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Author: Fiona Galbraith
Publisher: National Library of Canada = Bibliothèque nationale du Canada
ISBN: 9780612906464
Category :
Languages : en
Pages : 118
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![Genetic Evaluation of Longevity in Ayrshire and Jersey Dairy Cattle Using a Random Regression Model [microform] PDF](https://books.google.com/books/content/images/frontcover/q4quwgEACAAJ?fife=w80-h100)
Author: Fiona Galbraith
Publisher: National Library of Canada = Bibliothèque nationale du Canada
ISBN: 9780612906464
Category :
Languages : en
Pages : 118
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ISBN: 9789463430821
Category :
Languages : en
Pages : 188
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Author: Johannes Heise
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Longevity is an important trait in dairy cows, reflecting the overall functionality of a cow. The aim of this thesis was the development of a new model for the routine genetic evaluation of longevity in German Holsteins. To achieve this purpose, different studies were conducted. They are briefly summarized in the following: Chapter 1 provides the reader with background information on base principles of survival theory and on the frame conditions of routine genetic evaluations of longevity in German Holsteins. At the end, the necessity for a new routine evaluation system is defined. With the...
Author: Janez Jenko
Publisher:
ISBN:
Category :
Languages : en
Pages : 264
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Author: Špela Malovrh
Publisher:
ISBN:
Category :
Languages : en
Pages : 186
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Longitudinal measurements of body weight in 3,918 boars and 1,532 bulls from test station were analysed by random-regression models. Both species were housed in groups. Boars had 6 measurements during test, and bulls approximately 9. Covariance components for random-regression coefficients wereestimated by the REML method and the VCE5 software package. Orthogonal Legendre polynomials (LG) of different order were fit to random effects. Modelfor bulls included direct additive genetic and animal permanent environmental effects, while in boars common litter environment, common pen environment, and maternal genetic effect were fitted additionally. LG with four coefficients were found sufficient in both species. Animal permanent environment accounted for 35 to 40 % of phenotypic variabilitry in boars, and between 30 and 55 % in bulls. Estimates of direct heritability in bulls were in the range 0.22 to 0.45, inm boars were around 0.40. Maternal heritability in boars decreased from 0.03 to 0.01. The proportion of common litter effect decreased over time (0.24 to 0.15), too. The eigenfunctions and corresponding eigenvalues in both species showed that around 85 to 90 % of the total geneticvariability was explained by the constant term in regression, while 10 to 15 % was genetic variability in the shape of growth curve. In bulls, a combined random regression and conventional multi-trait model for body weight (BW) and five single measured carcass traits was studied. Estimated genetic correlation over time between BW and warm carcass weight, conformation index, and ratio muscle:bone increased with time from +0.02 to +0.80 (+0.60), between BW and ratio of valuable cuts was close to zero the entire time. Changing the shape of growth curve by selection is possible, but not easy. Using the results of the combined random-regression and multiple-trait analysis in selection could be an advantage for carcass traits.
Author: Daniel Gianola
Publisher: Springer Science & Business Media
ISBN: 3642744877
Category : Technology & Engineering
Languages : en
Pages : 554
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Developments in statistics and computing as well as their application to genetic improvement of livestock gained momentum over the last 20 years. This text reviews and consolidates the statistical foundations of animal breeding. This text will prove useful as a reference source to animal breeders, quantitative geneticists and statisticians working in these areas. It will also serve as a text in graduate courses in animal breeding methodology with prerequisite courses in linear models, statistical inference and quantitative genetics.
Author: Taisiia Shabalina
Publisher:
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Category :
Languages : en
Pages :
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Author: Anil Sigdel
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Category :
Languages : en
Pages : 0
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This dissertation deals with the genetic and genomic analyses of fetal loss and stillbirth in dairy cattle. The first chapter focuses on the genetic analysis of fetal loss in dairy cattle. The genetic analysis was performed to unravel whether fetal loss is a heritable trait, and hence, whether it will respond to genetic selection, and to what extent current fertility traits, such as daughter pregnancy rate, heifer conception rate and cow conception rate currently included in national evaluations of US dairy cattle are associated with fetal loss. This study estimated that fetal loss is a heritable trait, and the magnitude of heritability estimates suggest an important scope for genetic selection. Additionally, fetal loss traits are weakly correlated with current fertility traits included in the national genetic evaluation and thus current selection and breeding efforts have little or no impact on reducing the incidences of fetal loss. The second chapter focuses on dissecting the genetic basis of fetal loss with an aim of finding and characterizing genomic regions, individual genes, and pathways responsible for the genetic variation of fetal loss trait in dairy cattle. Two complementary studies were performed, namely a whole-genome association study and a subsequent gene-set analysis. These studies identified genomic regions, and particularly individual genes and pathways responsible for pregnancy maintenance, placental development, and fetal growth. These findings contribute to a better, deeper understanding of the genetic architecture of fetal loss in dairy cattle and provide opportunities for improving pregnancy success in dairy cattle via marker-assisted selection. The third chapter aims to predict yet-to-be observed fetal loss phenotype in dairy cattle using dense SNP genotype information of cows, bulls, and embryo and considering the environmental effects, health history, and lactation performance. Phenotypic prediction of fetal loss was evaluated using alternative approaches, including kernel-based models in linear and threshold framework. These genomic prediction models could identify with reasonable accuracy the proportion of cows that had a high probability of maintaining a successful pregnancy or experience fetal loss to a given insemination. Overall, the implementation of these predictive tools will allow dairy farmers to make accurate genome-guided management decisions on reproductive management, mating, and culling. The fourth chapter deals with genetic evaluations of stillbirth for five US dairy breeds viz., Ayrshire, Guernsey, Milking Shorthorn, Brown Swiss, and Jersey. The fourth chapter has four primary tasks i) characterizing stillbirth data in terms of stillbirth rates and their distributions in five US dairy breeds ii) determining the extent to which stillbirth data were recorded in the national database iii) performing single-breed genetic evaluations using Sire-maternal grandsire model iv) determining the feasibility of routine genetic evaluations of stillbirth for these breeds, given the currently available stillbirth data. Our results based on available stillbirth data resources suggest that national genetic evaluations of stillbirth are feasible in Brown Swiss and Jersey. However, reliable genetic evaluations of stillbirth in Ayrshire, Guernsey, and Milking Shorthorn require further data reporting on stillbirth.
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Category :
Languages : en
Pages :
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The objectives of this research were to estimate heritabilities and correlations between body condition score (BCS) from various sources, determine the genetic relationship among BCS, dairy form, cow health and reproductive performance and investigate various models to analyze BCS and dairy form. BCS was obtained from herds using PCDART dairy management software and from linear type appraisals by Holstein classifiers. Cow health data was obtained from several herds recording disease treatments. Genetic evaluations for cow health in Denmark were also obtained. Reproductive data and yield data were provided by DRMS and AIPL-USDA. Heritabilities and correlations among traits were estimated with REML using animal and sire models. Random regression and repeatability sire models were compared. Fixed effects for all models included contemporary group effects, age, and days in milk (DIM) when available. Random effects were sire or animal and error. The heritability estimate of BCS from linear type appraisal was 0.22. The genetic correlation estimate between BCS from PCDART records and linear type appraisals was 0.87, between BCS and dairy form was -0.72 and between BCS and strength was 0.69. The genetic correlation estimates from random regression models between DIM 0 in lactation 1 and DIM 305 in lactation 3 were estimated to be 0.77 for BCS and 0.60 for dairy form. Higher BCS and lower dairy form were significantly correlated with lower milk yield, less metabolic disease and fewer days open. The relationship among BCS, dairy form, cow health and reproductive disease remained significant after adjustment for milk yield. The relationship between BCS and cow health and reproductive performance tended to be non-significant after adjustment for dairy form. Supplementing direct genetic evaluations for days open with evaluations for dairy form increased reliability of days open by an average of 0.06 for 19 recently proven bulls. Selection for lower dairy form or higher BCS will slow the deterioration of cow health and reproductive performance that accompanies selection for increased yield.
Author: Margaret Raab Dentine
Publisher:
ISBN:
Category :
Languages : en
Pages : 198
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