Determining the priority selection emphasis on characteristics in terms of optimized and non-optimized conditions of production system in dairy cows

The aim of this study is assessment of the priority selection emphasis on characteristics in terms of optimized and non-optimized conditions of production system in dairy cows. Optimization is the approach of finding the best accessible value of a predefined objective function within a determined range of effective variables. In optimized conditions for cow future profitability, the decision to cull cattle from herd is based on future predicted profitability of cows. Dynamic planning is an efficient mathematical method which is used to study and optimization of multi-stage decision problems. One of the main challenges in estimating economic value of characteristics is inefficiency of production system. In this study, in order to estimating the economic values and relative importance of characteristics in efficient and inefficient conditions of production system, the average data of six Holstein herds was used which is recorded under supervision of breeding center. After optimizing production system for culling and replacement policies in the herd, a unit is added to the considered characteristic average in order to calculate the economic value of a characteristic after this changes, the production system optimized. The current value of the system calculated in optimized condition before and after changing characteristic and economic value of characteristics obtained from their difference. Relative importance of characteristics such as calving interval, milk production, milk fat, birth weight, mature live weight, increasing daily weight pre-weaning, increasing daily weight after weaning and the first calving age in non-optimized condition of production system are estimated respectively 2.06, 95.62, -4.34, -0.64, 1.90, 1.25, 1.93 and 2.22 percent and In optimized condition of production system are 0.42, 92.55, -0.642, 0.32, 2.00, 1.15, 1.81 and 2.37 percent respectively.