Genetic analysis of body weight and growth curve parameters in Muzaffarnagari sheep of India

Abstract The objective of this study was to estimate genetic effects on parameters of the Brody and Richards growth curves using body weight records from birth to 12 months of age on 2287 Muzaffarnagari lamb for a period of 29 years (1976–2004). Estimated growth curve parameters were analysed using six univariate animal models, and genetic correlations among and between the parameters of each function and between parameters of the functions and observed birth and yearling weights were estimated using bivariate analyses. Significant environmental factors including birth year, sex, season, birth status and dam parity were included as fixed effects in all models. Likelihood ratio tests indicated that maternal genetic effects were significant only for birth weight (BW) and degree of maturity at birth ( u 0 ) for the Brody and Richards functions. For these traits, direct heritabilities were similar (0.21, 0.19 and 0.17, respectively), but the estimated maternal heritability for BW (0.18) was twice that of u 0 for both functions. Heritabilites for yearling weight and asymptotic final body weights for the Brody and Richards functions were 0.28, 0.17 and 0.21, respectively. The remaining growth curve parameters were lowly heritable, ranging from zero for the predicted degree of maturity at the age of maximum growth rate for the Richards function to 0.08 for the maturing rate parameter of the Brody function. Genetic correlations between corresponding parameters for different growth functions exceeded 0.88. Our results showed that the Brody and Richards functions had similar genetic architecture, but the Richards function had no apparent advantages over the more easily interpreted Brody function. Failure to identify maternal genetic effects on maturing rate parameters suggested that both functions failed to identify potentially important maternal genetic effects. Therefore, there is no usefulness of estimated growth curve parameters in selection compared to the simple multi‐trait genetic evaluations of individual body weights.