Defining goal and breeding strategy for Sangsari sheep.

The aim of this studywere to estimate (co) variance components and genetic parameters forgrowth andreproductivetraits, evaluation of the genetic trends and defining goal and breeding strategy for Sangsari sheep. (Co)variance components and genetic parameters for production and reproduction traits were estimated using animal model analysis with REML procedure.4 flocks with 756 breeding ewes in extensive production system maintained in Semnan province were used to determine breeding objectives and relative economic values. 4 selection indices with different combination of greasy fleece weight, total weight of lambs weaned per ewe exposed and the ewe weight were studied. Stochastic simulation was used to produce flocks with the size of 100 to 300 breeding ewes.With changes in the percent of breeding rams from 2 to 4, 6 and 8% as well as change in components of selection index, the inbreeding level and genetic gain during a 10 years period based on the fitted selection index were studied. Estimates of direct heritability for growth traits were in the range between 0.17 (Kleiber ratio at 6 months of age) to 0.50 (pre-weaning average daily gain). Heritability of reproductive traits wasgenerally low,in most cases below 0.10. Genetic rends showed genetic improvement in some growth traits. Relative economic valuebased on maximum profit approach was maximum for selling lambs (26.23) and minimum for ewe weight (-8.48). With the increase in the flock size, the level of inbreeding decreased but the genetic gain and the profitability increased.In contrast, with increase in the number of breeding rams, the level of inbreeding decreased but the genetic gain and the profitability decreased. Considering the results, the full selection index )I1) which included greasy fleece weight, total weight of lambs weaned per ewe exposed and the ewe weight was suggested as the suitable selection index for Sangsari sheep. Keywords: Sheep, Genetic parameters, Economic weight, Selection index