Biomaterial Database

Estimates of (co)variance components and genetic parameters for growth traits in Sirohi goat. 2011

Gopal R Gowane, and Ashish Chopra, and Ved Prakash, and A L Arora

Animal Genetics and Breeding Division, Central Sheep and Wool Research Institute, Avikanagar-304501, via- Jaipur, Rajasthan, India. gopalgowane@gmail.com

Data were collected over a period of 21 years (1988-2008) to estimate (co)variance components for birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), weaning to 6WT (ADG2), and from 6WT to 12WT (ADG3) in Sirohi goats maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India. Analyses were carried out by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. The best model was chosen after testing the improvement of the log-likelihood values. Heritability estimates for BWT, WWT, 6WT, 9WT, 12WT, ADG1, ADG2, and ADG3 were 0.39 ± 0.05, 0.09 ± 0.03, 0.06 ± 0.02, 0.09 ± 0.03, 0.11 ± 0.03, 0.10 ± 0.3, 0.04 ± 0.02, and 0.01 ± 0.01, respectively. For BWT and ADG1, only direct effects were significant. Estimate of maternal permanent environmental effect were important for body weights from weaning to 12WT and also for ADG2 and ADG3. However, direct maternal effects were not significant throughout. Estimate of c (2) were 0.06 ± 0.02, 0.03 ± 0.02, 0.06 ± 0.02, 0.05 ± 0.02, 0.02 ± 0.02, and 0.02 ± 0.02 for 3WT, 6WT, 9WT, 12WT, ADG2, and ADG3, respectively. The estimated repeatabilities across years of ewe effects on kid body weights were 0.10, 0.08, 0.05, 0.08, and 0.08 at birth, weaning, 6, 9, and 12 months of age, respectively. Results suggest possibility of modest rate of genetic progress for body weight traits and ADG1 through selection, whereas only slow progress will be possible for post-weaning gain. Genetic and phenotypic correlations between body weight traits were high and positive. High genetic correlation between 6WT and 9WT suggests that selection of animals at 6 months can be carried out instead of present practice of selection at 9 months.

UI	MeSH Term	Description	Entries
D007194	India	A country in southern Asia, bordering the Arabian Sea and the Bay of Bengal, between Burma and Pakistan. The capitol is New Delhi.	Republic of India
D001835	Body Weight	The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.	Body Weights,Weight, Body,Weights, Body
D001947	Breeding	The production of offspring by selective mating or HYBRIDIZATION, GENETIC in animals or plants.	Breedings
D006041	Goats	Any of numerous agile, hollow-horned RUMINANTS of the genus Capra, in the family Bovidae, closely related to the SHEEP.	Capra,Capras,Goat
D000367	Age Factors	Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.	Age Reporting,Age Factor,Factor, Age,Factors, Age
D000704	Analysis of Variance	A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.	ANOVA,Analysis, Variance,Variance Analysis,Analyses, Variance,Variance Analyses
D000818	Animals	Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA.	Animal,Metazoa,Animalia
D012641	Selection, Genetic	Differential and non-random reproduction of different genotypes, operating to alter the gene frequencies within a population.	Natural Selection,Genetic Selection,Selection, Natural
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016013	Likelihood Functions	Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.	Likelihood Ratio Test,Maximum Likelihood Estimates,Estimate, Maximum Likelihood,Estimates, Maximum Likelihood,Function, Likelihood,Functions, Likelihood,Likelihood Function,Maximum Likelihood Estimate,Test, Likelihood Ratio