• Asian-Australasian Journal of Animal Sciences
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• v.15 no.2
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• pp.166-171
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• 2002

The main objective of the present study is to estimate the crossbreeding parameters in respect to serum lysozyme level in broilers. The experiment involved a complete $4{\times}4$ diallel design using four synthetic broiler lines namely Coloured Synthetic Male Line (CSML), White Synthetic Male Line (WSML), Coloured Synthetic Female Line (CSFL) and Naked Neck Line (NNL). The lyophilised Micrococcus lysodeikticus suspension was used to detect the lysozyme level in the serum of birds. The data were analysed by least-squares method to find the effects of genetic and non-genetic factors using appropriate model. The crossbreeding parameters for this trait were estimated by complete diallel model assuming the effect of each synthetic line as fixed. The results indicated that additive and non-additive genetic variation attributed to minor genes at many loci is important for the genetic control of serum lysozyme level in chickens. Total non-additive components of variance also showed significant amount of heterosis in crossbred progenies, and therefore exploitation of non-additive component of variance is possible for improvement in serum lysozyme level in broilers. The overall results suggested that for commercial broiler production system, the selection for specialised line on the basis of serum lysozyme level and subsequent crossing of parent lines could enhance the immunocompetence status in relation to serum lysozyme level in crossbred chickens.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.3
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• pp.60-67
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• 2008

In this study, the genetic algorithm has been used for the real-time defect diagnosis on the operation of the aircraft gas-turbine engine. The component elements of the gas-turbine engine for consideration of the performance deterioration consist of the compressor, the gas generation turbine and the power turbine. Compared to the on-design point, the teaming data has been increased 200 times in case off-design conditions for the altitude, the flight mach number and the fuel consumption. Therefore, enormous learning time has been required for the satisfied convergence. The optimal division has been proposed for learning time decrease as well as the high accuracy. As results, the RMS errors of the defect diagnosis using the genetic algorithm have been confirmed under 5 %.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.3
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• pp.238-247
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• 2007

Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to learning algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generator turbine and power turbine are considered for engine performance deterioration and estimation for performance deterioration of a single component at design point was conducted. As a result of that, defect diagnostics has been conducted. The input criteria for the genetic algorithm to guarantee the high stability and reliability was discussed as increasing learning data sets. As a result, the accuracy of defect estimation and diagnostics were verified with its RMS error within 3%.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.6
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• pp.775-781
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• 2016

A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

• Journal of Ginseng Research
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• v.35 no.3
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• pp.344-351
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• 2011

Ginsenoside $Rb_1$ is the main component in ginsenosides. It is a protopanaxadiol-type ginsenoside that has a dammarane-type triterpenoid as an aglycone. In this study, ginsenoside $Rb_1$ was transformed into gypenoside XVII, ginsenoside Rd, ginsenoside $F_2$ and compound K by glycosidase from Leuconostoc mesenteroides DC102. The optimum time for the conversion was about 72 h at a constant pH of 6.0 to 8.0 and the optimum temperature was about $30^{\circ}C$. Under optimal conditions, ginsenoside $Rb_1$ was decomposed and converted into compound K by 72 h post-reaction (99%). The enzymatic reaction was analyzed by highperformance liquid chromatography, suggesting the transformation pathway: ginsenoside $Rb_1$ ${\rightarrow}$ gypenoside XVII and ginsenoside Rd${\rightarrow}$ginsenoside $F_2{\rightarrow}$compound K.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1365-1371
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• 2017

Objective: This study was conducted to investigate the basic information on genetic structure and characteristics of Korean Native chickens (NC) and foreign breeds through the analysis of the pure chicken populations and commercial chicken lines of the Hanhyup Company which are popular in the NC market, using the 20 microsatellite markers. Methods: In this study, the genetic diversity and phylogenetic relationships of 445 NC from five different breeds (NC, Leghorn [LH], Cornish [CS], Rhode Island Red [RIR], and Hanhyup [HH] commercial line) were investigated by performing genotyping using 20 microsatellite markers. Results: The highest genetic distance was observed between RIR and LH (18.9%), whereas the lowest genetic distance was observed between HH and NC (2.7%). In the principal coordinates analysis (PCoA) illustrated by the first component, LH was clearly separated from the other groups. The correspondence analysis showed close relationship among individuals belonging to the NC, CS, and HH lines. From the STRUCTURE program, the presence of 5 clusters was detected and it was found that the proportion of membership in the different clusters was almost comparable among the breeds with the exception of one breed (HH), although it was highest in LH (0.987) and lowest in CS (0.578). For the cluster 1 it was high in HH (0.582) and in CS (0.368), while for the cluster 4 it was relatively higher in HH (0.392) than other breeds. Conclusion: Our study showed useful genetic diversity and phylogenetic relationship data that can be utilized for NC breeding and development by the commercial chicken industry to meet consumer demands.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.4
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• pp.445-452
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• 2004

Genetic diversity of sub-Saharan African goats was assessed using 19 microsatellite markers. Breeds were sampled from eastern Africa (Maasai, Kigezi, Mubende, North West Highland, Arsi-Bale), southern Africa (Ndebele, Pafuri) and West Africa (West African Dwarf, Maure, Djallonke). European breeds (Grisons Striped, Toggenburg), Asian breeds (Mongolian Cashmere, Bandipur) and a Middle East breed (Arab) were also included. The mean number of alleles per locus and average gene diversity ranged from 5.26$\pm$0.464 (Djallonke) to 7.05$\pm$0.516 (Mubende) and from 0.542$\pm$0.036 (Pafuri) to 0.672$\pm$0.031 (Ndebele), respectively. The between breeds variation evaluated using $$G_{ST}$$ and $\theta$ were found to account for 14.6% ($\theta$) and 15.7% ($$G_{ST}$$) of the total genetic variation. The $D_{A}$ measure of genetic distance between pairs of breeds indicated that the largest genetic distance was between Pafuri and Djallonke while the lowest genetic distance was between Arsi-Bale and North West Highland. A neighbour-joining tree of breed relationships revealed that the breeds were grouped according to their geographic origins. Principal component analysis supported the grouping of the breeds according to their geographic origins. It was concluded that the relationships of sub-Saharan African goat breeds were according to their geographical locations implying that the goats of eastern Africa, West Africa and southern Africa are genetically distinct. Within each sub-region, goat populations could be differentiated according to morphological characteristics.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.467-476
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• 2019

Objective: This research was conducted to study the genetic diversity in several Indonesian cattle breeds using microsatellite markers to classify the Indonesian cattle breeds. Methods: A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase chain reaction process was conducted using 12 labeled primers. The size of allele was generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS programs were used to obtain the observed number of alleles, effective number of alleles, observed heterozygosity value, expected heterozygosity value, allele frequency, genetic differentiation, the global heterozygote deficit among breeds, and the heterozygote deficit within the breed, gene flow, Hardy-Weinberg equilibrium, and polymorphism information content values. The MEGA program was used to generate a dendrogram that illustrates the relationship among cattle population. Bayesian clustering assignments were analyzed using STRUCTURE program. The GENETIX program was used to perform the correspondence factorial analysis (CFA). The GENALEX program was used to perform the principal coordinates analysis (PCoA) and analysis of molecular variance. The principal component analysis (PCA) was performed using adegenet package of R program. Results: A total of 862 alleles were detected in this study. The INRA23 allele 205 is a specific allele candidate for the Sumba Ongole cattle, while the allele 219 is a specific allele candidate for Ongole Grade. This study revealed a very close genetic relationship between the Ongole Grade and Sumba Ongole cattle and between the Madura and Pasundan cattle. The results from the CFA, PCoA, and PCA analysis in this study provide scientific evidence regarding the genetic relationship between Banteng and Bali cattle. According to the genetic relationship, the Pesisir cattle were classified as Bos indicus cattle. Conclusion: All identified alleles in this study were able to classify the cattle population into three clusters i.e. Bos taurus cluster (Simmental Purebred, Simmental Crossbred, and Holstein Friesian cattle); Bos indicus cluster (Sumba Ongole, Ongole Grade, Madura, Pasundan, and Pesisir cattle); and Bos javanicus cluster (Banteng and Bali cattle).

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.1
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• pp.19-25
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• 2018

Objective: In practical breeding, selection is often performed by ignoring the accuracy of evaluations and applying economic weights directly to the selection index coefficients of genetically standardized traits. The denominator of the standardized component trait of estimated genetic evaluations in practical selection varies with its reliability. Whereas theoretical methods for calculating the selection index coefficients of genetically standardized traits account for this variation, practical selection ignores reliability and assumes that it is equal to unity for each trait. The purpose of this study was to clarify the effects of ignoring the accuracy of the standardized component trait in selection criteria on selection responses and economic weights in retrospect. Methods: Theoretical methods were presented accounting for reliability of estimated genetic evaluations for the selection index composed of genetically standardized traits. Results: Selection responses and economic weights in retrospect resulting from practical selection were greater than those resulting from theoretical selection accounting for reliability when the accuracy of the estimated breeding value (EBV) or genomically enhanced breeding value (GEBV) was lower than those of the other traits in the index, but the opposite occurred when the accuracy of the EBV or GEBV was greater than those of the other traits. This trend was more conspicuous for traits with low economic weights than for those with high weights. Conclusion: Failure of the practical index to account for reliability yielded economic weights in retrospect that differed from those obtained with the theoretical index. Our results indicated that practical indices that ignore reliability delay genetic improvement. Therefore, selection practices need to account for reliability, especially when the reliabilities of the traits included in the index vary widely.

• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.4
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• pp.81-88
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.