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Evaluating Sire Selection Practices Using Lifetime Net Income Functions

机译:使用终生净收入函数评估父系选择实践

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Dairy farmers do not take full advantage of opportunities available for genetic improvement through use of artificial insemination, perhaps because economic advantages of good sire selection may not be fully recognized or understood. This study was undertaken to document differences between use of AI and non-AI bulls and to develop prediction equations to compare lifetime economic merit of future progeny from alternative sire selection policies. We describe the use of two methods of measuring lifetime economic merit, with and without adjustment for opportunity cost of a postponed replacement. Comparison of lifetime relative net income adjusted for opportunity cost on groups of cows sired by different kinds of bulls showed that daughters of proven AI bulls generated $148 and $120 more lifetime net income under fluid and manufactured milk market conditions than daughters of non-AI bulls. Daughters of proven AI bulls produced $60 more than daughters of AI young sires in progeny testing programs at the time of daughter conception. We developed prediction equations from combinations of genetic evaluations for production, productive life, SCS, and linear type traits on sires to predict lifetime relative net income of progeny produced from alternative sire selection strategies. Prediction equations explained 14 to 18% of variation in relative net income (not adjusted for opportunity cost), but herd and year of first freshening accounted for considerably more variation than did genetic evaluations on the sire of the cow. Finally, two independent data sets were used to develop and test predictions of lifetime relative net income adjusted for opportunity cost using genetic evaluations based on the eight traits included in the Merit indexes for the sire of each cow. Prediction equations from odd numbered herds were used to predict lifetime economic merit in even numbered herds and vice versa. Coefficients of determination ranged from 0.088 to 0.103 and averaged 0.004 higher than prediction equations with Net or Fluid Merit. Accuracy of predictions showed that Net and Fluid Merit were robust and useful indexes that accurately identified bulls whose daughters generated highest lifetime economic merit.
机译:奶农没有充分利用通过人工授精进行遗传改良的机会,这可能是因为可能无法充分认识或理解优良种公选择的经济优势。进行这项研究是为了记录使用AI和非AI公牛之间的差异,并开发预测方程,以比较来自替代父系选择政策的后代的终生经济价值。我们描述了使用两种方法来衡量一生的经济价值,对延迟更换的机会成本有无调整。对因不同种类的公牛而生的成群母牛进行机会成本调整后的终生相对净收入的比较表明,在流动和人造牛奶市场条件下,经过证实的AI公牛的女儿比非AI公牛的女儿产生的终身净收入多了148美元和120美元。经过验证的AI公牛的女儿在后代测试计划中的生育能力比AI年轻公公的女儿高出60美元。我们通过对种公牛的生产,生产寿命,SCS和线性型性状进行遗传评估,从而开发了预测方程,以预测由其他种公牛选择策略产生的后代的终身相对净收入。预测方程式解释了相对净收入的14%至18%的变化(未根据机会成本进行调整),但是与牛的遗传评价相比,牛群和首次新鲜的年份所造成的变化要大得多。最后,使用两个独立的数据集来开发和测试基于机会成本调整后的终生相对净收入的预测,该预测是根据每头母牛的优异指数中包含的八个特征进行的遗传评估。来自奇数畜群的预测方程式用于预测偶数畜群的终生经济价值,反之亦然。测定系数的范围为0.088至0.103,平均比具有净值或流体值的预测方程式高0.004。预测的准确性表明,净资产价值和流动资产价值是稳健而有用的指标,可以准确地识别出其女儿产生终生最高经济价值的公牛。

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