Multivariate Animal Model-based Analysis of Fiber Traits in Kashmir Merino Sheep

Abstract

ABSTRACT An attempt was made in the present study to elucidate the (co)variance components and genetic parameters of fiber traits in Kashmir Merino sheep population using multivariate animal model. The data pertained to a total of 6836 sheep lambs born over a period of 21 years (1997–2017) and included information on different fiber traits [greasy fleece weight at first (GFW1) and second (GFW2) clips; and fiber diameter (FD) and staple length (SL) at second clip]. Genetic analysis was undertaken using average information restricted maximum likelihood (AI-REML) algorithm in WOMBAT program. The model incorporated six fixed (sex of lamb, season and period of birth, farm of origin, breed and type of birth) and two random effects (direct additive genetic and maternal genetic effects without any covariance between them) in it. The additive genetic heritability estimates for fiber traits were 0.300 ± 0.031; 0.289 ± 0.022; 0.254 ± 0.029 and 0.189 ± 0.028 for GFW1, GFW2, FD, and SL, respectively. The maternal genetic heritability estimates were very low for all traits under study. The genetic correlation between different traits was positive and estimates ranged from moderate to high. The results from present study imply that the variation in these traits has genetic basis which can be exploited in the selection programmes for their improvement. The correlation between different fiber traits was found to be favorable, which can lead to indirect selection response upon formulation of efficient breeding programmes.