Selection response from a two-tier nucleus breeding scheme using the current Kenyan breeding goal was compared with an alternative that also accounts for protein yield (PY) and mastitis resistance (MR). The economic value for PY was estimated using a bio-economic model. For mastitis resistance, like other disease resistance traits, the economic value cannot be estimated with profit equations because they have multi-fold effects on input and output, which affects profitability. Therefore, selection index methodology was used. Somatic cell count (SCC) was used as an indicator trait for MR. The ZPAN computer program was used to model the breeding schemes and evaluate response to selection. The alternative breeding goal, which included PY and MR, realized additional KES358.48, 613.55, and 613.65 in annual genetic gain, returns and profit per cow per year, respectively, compared with the current breeding goal. Economic values for PY and MR were KES778.99 and -2364, respectively. Relative economic values for milk yield (MY, kg), fat yield (FY, kg), protein yield (PY, kg), MR, calving interval (CI, days), preweaning daily gain (DG, g/day), postweaning daily gain (PDG, g/day), live weight (LW, kg), preweaning survival (SR1, %), postweaning survival (SR2, %), and length of productive life (PLT, days) were 23 689.80, 4 146.77, 34 665.50, -992.88, 33.66, 62.40, 159.80, 391.94, 987.04, 4 474.37, and 7.56, respectively. This implies that including milk quality traits such as PY in the breeding goal would optimize response to selection in dairy cattle production. Keywords: breeding objective, economic values, genetic evaluation, milk quality, traits, udder health
It was reasoned that technologies that increase the reproductive rate of males and females in dairy cattle would realize higher responses to selection. The authors tested this hypothesis using deterministic simulation of breeding schemes that resembled those of dairy cattle in Kenya. The response to selection was estimated for four breeding schemes and strategies. Two breeding schemes were simulated, based on artificial insemination (AI) and multiple ovulation and embryo transfer (MOET) reproductive technologies. The strategies were defined according to the use of conventional semen (CS) and X-chromosome-sorted semen (XS). The four strategies therefore were AI with CS (AI-CS) and XS (AI-XS), and MOET with CS (MOET-CS) and XS (MOET-XS). The four strategies were simulated based on the current dairy cattle breeding goal in Kenya. A two-tier closed nucleus breeding programme was considered, with 5% of the cows in the nucleus and 95% in the commercial. Dissemination of superior genetic materials in the nucleus was based on all four breeding strategies, while in the commercial only the AI-CS strategy was considered. The strategies that increased the reproductive rates of both males and females (MOET-CS and MOET-XS) realized 2.1, 1.4, and 1.3 times more annual genetic gain, return and profitability per cow, per year, respectively, than strategies that increased the reproductive rates only of males (AI-CS and AI-XS). The use of CS or XS, however, did not affect response to selection in the two schemes. The findings demonstrate that reproductive technologies such as MOET maximize response to selection in dairy cattle breeding. ______________________________________________________________________________________
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