MARATTO

preprint

Estimation of genetic and phenotypic parameters for milk production and reproduction traits in a developing synthetic dairy cattle breed at Holeta Agricultural Research Center, Ethiopia

2026Open accessHawassa University

Abstract

<title>Abstract</title> This study was carried out to estimate genetic and phenotypic parameters for milk production and reproduction traits of synthetic dairy cattle breed development program being implemented at Holeta research center dairy farm. Data collected from 1995 through 2024 on lactation milk yield, lactation length ,daily milk yield, age at first service, age at first calving, and calving intervals from experiments targeted at developing a synthetic breed at the Holeta Agricultural Research Center dairy herd were used for this study. The GLM procedures of SAS software were used to estimate the effect of fixed effects such as year, season and parity while regression analysis was performed to estimate crossbreeding parameters (additive, heterosis and recombination effects). Genetic components, including variance covariance estimates were analyzed using WOMBAT software. A univariate mixed model for genetic parameters and Multiple Regression Model for crossbreeding parameters was used for data analysis. The performance of dairy cattle affected by genetic and non-genetic factors. The result of fixed effects (year and genetic group) analysis showed that significant (p&lt;0.0001) differences in all productive and reproductive traits. Correspondingly, productive traits (LMY and DMY) and reproductive (CI) traits were also significantly (p&lt;0.0001) influenced by parity. The traits, lactation and milk yield, were sensitive to seasonal variation. The overall least square means for lactation milk yield (LMY), daily milk yield (DMY), lactation length (LL), age at first service (AFS), age at first calving (AFC), and calving interval(CI)were 2140.61 ± 32.92kg, 6.89 ± 0.07kg, 316.54 ± 3.31days, 33.56 ± 0.63months, 42.78 ± 0.63months and, 469.01 ± 7.03days, respectively. Additive genetic effects were much larger than the non-significant negative value of heterosis effect of lactation milk yield (3728 ± 139.39 kg of additive and -81.65 ± 97.98 kg of heterosis). The cross-breeds were -21.51± 29.19 days, -2.29 ± 3.12 months, and -2.23 ± 3.12 months, reduced for CI, AFS and, AFC due to the additive effect of the Friesian gene. Estimations of heritability for productive traits (LMY, DMY, and LL) were 0.180 ± 1.00, 0.235 ± 0.053 and 0.219 ± 0.077, respectively, and reproductive traits (AFS, AFC, and CI) 0.0798 ±0.034, 0.080 ±0.033and 0.180 ± 0.042, in respective order. The current result indicated that repeatability values of productive traits 0.589 ± 1.00 for LMY, 0.491± 0.227 for DMY, 0.735± 0.151 for LL, and0.23±0.01 for CI. The current study indicated that the direct genetic correlation between productive traits was positive and ranged from very weak (0.141 ± 0.073) to very strong (0.854 ± 0.304) genetic correlations. From the current study, a high correlation was observed between LMY and LL (0.854 ± 0.304). The current study indicated that positive genetic correlation ranged from very weak to weak genetic correlation among reproductive traits. AFS-AFC (0.228 ± 0.172), AFS-CI (0.181 ± 0.194), and AFC-CI (0.063 ± 0.02). The present study indicated that the genetic correlation between productive and reproductive traits was closely related with each other in some traits. Strong genetic correlation looked 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. Thus, based on the study's findings, it was feasible to draw the conclusion that proper parental line selection and crossing should be used to create next-generation calves and improve the farm's overall management system.

Research topics

  • Genetic and phenotypic traits in livestock
  • Milk Quality and Mastitis in Dairy Cows
  • Effects of Environmental Stressors on Livestock

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.21203/rs.3.rs-8744363/v1

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.