Genetic variation of lactation curves in dairy sheep: a Bayesian analysis of Wood’s function

Abstract

Test-day milk yield records (1752) of 451 first-lactation ewes in four flocks from Nebraska and Wisconsin were analyzed. Breeds included crosses among Dorset, Romanov, Targhee, Rideau Arcott, Polypay, Booroola Merino, Suffolk, Rambouillet, Finnsheep and East Friesian. The objective was to investigate genetic variation of features of lactation curves using a three-stage Bayesian hierarchy. Wood’s model, E( y | a, b, c, t)= at b exp(− ct), was used as first-stage; a indicates level of starting yield, and parameters b and c describe ascending and descending phases of the lactation curve; t is time. The second-stage model described variation between ewes. It had a linear structure including flock-year, age at lambing, type of lambing, length of suckling period and the expected percentage of genes of East Friesian origin as fixed effects, plus random additive genetic effects. The third stage included prior distributions for all unknown parameters. Gibbs sampling and the Metropolis–Hastings (MH) algorithm were employed for drawing samples from posterior distributions of parameters. A chain of 60 000 iterations (burn-in of 11 000) was used. Acceptance rate with MH was 24%. Residual variance (posterior mean) was 0.042 kg 2. Posterior means of heritability of a, b and c were 0.35, 0.35 and 0.27, respectively. Estimates indicate that part of the variation in lactation curves between ewes is heritable. Genetic correlations were negligible, suggesting flexible scope for modifying lactation curves via genetic selection