Bayesian Estimation of Heritability, Repeatability, and Genetic Correlations in Crossbred Jersey Cattle

Abstract

In animal breeding programs, estimating genetic parameters such as heritability, repeatability, and genetic correlation is crucial for assessing breeding value, forecasting genetic progress in selection programs, and improving breeding strategies. Since both populations and environments evolve over time, genetic parameters must be updated frequently. In this study, the genetic parameters of economically significant traits in crossbred Jersey cattle were evaluated using univariate and multi-trait repeatability animal models with a Bayesian approach. The posterior mean of Heritability estimates for lactation milk yield, lactation length, calving interval, dry period, services per conception, and service period were 0.43±0.21, 0.26±0.20, 0.18±0.15, 0.23±0.17, 0.13±0.10, and 0.17±0.13 respectively and estimates of repeatability for the corresponding traits were 0.75±0.11, 0.53±0.17, 0.32±0.17, 0.41±0.17, 0.23±0.10, and 0.31±0.13. Moderate heritability values for lactation milk yield and lactation length suggest that there is sufficient additive genetic variability to achieve genetic improvement through selection. The moderate repeatability estimates for traits such as lactation milk yield, lactation length, and calving interval indicate the potential for early evaluation of crossbred cattle for selection purposes. Negative genetic correlations were found between productive traits (such as lactation milk yield and lactation length) and reproductive traits (such as services per conception), with values ranging from 0.17 to 0.26. Additionally, strong negative genetic correlations were observed between lactation milk yield, lactation length, and dry period. These findings highlight the importance of giving attention to reproductive traits when selecting high-yielding crossbred Jersey dairy cattle, as the negative correlation suggests that an increase in production may adversely affect reproductive performance.