Abstract

Breeding objectives are designed to achieve targeted dairy cow production goals, which can be affected by production type, farmer preferences, environmental factors and genetic factors individually or in combination. Breeding practices, such as both controlled and uncontrolled, and artificial insemination (AI) are the tools used to obtain the desired breeding objectives. The lower reproductive performance of indigenous dairy cows affects the total milk production and calf crops that are produced during their lifetime. Designing appropriate breeding objectives and breeding practices can improve the reproductive performance of dairy cows and their overall production performance. The current study was conducted with the objective of evaluating the breeding, practices and performance of indigenous dairy cattle in the south western part of Ethiopia. The districts of Gesha and Chena were purposefully chosen. The study design for the 384 household surveys was a cross-sectional survey with a simple random sample approach. Data analysis was carried out by MS-Excel (2010) and the general linear model procedure of SAS of 2008. The current study revealed that methods of breeding were predominantly natural-controlled mating, followed by natural-uncontrolled mating and AI in descending order. Breeding objectives were input function, output function, sociocultural and economic functions and assets and security functions in decreasing order of rank. Reproduction performance indexes of indigenous dairy cows age at first service (3.72±0.05 years), age at first calving (AFC) (4.71±0.07 years), calving interval (CI) (1.58±0.03 years), days open (DO) (4.26±0.11 months), services per conception in natural mating (1.4±0.08) and AI (2.73±0.14), age of bull at maturity (4.17±0.74 years), interoestrus interval (23.18±0.61 days), calves crop (7.53±0.22) and the life span of indigenous dairy cow (11.94±0.26 years) were significant (p<0.01) between two districts, whereas the values of age of bull at maturity and number of services per conception in natural mating were significant (p<0.05) between districts. Using AI and major reproduction performances, such as AFC, CI and DO of indigenous dairy cows in the study area, were very low. Therefore, concerned bodies should intervene to improve reproduction performance through the utilization of AI techniques, with the integration of forage development activities and improvements in livestock health care.

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