
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• pp.1508-1516
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• 2023

Objective: To carry out a comprehensive production planning of the existing Rongchang pig population from both environmental and genetic aspects, and to establish a closed population with stable genetic diversity and strict pathogen control, it is necessary to fully understand the genetic background of the population. Methods: We genotyped 54 specific pathogen free (SPF) Rongchang pigs using the Zhongxin-1 Porcine Breeding Array PLUS, calculated their genetic diversity parameters and constructed their families. In addition, we also counted the runs of homozygosity (ROH) of each individual and calculated the value of inbreeding coefficient based on ROH for each individual. Results: Firstly, the results of genetic diversity analysis showed that the effective population size (N_e) of this population was 3.2, proportion of polymorphic markers (P_N) was 0.515, desired heterozygosity (H_e) and observed heterozygosity (H_o) were 0.315 and 0.335. H_o was higher than H_e, indicating that the heterozygosity of all the selected loci was high. Secondly, combining the results of genomic relatedness analysis and cluster analysis, it was found that the existing Rongchang pig population could be divided into four families. Finally, we also counted the ROH of each individual and calculated the inbreeding coefficient value accordingly, whose mean value was 0.09. Conclusion: Due to the limitation of population size and other factors, the genetic diversity of this Rongchang pig population is low. The results of this study can provide basic data to support the development of Rongchang pig breeding program, the establishment of SPF Rongchang pig closed herd and its experimental utilization.

• Journal of Environmental Health Sciences
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• v.48 no.6
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• pp.298-305
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• 2022

Background: The concentration of air pollutants as measured by the Air Quality Monitoring System (AQMS) is not an accurate population exposure level since actual human activities and temporal and spatial variability need to be considered. Therefore, to increase the accuracy of exposure assessment, the population should be considered. However, it is difficult to obtain population data due to limitations such as personal information. Objectives: The existing population defined in this study is the number of people in each region's grid. The purpose is to provide a methodology for evaluating exposure to PM_2.5 through existing population data provided by the National Geographic Information Institute. Methods: The selected study period was from October 26 to October 28, 2021. Using PM_2.5 concentration data measured at the Sensor-based Air Monitoring Station (SAMS) installed in Guro-gu and Wonju-si, the concentration for each grid was estimated by applying inverse distance weights through QGIS version 3.22. Considering the existing population, population-weighted average concentration (PWAC) was calculated and the exposure level of the population was compared by region. Results: The outdoor PM_2.5 concentration as measured through the SAMS was high in Wonju-si on all three days. Wonju-si showed an average 22% higher PWAC than Guro-gu. As a result of comparing the PWAC and outdoor PM_2.5 concentration by region, the PWAC in Guro-gu was 1~2% higher than the observed value, but it was almost the same. Conversely, observations of Wonju-si were 10.1%, 11.3%, and 8.2% higher than PWAC. Conclusions: It is expected that the Geographic Information System (GIS) method and the existing population will be used to evaluate the exposure level of a population with a narrow activity radius in further research. In addition, based on this study, it is judged that research on exposure to environmental pollutants and risk assessment methods should be expanded.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Animal Bioscience
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• v.36 no.5
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• pp.692-703
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• 2023

Objective: The main goals of this investigation were to i) assess the population structure and genetic diversity and ii) determine the efficiency of the ongoing breeding program in a closed flock of Angora rabbits through pedigree analysis. Methods: The pedigree records of 6,145 animals, born between 1996 to 2020 at NTRS, ICAR-CSWRI, Garsa were analyzed using ENDOG version 4.8 software package. The genealogical information, genetic conservation index and parameters based on gene origin probabilities were estimated. Results: Analysis revealed that, 99.09% of the kits had both parents recorded in the whole dataset. The completeness levels for the whole pedigree were 99.12%, 97.12%, 90.66%, 82.49%, and 74.11% for the 1st, 2nd, 3rd, 4th, and 5th generations, respectively, reflecting well-maintained pedigree records. The maximum inbreeding, average inbreeding and relatedness were 36.96%, 8.07%, and 15.82%, respectively. The mean maximum, mean equivalent and mean completed generations were 10.28, 7.91, and 5.51 with 0.85%, 1.19%, and 1.85% increase in inbreeding, respectively. The effective population size estimated from maximum, equivalent and complete generations were 58.50, 27.05, and 42.08, respectively. Only 1.51% of total mating was highly inbred. The effective population size computed via the individual increase in inbreeding was 42.83. The effective numbers of founders (f_e), ancestors (f_a), founder genomes (f_g) and non-founder genomes (f_ng) were 18, 16, 6.22, and 9.50, respectively. The fe/fa ratio was 1.12, indicating occasional bottlenecks had occurred in the population. The six most influential ancestors explained 50% of genes contributed to the gene pool. The average generation interval was 1.51 years and was longer for the sire-offspring pathway. The population lost 8% genetic diversity over time, however, considerable genetic variability still existed in the closed Angora population. Conclusion: This study provides important and practical insights to manage and maintain the genetic variability within the individual flock and the entire population.

• Animal Bioscience
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• v.35 no.4
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• pp.511-516
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• 2022

Objective: A genomic region associated with a particular phenotype is called quantitative trait loci (QTL). To detect the optimal F₂ population size associated with QTLs in native chicken, we performed a simulation study on F₂ population derived from crosses between two different breeds. Methods: A total of 15 males and 150 females were randomly selected from the last generation of each F₁ population which was composed of different breed to create two different F₂ populations. The progenies produced from these selected individuals were simulated for six more generations. Their marker genotypes were simulated with a density of 50K at three different heritability levels for the traits such as 0.1, 0.3, and 0.5. Our study compared 100, 500, 1,000 reference population (RP) groups to each other with three different heritability levels. And a total of 35 QTLs were used, and their locations were randomly created. Results: With a RP size of 100, no QTL was detected to satisfy Bonferroni value at three different heritability levels. In a RP size of 500, two QTLs were detected when the heritability was 0.5. With a RP size of 1,000, 0.1 heritability was detected only one QTL, and 0.5 heritability detected five QTLs. To sum up, RP size and heritability play a key role in detecting QTLs in a QTL study. The larger RP size and greater heritability value, the higher the probability of detection of QTLs. Conclusion: Our study suggests that the use of a large RP and heritability can improve QTL detection in an F₂ chicken population.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.428-434
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• 1997

The effect of genetic diversity in sub-populations on breeding efficiency was examined with prospect of potential crossbreeding. Simulation study of selection was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systemes; single population scheme and two population scheme. The different genetic levels were assumed to be caused by different gene frequencies. Phenotypes of two traits generated polygenic effect with additive 36 loci and residuals distributed normally were selected by selection index procedure. High genetic gain with less inbreeding was clearly recognized in the single population scheme, independently of difference in genetic level, economic weight and genetic correlation. Genetic correlation after selection in the single population scheme was lower than the two population scheme. When crossbreeding between the sub-population was taken into account, superiority of the two population scheme was suggested under those restrictions; difference in genetic level is moderate, selection criterion for the two traits is not far from even economic weight, and genetic correlation is positive with low to moderate value. The use of complementarity increased the possibility of the two population scheme.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.362-371
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• 2023

Background: PM_2.5 pollution has been a persistent problem in South Korea, with concentrations consistently exceeding World Health Organization (WHO) guidelines. The aging of the population in the country further exacerbates the health impacts of PM_2.5 since older adults are more susceptible to the adverse effects of air pollution. Objectives: This study aims to evaluate how the health impact (premature death) due to long-term exposure to PM_2.5 in South Korea could change in the future according to the trend of change in the country's population structure. Methods: The study employs a relative risk function, which accounts for age-specific relative risks, to assess the changes in premature deaths by age and region at the average annual PM_2.5 concentration for 2022 and at PM_2.5 concentration improvement levels. Premature deaths were estimated using the Global Exposure Mortality Model (GEMM). Results: The findings indicate that the increase in premature deaths resulting from the projected population structure changes up to 2050 would significantly outweigh the health benefits (reduction in premature deaths) compared to 2012. This is primarily attributed to the rising number of premature deaths among the elderly due to population aging. Furthermore, the study suggests that the effectiveness of the current domestic PM_2.5 standard would be halved by 2050 due to the increasing impact of population aging on PM_2.5-related mortality. Conclusions: The study highlights the importance of considering trends in population structure when evaluating the health benefits of air pollution reduction measures. By comparing and evaluating the health benefits in reflection of changes in population structure to the predicted PM_2.5 concentration improvements at the provincial level, a more comprehensive assessment of regional air quality management strategies can be achieved.