| dc.contributor.author | CM Kariuki, ED Ilatsia, CB Wasike, IS Kosgey, AK Kahi | |
| dc.date.accessioned | 2020-08-28T07:26:26Z | |
| dc.date.available | 2020-08-28T07:26:26Z | |
| dc.date.issued | 2010-10-01 | |
| dc.identifier.uri | https://repository.maseno.ac.ke/handle/123456789/2502 | |
| dc.description | https://www.sciencedirect.com/science/article/abs/pii/S0921448810001616 | en_US |
| dc.description.abstract | Data consisting of 8922 weight records from 2642 Dorper sheep from 20 to 380 days of age spanning 1981–1996 were used to model the growth trajectory using random regression (RR) and estimate genetic parameters. The independent variables were orthogonal (Legendre) polynomials of age at weighing and orders of fit up to 3 were considered. Analyses were carried out fitting sets of RR coefficients due to direct and maternal additive genetic and environmental effects, and heterogeneous error variances. Direct additive genetic variance increased steadily along the trajectory from 0.9 at 20 days of age to 2.44 at 380 days of age. Maternal additive genetic variance increased steadily along the trajectory from 0.13 to 2.92. Direct permanent environmental effect variances increased steadily from a value of 0.66 at 20 days to 2.13 at 380 days of age. Maternal permanent environmental variances declined from 0.87 at … | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Covariance functionsDorper sheepGenetic parametersGrowthRandom regression model | en_US |
| dc.title | Genetic evaluation of growth of Dorper sheep in semi-arid Kenya using random regression models | en_US |
| dc.type | Article | en_US |
