Factors affecting birth weight and pre-weaning growth rate of lambs from the Icelandic sheep breed

In Iceland, the sheep production year is characterized by lambing in May, weaning and slaughtering in September and October. Our hypothesis is that modelling interrelationships of production parameters will aid in controlling variation in important outputs like weaning weight. We analyzed data from twelve production years in our experimental farm with total records of 9661lambs born to 1847 dams. In the whole dataset, 7.4 % of the lambs were born as singles, 78.1 % as twins, 13.7 % as triplets and 0.8 % as quads. Surrogate mothers fostered 5.5 % of the lambs. We fitted multilevel models to data on lamb weight at birth, at 50.9 ± 8.6 days and at weaning at 140.7 ± 8.3 days of age, and to the respective lamb growth rates. Ewe was included as a random effect in the model. Fixed group effects that significantly influenced birth weight were (presented as least square means, kg): litter size (singles 4.60; twins 4.01; triplets 3.35; quads 3.02), lamb sex (male 3.84; female 3.65), dam age (lowest for 2 year old dams), and production year (3.68–3.84). The model describing birth weight, also included positive linear relationships with ewe weight in the first month of pregnancy, ewe weight gain from first to third month of pregnancy, and a second degree relationship with body condition score (BCS) in third month of pregnancy. Fixed group effects significantly influencing growth rate from birth to weaning at 4–5 months of age were: rearing type (as singles 264.0; as twins 235.9 g d⁻¹); lamb sex (males 263.6; females 237.4 g d⁻¹), dam age (growth rate highest for 3 and 4 year old dams), production year (238.8 to 262.5 g d⁻¹), time of weaning (late October 240.0; late September 254.5 g d⁻¹). There were also positive linear relationships with lamb birth weight, ewe weight in third month of pregnancy, and BCS in last month of pregnancy. In conclusion, multilevel models on lamb birth weight and growth rate provide an opportunity to predict and control the variability in lamb weaning weight.