• Animal Bioscience
• /
• v.34 no.7
• /
• pp.1116-1122
• /
• 2021

Objective: The aim was to characterize the genetic diversity evolution of the registered Mexican Charolais cattle population by pedigree analysis. Methods: Data consisted of 331,390 pedigree records of animals born from 1934 to 2018. Average complete generation equivalent, generation interval, effective population size (N_e), and effective numbers of founders (f_e), ancestors (f_a), and founder genomes (N_g) were calculated for seven five-year periods. The inbreeding coefficient was calculated per year of birth, from 1984 to 2018, whereas the gene contribution of the most influential ancestors was calculated for the latter period. Results: Average complete generation equivalent consistently increased across periods, from 4.76, for the first period (1984 through 1988), to 7.86, for the last period (2014 through 2018). The inbreeding coefficient showed a relative steadiness across the last seventeen years, oscillating from 0.0110 to 0.0145. During the last period, the average generation interval for the father-offspring pathways was nearly 1 yr. longer than that of the mother-offspring pathways. The effective population size increased steadily since 1984 (105.0) and until 2013 (237.1), but showed a minor decline from 2013 to 2018 (233.2). The population displayed an increase in the f_a since 1984 and until 2008; however, showed a small decrease during the last decade. The effective number of founder genomes increased from 1984 to 2003, but revealed loss of genetic variability during the last fifteen years (from 136.4 to 127.7). The f_a:f_e ratio suggests that the genetic diversity loss was partially caused by formation of genetic bottlenecks in the pedigree; in addition, the N_g:f_a ratio indicates loss of founder alleles due to genetic drift. The most influential ancestor explained 1.8% of the total genetic variability in the progeny born from 2014 to 2018. Conclusion: Inbreeding, N_e, f_a, and N_g are rather beyond critical levels; therefore, the current genetic status of the population is not at risk.

• Animal Bioscience
• /
• v.37 no.5
• /
• pp.795-806
• /
• 2024

Objective: Karan Fries (KF), a high-producing composite cattle was developed through crossing indicine Tharparkar cows with taurine bulls (Holstein Friesian, Brown Swiss, and Jersey), to increase the milk yield across India. This composite cattle population must maintain sufficient genetic diversity for long-term development and breed improvement in the coming years. The level of linkage disequilibrium (LD) measures the influence of population genetic forces on the genomic structure and provides insights into the evolutionary history of populations, while the decay of LD is important in understanding the limits of genome-wide association studies for a population. Effective population size (N_e) which is genomically based on LD accumulated over the course of previous generations, is a valuable tool for e valuation of the genetic diversity and level of inbreeding. The present study was undertaken to understand KF population dynamics through the estimation of N_e and LD for the long-term sustainability of these breeds. Methods: The present study included 96 KF samples genotyped using Illumina HDBovine array to estimate the effective population and examine the LD pattern. The genotype data were also obtained for other crossbreds (Santa Gertrudis, Brangus, and Beefmaster) and Holstein Friesian cattle for comparison purposes. Results: The average LD between single nucleotide polymorphisms (SNPs) was r² = 0.13 in the present study. LD decay (r² = 0.2) was observed at 40 kb inter-marker distance, indicating a panel with 62,765 SNPs was sufficient for genomic breeding value estimation in KF cattle. The pedigree-based N_e of KF was determined to be 78, while the N_e estimates obtained using LD-based methods were 52 (SNeP) and 219 (genetic optimization for N_e estimation), respectively. Conclusion: KF cattle have an N_e exceeding the FAO's minimum recommended level of 50, which was desirable. The study also revealed significant population dynamics of KF cattle and increased our understanding of devising suitable breeding strategies for long-term sustainable development.

• Korean Journal of Environmental Biology
• /
• v.37 no.3
• /
• pp.335-342
• /
• 2019

The purpose of this study was to investigate the toxic effects of zinc in collembolan Paronychiurus kimi at the individual (survival and juvenile production) and population (population growth and age structure) levels after 28 days of exposure in artificially spiked soil. These toxic effects were interpreted in conjunction with the internal zinc concentrations in P. kimi. The EC₅₀ value for juvenile production based on the total zinc concentration was 457 mg Zn kg^-1 dry soil, while the LC₅₀ value for adult survival and r_i=0 value for population growth were within the same order of magnitude (2,623 and 1,637 mg Zn kg^-1 dry soil, respectively). Significant differences in adult survival, juvenile production, and population growth compared with the control group were found at concentrations of 1,500, 375, and 375 mg Zn kg^-1 dry or higher, respectively, whereas significant differences in the age structure, determined by the proportion of each age group in the population, were observed in all treatment groups. It appeared that the internal zinc level in P. kimi was regulated to some extent at soil zinc concentrations of ≤375 mg Zn kg^-1 dry soil, but not at high soil zinc concentrations. These results indicate that, despite zinc being regulated by P. kimi, excess zinc exceeding the regulatory capacity of P. kimi can trigger changes in the responses at the individual and population levels. Given that population dynamics are affected not only by individual level but also by population level endpoints, it is concluded that the toxic effects of pollutants should be assessed at various levels.

• Journal of the Korea Safety Management & Science
• /
• v.3 no.3
• /
• pp.191-200
• /
• 2001

Parallel Genetic Algorithms partition the whole population into several sub-populations and search the optimal solution by exchanging the information each others periodically. Distributed Genetic Algorithm, one of Parallel Genetic Algorithms, divides a large population into several sub-populations and executes the traditional Genetic Algorithm on each sub-population independently. And periodically promising individuals selected from sub-populations are migrated by following the migration interval and migration rate to different sub-populations. In this paper, for the Travelling Salesman Problems, we analyze and compare with Distributed Genetic Algorithms using different Genetic Algorithms and using same Genetic Algorithms on each separated sub-population The simulation result shows that using different Genetic Algorithms obtains better results than using same Genetic Algorithms in Distributed Genetic Algorithms. This results look like the property of rapidly searching the approximated optima and keeping the variety of solution make interaction in different Genetic Algorithms.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.9
• /
• pp.1369-1377
• /
• 2020

Objective: The main objectives of the present study were to assess the genetic diversity, population structure and to appraise the efficiency of ongoing selective breeding program in the closed nucleus herd of Nellore sheep through pedigree analysis. Methods: Information utilized in the study was collected from the pedigree records of Livestock Research Station, Palamaner during the period from 1989 to 2016. Genealogical parameters like generation interval, pedigree completeness, inbreeding level, average relatedness among the animals and genetic conservation index were estimated based on gene origin probabilities. Lambs born during 2012 and 2016 were considered as reference population. Two animal models either with the use of F_i or ΔF_i as linear co-variables were evaluated to know the effects of inbreeding on the growth traits of Nellore sheep. Results: Average generation interval and realized effective population size for the reference cohort were estimated as 3.38±0.10 and 91.56±1.58, respectively and the average inbreeding coefficient for reference population was 3.32%. Similarly, the effective number of founders, ancestors and founder genome equivalent of the reference population were observed as 47, 37, and 22.48, respectively. Fifty per cent of the genetic variability was explained by 14 influential ancestors in the reference cohort. The ratio f_e/f_a obtained in the study was 1.21, which is an indicator of bottlenecks in the population. The number of equivalent generations obtained in the study was 4.23 and this estimate suggested the fair depth of the pedigree. Conclusion: Study suggested that the population had decent levels of genetic diversity and a non-significant influence of inbreeding coefficient on growth traits of Nellore lambs. However, small portion of genetic diversity was lost due to a disproportionate contribution of founders and bottlenecks. Hence, breeding strategies which improve the genetic gain, widens the selection process and with optimum levels of inbreeding are recommended for the herd.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2480-2488
• /
• 2024

Pakistan is a developing country whose maximum amount of mixed energy is provided by electricity, oil, coal, and gas. The study objective is to analyze the six major social factors to describe the significance of nuclear energy and CO₂ emissions at the decisive point coming from income, trade, energy, and urbanization. This study has tried to analyze the impact of different factors (i.e., fossil energy, GDP per capita, overall population, urban population, and merchandise trade) on Pakistan's CO₂ emissions using the extended STRIPAT model from 1986 to 2021. Ridge regression has been applied to analyze the parameters due to the multicollinearity problem in the data. The results show that (i) all the factors show significant results on carbon emissions; (ii) population and energy factors are the huge contributors to raising CO₂ emissions by 0.15% and 0.16%; however, merchandise and GDP per capita are the least contributing factors by 0.12% and 0.13% due to import/export and income level in Pakistan, and (iii) nuclear energy and substitute overall show a prominent and growing impact on CO₂ emissions by 0.16% and 0.15% in Pakistan. Finally, empirical results have wider applications for energy-saving, energy substitution, capital investment, and CO₂ emissions mitigation policies in developing countries. Moreover, by investigating renewable energy technologies and renewable energy sources, insights are provided on future CO₂ emissions reduction.

• The Plant Pathology Journal
• /
• v.37 no.3
• /
• pp.280-290
• /
• 2021

Population genetic studies of Hemileia vastatrix have been conducted in order to describe the evolutionary dynamics of the pathogen and the disease epidemiology as consequence of changes in disease management and host distribution occurred in Peru after the 2013 epidemic. These analyses were performed by sequencing the internal transcribed spacers of the nuclear ribosomal DNA (rDNA-ITS) of H. vastatrix collected from two coffee growing areas in 2014 and 2018. H. vastatrix population showed high haplotype diversity (Hd = 0.9373 ± 0.0115) with a low nucleotide diversity (π = 0.00322 ± 0.00018). Likewise, AMOVA indicated that fungus population has behaved as a large population without structuring by geographical origin and sampling years (F_ST = 0.00180, P = 0.20053 and F_ST = 0.00241, P = 0.19693, respectively). Additionally, the haplotype network based on intraspecific phylogenetic analysis of H. vastatrix using Peruvian and NCBI sequences revealed that Peruvian ancestral haplotypes, which were maintained in time and space, would correspond to the reported sequences of the races II and XXII. This result suggests that no substantial changes have occurred through time in Peruvian Hemileia vastatrix population.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.10a
• /
• pp.40-47
• /
• 2000

One of the drawbacks of GA-based structural optimization is that the fitness evaluation of a population of hundreds of individuals requiring hundreds of structural analyses at each CA generation is computational too expensive. Therefore, a parallel genetic algorithm is developed for structural optimization on a cluster of personal computers in this paper. Based on the parallel genetic algorithm, a population at every generation is partitioned into a number of sub-populations equal to the number of slave computers. Parallelism is exploited at sub-population level by allocationg each sub-population to a slave computer. Thus, fitness of a population at each generation can be concurrently evaluated on a cluster of personal computers. For implementation of the algorithm a virtual distributed computing system in a collection of personal computers connected via a 100 Mb/s Ethernet LAN. The algorithm is applied to the minimum weight design of a steel structure. The results show that the computational time requied for serial GA-based structural optimization process is drastically reduced.

• Fisheries and Aquatic Sciences
• /
• v.27 no.6
• /
• pp.392-409
• /
• 2024

The present study aims to analyze the biological aspects and population dynamics of Indian mackerel in Barru waters. Data was collected in Barru for 11 months, from June 2022 to April 2023. The observed parameters of biological aspects included gonadal maturation stages (GMSs), size at first gonadal maturation, and length-weight relationship. Meanwhile, the aspects of population dynamics encompass age group, growth, mortality rate, and exploitation rate. Data analysis consisted of morphological selection of general maturation stages, Spearman-Kärber method in estimating gonadal first maturation size, Bhattacharya method in identifying age group, von Bertalanffy function through FISAT II to measure growth (L_∞ and K), Pauly Model to estimate mortality rate, Beverton & Holt Model to estimate Y/R, and virtual population analysis (VPA) analysis to estimate stock and fish yield. The results demonstrated that GMS I was observed to be dominant, followed by stages II and III. The initial gonadal maturation was estimated to be 17.98-19.28 cm (FL) for females and 17.98-19.27 cm (FL) for males. The length-weight relationship in male and female Indian mackerels indicated a positive allometric growth. The mode grouping analysis results from the fork length measurement revealed three age groups. It was also identified that the asymptotic length (L_∞) = 29.5 cm (fork length), growth rate coefficient (K) = 0.46 per year, and theoretical age at zero length (t₀) = -0.3576 per year. Total mortality (Z) = 2.67 per year, natural mortality (M) = 1.10 per year, fishing mortality (F) = 1.57 per year, and exploitation rate (E) = 0.59, the actual Y/R = 0.083 gram/recruitment, and optimal Y/R 0.03 gram/recruitment. Fishing mortality is higher than the natural mortality rate, and a high exploitation value (E > 0.5) also reflects over-exploitation. VPA analysis on fish yields and stock estimation reported a highly exploited rate between the 11.5 cm and 14.5 cm length classes and an exceeding current yield of 467.07 tons/year with a recommended yield of 233.53 tons/year to ensure population sustainability.

• Animal Bioscience
• /
• v.36 no.3
• /
• pp.417-428
• /
• 2023

Objective: Few studies have genetically monitored chickens over time, and no research has been conducted on ducks. To ensure the sustainable management of key duck breeds, we used microsatellite markers to monitor Brown Tsaiya ducks over time genetically. Methods: The second, fourth, sixth to eighth generations of the Brown Tsaiya duck selected for feeding efficiency and control lines were included in this study to investigate the genetic variations, effective population size, population structure and the differentiation between populations over time with 11 microsatellite markers derived from Brown Tsaiya duck. Results: The results showed there were a slight decrease in the genetic variations and an increase in within-population inbreeding coefficient (F_IS) in both lines, but no consistent increase in F_IS was observed in each line. The effective population size in the second and eighth generations was 27.2 for the selected line and 23.9 for the control line. The change in allele richness showed a downward trend over time, and the selected line was slightly lower than the control line in each generation. The number of private alleles (N_p) in the selected line were higher than in the control line. Moderate differentiation was observed between the second and eighth generations in the selected line (F_ST = 0.0510) and the control line (F_ST = 0.0606). Overall, differentiation tended to increase with each generation, but genetic variation and structure did not change considerably after six generations in the two lines. Conclusion: This study provides a reference for poultry conservation and helps to implement cross-generation genetic monitoring and breeding plans in other duck breeds or lines to promote sustainable management.