Optimising Dairy Cattle Breeding Systems By Incorporating Reproductive Technologies, Protein Yield And Resistance To Mastitis

The objective of this study was to contribute to dairy cattle improvement in Kenya through optimization of breeding systems that incorporate reproductive technologies and milk quality traits in the dairy cattle breeding programme. Specifically, the study: 1) compared response to selection realized in a closed two-tier nucleus breeding system utilizing different reproductive technologies, 2) estimated the economic values for milk protein yield and mastitis resistance, and 3) compared response to selection realized in a closed two-tier nucleus breeding system utilizing the current and alternative breeding goal accounting for protein yield and mastitis resistance in dairy cattle in Kenya. The current breeding goal which does not account for milk quality traits such as for protein yield and mastitis resistance was considered as base scenario. Deterministic computer simulation programme ZPLAN was used to model and evaluate response to selection. The economic values for milk protein yield and mastitis resistance were estimated using bio-economic model and selection index methodology, respectively. Four strategies considered were Multiple ovulation and embryo transfer using conventional semen (MOET-CS) and X-sorted semen (MOET-XS) and Artificial Insemination using conventional semen (AI-CS) and X-sorted semen (AI-XS). The findings demonstrate that, reproductive technologies that increased reproductive rates of both males and females (MOET-CS) realized higher annual genetic gain and profit of KES 301.42 and 1,769.91 per cow per year, respectively compared to corresponding values of KES 143.97 and 992.84 for (AI-CS). The cost per cow per year for MOET-CS and MOET-XS, however, was 3.4 and 2.5 fold higher than those realized in AI-CS and AI-XS, respectively. Although the type of semen did not have an effect on annual genetic gain and return per cow when used with AI or MOET, they affected the costs and profitability per cow per year. The AI-XS and MOET-XS realized additional costs of KES 31.54 compared with AI-CS and MOET-CS strategies. The corresponding profitability per cow per year was therefore reduced by a similar amount. The economic values for PY and MR were KES 778.99 and -2,364.00, respectively. The alternative breeding goal outperformed the base scenario by KES 358.48 and 613.65 in annual genetic gain and profit per cow per year, respectively. This study has demonstrated that, adoption of reproductive technologies that increase reproductive rate of both males and females such as MOET- CS and incorporating milk quality traits in the breeding goal of dairy cattle optimize response to selection.