Community-based sheep breeding programs (CBBPs) have been adopted strategically to improve Bonga sheep, the most popular sheep breed in Ethiopia. The present study was undertaken to estimate genetic parameters and genetic trends for growth traits and inbreeding levels in each Bonga sheep CBBP. Data pertaining to growth traits, spanning a period of seven years (2012-2017), were collected from 14 Bonga sheep CBBPs. Data were analyzed using the General Linear Model procedure of SAS to study the performance of the breed over the years. The genetic parameters were estimated by univariate and multivariate animal model using restricted maximum likelihood method of WOMBAT software. The genetic trends were estimated by the regression of the average breeding values of the animals on the year of birth. The overall least square means ± SE of BW (kg) were 3.10 ± 0.010, 16.1 ± 0.07, 24.7 ± 0.20, 30.4 ± 0.40 and 34.0 ± 0.84 for birth weight (BWT), weaning weight (WWT), six-month weight (SMWT), nine-month weight (NMWT) and yearling weight (YWT), respectively. Direct heritability estimates from selected models were 0.56 ± 0.030, 0.36 ± 0.030, 0.22 ± 0.040, 0.17 ± 0.070 and 0.13 ± 0.150 for BWT, WWT, SMWT, NMWT and YWT, respectively. Six-month weight was the selection trait and presented positive trends for 10 CBBPs, and negative trends for four CBBPs. Moderate to high heritability estimates and positive genetic trends indicated scope for further improvement of BW. Additionally, the positive and high correlation between BW traits indicated that selection for just one trait would also improve the other traits through correlated responses.

Objective: The objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep.Methods: Reproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/ lambing.Results: The overall least squares mean±standard error of AFL, LI, LS, and ARR were 375± 12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were –0.0281 days, –0.016 days, –0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively.Conclusion: Implications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

This study aimed to identify key morphometric predictors of body weight in local ducks and assess their genetic diversity to inform breeding programs in southeastern Nigeria. A total of 200 ducks (100 from each of the states of Abia and Imo) were measured for 10 morphometric traits to evaluate their relationship with body weight. Principal Component Analysis (PCA) revealed five distinct clusters within the duck population, with Cluster 1 showing the lowest and Cluster 5 the highest average body weights. Hierarchical clustering corroborated these groupings. Correlation analysis identified body circumference (BDC) as the most reliable predictor of body weight (r=0.76). Gender-specific trends were also observed: shank length (SHL) had a positive correlation with females (r=0.65), while neck length (NKL) was more strongly correlated with males (r=0.72). The strongest overall correlation was between body weight and body circumference, modelled by the equation BDW = 2401.41 + 122.04 × BDC (R²=0.84, r=0.91). For genetic diversity assessment, 40 blood samples (20 from each state) were collected from randomly selected, unrelated ducks. DNA was extracted, amplified using PCR, and sequenced, revealing two single-nucleotide polymorphisms (SNPs): C→A and A→G substitutions. This led to the identification of two homozygous (CC, AA) and two heterozygous (CA, AG) genotypes, along with four haplotypes and 133 polymorphic sites. The haplotype diversity was 1.000, and nucleotide diversity averaged 0.606%. These findings demonstrate that integrating morphometric and molecular analyses provides a robust framework for characterizing local duck populations. This dual approach supports the development of informed breeding strategies to enhance productivity, particularly in resource-limited settings.