Estimates of genetic parameters for milk yield and reproductive traits in crossbreed dairy cattle at the Holeta Agricultural Research Center, Ethiopia
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The objective of this study was to estimate genetic parameters for production (milk yield) and reproduction traits in a dairy cattle breed at the Holeta Agricultural Research Center. The analysis utilized extensive records covering 13,116 observations collected over a 30-year period (1995 to 2024). The genetic parameters for milk yield and reproductive traits were estimated using WOMBAT software via multivariate analysis. The heritability estimates for lactation yield traits (LMY, DMY, and LL) were 0.180 ± 1.00, 0.235 ± 0.053, and 0.219 ± 0.077, respectively, and for reproductive traits (AFS, AFC, and CI) 0.0798 ± 0.034, 0.080 ± 0.033, and 0.180 ± 0.042, respectively. The results indicated that repeatability values of lactation yield traits were 0.589 ± 1.00 for LMY, 0.491 ± 0.227 for DMY, 0.735 ± 0.151 for LL, and 0.23 ± 0.01 for CI. The study also found positive direct genetic correlations between lactation yield traits, ranging from very weak (0.141 ± 0.073) to very strong (0.854 ± 0.304) genetic correlations. High correlation was observed between LMY and LL (0.854 ± 0.304). Positive genetic correlations ranging from very weak to weak were found among reproductive traits. AFS-AFC (0.228 ± 0.172),AFS-CI (0.181 ± 0.194), AFC-CI (0.063 ± 0.02). The study indicated that the genetic correlation among lactation yield and reproductive traits was closely related in some traits. Strong genetic correlation was found between CI-LL (0.785 ± 0.074), moderate genetic correlation between CI-LMY and AFC-LL (0.428 ± 0.098, and 0.40 ± 0.107), respectively. The low to moderate heritability estimates suggest that mass selection alone may be slow, and proper management plays a significant role in improving these traits. The favorable genetic correlations found indicate that selection for certain milk yield traits (like LMY or LL) could also lead to a positive correlated response in reproductive efficiency (e.g., shorter CI). Knowing these genetic parameters is crucial for designing effective breeding programs that prioritize traits showing high favorable correlations for overall animal performance improvement.