Genetic aspects of calving, growth, and carcass traits in beef cattle

The aim of this thesis was to learn more about the genetic background of calving, growth and carcass traits of beef cattle breeds in Sweden, and to assess the possibility of including calving traits and commercial carcass traits in the genetic evaluation. In addition, the genetic relationship between field-recorded growth rate and daily weight gain at station performance testing was investigated. The breeds studied were Charolais, Hereford and Simmental. Records of birth weight, pre-weaning gain, post-weaning gain, carcass fleshiness grade, carcass fatness grade, carcass weight, calving difficulty score and stillbirth were analysed using linear animal models. The estimated direct heritabilities were moderate to high for birth and carcass weight, moderate for pre- and post-weaning gain, carcass fleshiness and fatness grades, low for calving difficulty score and very low for stillbirth. Maternal heritabilities tended to be lower than the direct ones. Genetic relationships between direct and maternal genetic effects were generally antagonistic. Moderate to high genetic correlations were estimated between post-weaning gain in the field and at the station, showing considerable breed differences, and the added value of station testing was questioned. Genetic relationships were generally weaker between growth traits and both carcass fleshiness and fatness grade than between growth and carcass weight. Male and female birth weights were found to be the same trait genetically, and strong genetic relationships were estimated between birth weight and calving traits. Less than unity genetic correlations between calving difficulty at first and later parities indicated that partly different sets of genes control these traits. Some antagonistic relationships were found between carcass and calving traits. It was concluded that it would be feasible to include commercial carcass records and calving difficulty score in the genetic evaluation, and that both direct and maternal effects should be considered for pre-weaning traits. Information on correlated traits should be used for selection against stillbirth as direct selection would be inefficient due to small progeny group size and very low heritability. Joint genetic evaluation of pre-weaning gain and carcass weight was recommended to reduce selection bias

Genetic Diversity Evaluation of Moringa Oleifera, Lam From East Flores Regency Using Marker Random Amplified Polymorphic DNA (RAPD) and Its Relationship to Chemical Composition and in Vitro Gas Production

The research objective was to evaluate the genetic diversity of Moringa oleifera, Lam (MO) and its relationship to chemical composition and in vitro gas production (IVGP). Fresh MO leaves were kept frozen in ice gels pack until laboratory analysis. Four methods applied: RAPD marker for measuring DNA concentration and purification; Kjeldhal and HPLC for analysing proximate and amino acid (AA) composition; and IVGP. MO\u27s four distinct morphology found: green, red, reddish green and aromatic green. RAPD result analysis was 68.8-74.7 %, it means those MO had a close genetic similarity. The morphological differences are also related to leaves chemical composition variation. The highest protein and AAs content were found in aromatic green MO. Total IVGP at 96 hours reached 95.9, 99.3, 111, 115 mL per 500 mg DM in aromatic green, green, reddish green, red MO, respectively and statistically among those was highly significant difference (P<0.01). However, DM and OM digestibility did not differ significantly and estimated ME contents were similar suggesting MO leaves had sufficient fermentable nitrogen amount required to ensure rumen microbes normal activities. Conclusively, those MO has a close genetic relationship but the aromatic green MO more beneficial due its higher content of crude protein and AAs

A service oriented architecture for engineering design

Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithms (MOGAs) are well suited to implementation in a Service Oriented Architecture. Often the evaluation process of the MOGA is compute-intensive due to the use of a complex computer model to represent the real-world system. The emerging paradigm of Grid Computing offers a potential solution to the compute-intensive nature of this objective function evaluation, by allowing access to large amounts of compute resources in a distributed manner. This paper presents a grid-enabled framework for multi-objective optimisation using genetic algorithms (MOGA-G) to aid decision making in engineering design

Chloroplast microsatellites: measures of genetic diversity and the effect of homoplasy

Chloroplast microsatellites have been widely used in population genetic studies of conifers in recent years. However, their haplotype configurations suggest that they could have high levels of homoplasy, thus limiting the power of these molecular markers. A coalescent-based computer simulation was used to explore the influence of homoplasy on measures of genetic diversity based on chloroplast microsatellites. The conditions of the simulation were defined to fit isolated populations originating from the colonization of one single haplotype into an area left available after a glacial retreat. Simulated data were compared with empirical data available from the literature for a species of Pinus that has expanded north after the Last Glacial Maximum. In the evaluation of genetic diversity, homoplasy was found to have little influence on Nei's unbiased haplotype diversity (H(E)) while Goldstein's genetic distance estimates (D2sh) were much more affected. The effect of the number of chloroplast microsatellite loci for evaluation of genetic diversity is also discussed

Evolving cellular automata to generate nonlinear sequences with desirable properties

This paper presents a new chromosomal representation and associated genetic operators for the evolution of highly nonlinear cellular automata that generate pseudorandom number sequences with desirable properties ensured. This chromosomal representation reduces the computational complexity of genetic operators to evolve valid solutions while facilitating fitness evaluation based on the DIEHARD statistical tests

Contesting Genetic Knowledge-Practices in Livestock Breeding: Biopower, Biosocial Collectivities, and Heterogeneous Resistances

Cattle and sheep breeders in the UK and elsewhere increasingly draw on genetic techniques in order to make breeding decisions. Many breeders support such techniques, while others argue against them for a variety of reasons, including their preference for the ‘traditions' of visual-based and pedigree-based selections. Meanwhile, even for those institutions and breeders who promote genetic techniques, the outcomes are not always as predicted. We build on our recent use of Foucault's discussions of biopower to examine the effects of the introduction of genetic techniques in UK livestock breeding in order to begin to explore the diffuse and capillary nature of resistance within relations of biopower. We focus specifically on how resistance and contestation can be understood through the joint lenses of biopower and an understanding of livestock breeding as knowledge-practices enacted within heterogeneous biosocial collectivities. In some instances these collectivities coalesce around shared endeavour, such as increasing the valency of genetic evaluation within livestock breeding. Yet such mixed collectivities also open up opportunities for counter-conduct: heterogeneous resistances to and contestations of genetic evaluation as something represented as progressive and inevitable. We focus on exploring such modes of resistance using detailed empirical research with livestock breeders and breeding institutions. We demonstrate how in different and specific ways geneticisation becomes problematised, and is contested and made more complex, through the knowledge-practices of breeders, the bodies of animals, and the complex relationships between different institutions in livestock breeding and rearing

Genetic Algorithms: Genesis of Stock Evaluation

The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many optimisation models that have subsequently addressed much of the scepticism. In this paper the author proposes a methodology based on Genetic Algorithms and individual data maximum likelihood estimation using logit model arguing that forecasting discrepancy can be rationalised by combined approximation of both the approaches. Thus this paper offers a methodological overture to further investigate the anomalies surrounding stock market. In the main, this paper attempts to provide a temporal dimension of the methods transposed on recurrent series of data over a fixed window conjecturereGenetic Algorithms, Individual Maximum Likelihood Estimation, Stock Price

Higher-Order Quantum-Inspired Genetic Algorithms

This paper presents a theory and an empirical evaluation of Higher-Order Quantum-Inspired Genetic Algorithms. Fundamental notions of the theory have been introduced, and a novel Order-2 Quantum-Inspired Genetic Algorithm (QIGA2) has been presented. Contrary to all QIGA algorithms which represent quantum genes as independent qubits, in higher-order QIGAs quantum registers are used to represent genes strings which allows modelling of genes relations using quantum phenomena. Performance comparison has been conducted on a benchmark of 20 deceptive combinatorial optimization problems. It has been presented that using higher quantum orders is beneficial for genetic algorithm efficiency, and the new QIGA2 algorithm outperforms the old QIGA algorithm which was tuned in highly compute intensive metaoptimization process