DEVELOPING BREEDING STRATEGIES FOR BEGAIT CATTLE GENETIC IMPROVEMENT IN NORTHERN ETHIOPIA

Abstract

This study was conducted with the objective to describe production system, evaluate performance, identify preferable traits and evaluate their economic values, and to optimize alternative breeding strategies to increase productivity of Begait cattle. Data were collected using semi-structured questioner from 30 small-scale and 15 large-scale households each in four selected rural kebeles of Kafta-Humera district. Reproductive and productive performances were studied under low input herd management system (LIHM) and medium input herd management system (MIHM). Preferable traits of farmers were identified using choice experiment. Hundred twenty households from each small-scale and large-scale farm were used to apply choice experiment. The economic values (EV) of the identified breeding-objective traits were evaluated using bio-economic model based on fixed herd size. Production systems were described according to their level of input and sale age. Finally, alternative breeding schemes were optimized using a deterministic approach (ZPLAN). Natural service (NS)-based, artificial insemination (AI)-based and combination of AI and NS central nucleus breeding schemes were simulated and evaluated for their relative annual genetic gain (AGG) and profit. Results showed that households considered income generation, calf production and milk for home consumption as the major purpose of keeping Begait cattle across production systems. The mean livestock holding sizes for small-scale farms were 19, 26, 18, 8 and 1 for cattle, sheep, goats, chicken and donkey, respectively. The corresponding values for large-scale farms were 86, 41, 30, 10 and 2. Except bull maturity, production system had significant (P<0.05) influence on other traits. Large-scale farmers recorded shorter calving interval (CI) (12.0 vs 14.8 months), reduced age at first calving (AFC) (37.6 vs 44.5 months) and higher daily milk yield (DMY) (4.4 vs 3.7 kg) than small-scale farmers. Farmers mentioned theft, feed shortage, water scarcity and disease as major constraints to livestock production. The MIHM achieved 232 and 385 g/day calf growth improvements over LIHM (398 and 184 g/day gain) from birth to 9 months (Gain1) and from 9 to 12 months (Gain2), respectively. The MIHM recorded lower CI (419 days) and AFC (863 days) and higher daily milk yield (6.5 kg) and lactation milk yield (1630 kg) as compared to xii LIHM. Cows calved in the dry season had 77 days longer in CI and 93 kg reduced LMY than those cows calved in the wet season. Production system had no significant (P>0.05) influence on cattle trait preferences. Across production system, short CI, reduced AFC, good body conformation, big body size and mixed coat colors were the most preferable traits for selecting breeding cow. For bull, high libido, aggressive temperament, good body conformation, big body size and mixed coat color were recognized as vital selection criteria. Attribute levels related to higher milk yield ranked below the medium level due to shortage of demand for fresh milk. Except pre-weaning average daily gain (PrADG), all traits have positive economic values across production systems. However, production system had significant influence on the magnitude of EV of traits. MIHM was superior by 9-100% over LIHM. A 1-10% increase in EV of MY traits due to a rise in milk price, reduction in weaning rate and reduced culling rate by 10% resulted in 1-12% increment in profit. However, beef traits only made 5.1×10-7 to 2.3×10-6% increases of profits with 18-50% increment in its EV by beef price increment and reduced age at first calving. Conversely, when increasing the weaning rate and culling rates by 10%, the economic values of PsADG, MWT and DP increased by 11-23% across production system, while the profit reduced by 1-6%. AI-based breeding schemes gave 47-90% more AGG and 79-128% more profit over NS-based breeding schemes. Inclusion of multiplier unit for two tier NS-based breeding scheme improved profit by 10% due to reduction in costs by 68%. However, in the AI-based breeding schemes, the two tier breeding scheme achieved better improvements of AGG (29%) and profit (15%) over three tier AI-based breeding scheme. In conclusion, Begait cattle farmers have relatively specific breeding objective traits, higher herd size and owned cattle with higher productivity compared to many indigenous cattle breeds in Ethiopia. Non-genetic factors (herd management) had major influences on growth, milk production and reproductive traits of Begait cattle. Farmers have similar trait preferences for selecting breeding bull and cow across production systems. Milk yield traits have higher marginal profit than beef production traits. Adoption of two tier AI-based breeding scheme is better for faster genetic gain and higher profit. Thus, the observed breeding objective traits, productivity parameters and their major factors, and simulated alternative breeding schemes, presented here could be used as reliable benchmark for the anticipated Begait cattle improvement program.