MULATU GOBEZE ALAMIREW2026-02-042022https://etd.hu.edu.et/handle/123456789/640Community-based breeding programs (CBBPs) are currently proved as one of the approaches used for small ruminants’ genetic improvement in developing countries, particularly in Ethiopia. This study was conducted to evaluate the overall performance of the ongoing Abergelle goat community-based breeding program using technical and socio-economic criteria. On-farm biological performance data was collected from 2013-2019. Survey data was collected using semi-structured questionnaire interviews, focus group discussions and key informant interviews. Growth, reproduction and milk production performance data was analyzed using generalized linear model (GLM) procedure of the Statistical Analysis System (SAS, version 9.0) software. The genetic parameters for the breeding objective traits were estimated by the Restricted Maximum Likelihood method (REML) of WOMBAT software fitting different single-trait animal models. Six single-trait animal models for growth performance and two each for reproductive and milk production traits were fitted for genetic parameters estimation. Best model was selected using log likelihood ratio test. The genetic trend was estimated by the weighted regression of the average breeding value of the animals on the year of birth for each targeted trait. Random assignment of a single buck for the paternal pedigree line was used in the genetic evaluation process as the pedigree data structure in this study was obtained from multiple sires joining. Genetic and phenotypic correlations were estimated fitting multivariate animal models. Socio economic data was analyzed using descriptive statistics in addition to direct narrations from formal and informal discussions. The overall least squares mean body weight at birth (BWt), three-month (TMWt), six-month (SMWt), nine-month (NMWt) and at yearling age (YWt) were 2.18±0.01, 7.27±0.03, 9.22±0.04, 12.16±0.04, and 15.56±0.10 kg, respectively. Location, sex of kid, birth type, season of birth, year of birth and parity of the dam were the important sources of variation for most of the growth performance traits (P<0.05). The average daily weight gain from birth to weaning (ADG1), weaning to six- month (ADG2), six to nine month (ADG3) and nine month to yearling age (ADG4) were 55.93±0.30, 21.59±0.29, 32.67±0.43, and 39.48±0.90 g/day, respectively. The overall least-squares mean of reproductive traits for litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB), litter weight at weaning (LWW), and kidding interval (KI) were 1.04±0.00 kids, 0.99±0.01 kid, 3.18±0.01kg, 11.24±0.04kg, and 356.05±1.68 days, respectively. In addition, the overall least-squares means of milk production traits found in this study for average daily milk yield (ADMY), lactation length (LL), and ninety day milk yield (MY90D) were 410 ±2.11 ml, 72.44±28 days, and 36.92±0.19 liter, respectively. Site, season of kidding, year of kidding and parity of the dam were the most important traits affecting most of the reproductive and milk production performance traits. The total heritability (h2 t) estimates for weight at different ages were in the range of 0.28 to 0.40 at Bilaque site while 0.15 to 0.38 at Saziba site from selected models, respectively. Heritability estimates were in the rage of, 0.03±0.19 to 0.13±0.08 for reproductive traits and total heritability estimates for milk production traits were in the range of 0.05 to 0.20. The genetic correlations for growth traits ranged from 0.04 (BWt-NMWt) to 0.85 (TMWt-SMWt) but it was higher than the phenotypic correlation values. Genetic trend values were positive (P<0.05) for growth traits except BWt, no change (P>0.05) for reproductive traits and moderately higher (P<0.05) for milk production traits. The mean flock size of cooperative members was increased by more than 37% while reduced by 20% for non-members during the program implementation period. Even though the cooperatives build relatively strong institutional and financial capacity in the short run, they still require sustainable technical and financial support to run the breeding program. In the future, optimizing genetic evaluation methods like considering uncertain sire, economic selection index and improving mating ratio are suggested for maximizing overall benefit of the breeding program. Improving feeding and overall management assisted with strong reproductive biotechnology tools like estrus synchronization and artificial insemination are suggested for improving reproduction traits.en-USAbergelle goatCBBPgrowth traitsmilk productiongenetic parametersThesis