Using meta-analysis to estimate the genetic parameters of longevity traits in dairy cows

Document Type : Research Paper

Authors

1 Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan ,Iran.

2 Department of Animal Science, College of Agriculture ‎and Natural Resources, University of Tehran, Karaj, Iran.

3 College of Agriculture, Isfahan University of Technology, Isfahan, Iran.

Abstract

Designing effective breeding programs for dairy cattle relies on accurate estimates of genetic parameters for economically important traits. Extensive research over the years has explored genetic parameters associated with longevity in dairy cows. However, these estimates often come from studies using different cow populations, leading to significant variations in heritability and genetic correlations. Thus, this study aimed to conduct a meta-analysis based on a random-effects model to combine different published heritability estimates for longevity traits as well as their genetic correlations with milk production traits, type traits, days open (DO), and somatic cell score (SCS) in dairy cows. In total, 66 articles published between 1994 and 2023 were used in the present study. After gathering the articles and extracting the parameters, genetic parameters were estimated by meta-analysis method. pooled heritabilities for the productive life (PL), herd life (HL), Number of Lactation (NL), Stayability(ST), and Survival rate(SR) traits were 0.10, 0.08, 0.07, 0.10, and 0.04, respectively. Genetic correlations between most type and longevity traits were generally negative and low. The highest positive genetic correlation was found between the subjective score for type and ST (0.62). Genetic correlations between longevity (ST and SR) and SCS were -0.13 and -0.38, respectively. Genetic correlations between longevity (PL and HL) and DO were -0.54 and 0.40, respectively. Obtained results in the study can be useful to define animal breeding strategies to improve longevity in dairy cattle

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Articles in Press, Accepted Manuscript
Available Online from 10 July 2024
  • Receive Date: 28 January 2024
  • Revise Date: 02 June 2024
  • Accept Date: 10 June 2024