College of Agriculture

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The College of Agriculture is committed to advancing agricultural education, research, and community service. It serves as a center for knowledge creation and dissemination in crop science, animal production, natural resource management, and sustainable agriculture.

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    EVALUATION OF COMMUNITY-BASED ABERGELLE GOAT BREEDING PROGRAM IN WAGHIMRA ZONE, AMHARA REGIONAL STATE, ETHIOPIA
    (Hawassa University College of Agriculture, 2022) MULATU GOBEZE ALAMIREW
    Community-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.
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    PERFORMANCE EVALUATION AND SCALING OPTIONS FOR DOYOGENA SHEEP COMMUNITY-BASED BREEDING PROGRAM IN CENTRAL ETHIOPIA
    (Hawassa University College of Agriculture, 2025) ADDISU JIMMA FALITA
    ABSTRACT The studies were carried out to: (1) explore genetic parameters for growth, reproductive, and survival traits; (2) asses morphological changes in the animals and socioeconomic benefits to the community, and describe the flock dynamics of Doyogena sheep; and (3) develop and compare effective scaling options for Doyogena Community Based Breeding Program (CBBP). Data were collected over ten years (2013–2022) on the following traits: birth weight (BWT), weaning weight (WWT), six months weight (SMW), annual reproductive rate (ARR), lambing interval (LI), lambing interval (LI), litter weights and sizes at birth (LWB, LSB) and weaning (LWW, LSW), ewe post-partum weight (EPPW), pre-weaning lamb survival (PWLS), and lamb survival up to six months (LSSM). Variance components and genetic parameters were investigated using the average information-restricted maximum likelihood algorithm were applied in a multivariate mixed model. The WOMBAT and DMU software was used for analyses. A survey of 260 farmers (130 CBBP members, 130 non-members) captured perceptions and flock data. Five scaling strategies were modeled using gene flow method, assuming a nucleus and production unit structure. Results indicated that the Additive heritability estimates were 0.37 (BWT), 0.26 (WWT), 0.21 (SMW), 0.10 (LSB), 0.24 (LWB), 0.03 (LSW), and 0.22 (LWW). For LI, ARR, EPPW, PWLS, and LSSM, estimates were 0.15, 0.12, 0.14, 0.10, and 0.08, respectively. Most performance traits showed positive and significant (P < 0.001) annual genetic trends. Positive and low to moderate genetic correlations were observed between growth traits (WWT, SMW) and most reproduction and lamb survival traits. CBBP members had significantly (p<0.05) larger flock size, with more lambs under 3 months, male lambs (3-6 months), intact males (6-12 months), breeding rams, and mature ewes. The primary routes of sheep entry into flocks were birth (81%), and purchase (17%). The total number of entries (284 vs. 240) and births (148 vs. 112) was higher (p<0.05) for CBBP members than non-members. The offtake-rate, representing the proportion of sheep exiting the flock was also significantly higher (p<0.05) for CBBP members (36.45%) than non-members (17.35%). The CBBP was attributed to performance improvements in traits such as growth, coat color, litter size, survival, and lambing interval. Among scaling options, strategy 3 showed the highest return on investment (ROI) at the xvii production unit level ($122), while Strategy 5 showed the highest nucleus ROI ($8.5) and the greatest accumulated discounted benefits (nucleus: $62,847; production: $353,757). The highest genetic progress at the nucleus level was achieved with strategy 4 (27.88 kg), where a proportion of sires were produced through AI (Artificial Insemination). Strategy 2 and 5 also outperformed the baseline strategy 1 at SMW trait levels, indicating that increasing the number of breeding females and retaining all candidates has a positive effect. Although strategy 3 did not achieve the highest genetic gains, it delivered a competitive nucleus trait level (SMW=26.00 kg) while maximizing dissemination, leading to exceptional economic outcomes. The AI-based strategies (strategies 4 and 5) produced higher SMW, but their economic returns varied. The medium heritability and moderate correlations between growth and litter weight traits (LWB and LWW) suggest the importance of considering litter weight in addition to growth traits in selection processes. The CBBP was effective and well-accepted by participants. Scaling up is recommended to benefit more farmers. The AI integration scaling strategy can accelerate genetic progress, optimal economic outcomes depend on effective candidate retention, dissemination strategies, and aligning breeding strategies with operational capacity. Policymakers and practitioners should tailor adoption strategies to their specific genetic improvement targets, financial constraints, and infrastructural readiness to ensure that both genetic and economic goals are met sustainably.