Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle

Abstract

We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model.

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

“…The estimates obtained by the REP model were markedly lower for the same group of bulls, corresponding to 0.56 (±0.13), 0.65 (±0.14), and 0.57 (±0.13) for DO, CI and DPR, respectively. These results are in agreement with those obtained in the Portuguese Holstein herd, where the reliabilities for the best 1%, 10%, 50% bulls were higher when accessed from the AR model (Silva, Lopes, et al, 2020). According to Carvalheira et al.…”

“…However, the superiority in the analyses of model‐fitting criterion, the highest EBV reliabilities and the direct impact on the bulls ranking suggest a superiority of the AR model for genetic analyses of longitudinal reproductive traits. In addition, the recent study of Silva, Lopes, et al (2020) reporting the applicability of AR model for genomic evaluation of reproductive traits in Portuguese Holstein cattle supports the indication of the AR model to implement the genetic evaluations of reproductive traits in the Brazilian Holstein cattle.…”

“…The moderate rank correlation in the group of Top 10 bulls indicates a re‐ranking of the best animals between the AR and the REP models. In a similar study, Silva, Lopes, et al (2020) also reported a re‐ranking of bulls when evaluating the AR and REP models for genetic analyses of reproductive traits in Portuguese Holstein cattle. Those authors reported rank correlations between the Top 100 bulls ranging from 0.71 to 0.88 among the evaluated traits.…”

“…Autoregressive models have been successfully used for genetic analyses of milk traits in Holstein cattle, corresponding to higher genetic variance, higher reliabilities, lower residual variance estimates and predictive ability similar to models with more complex structure (Carvalheira et al., 2002; Silva et al., 2019). In addition, Silva, Lopes, et al (2020) reported the feasibility of this methodology for genetic evaluation of reproductive traits in Portuguese Holstein cattle.…”

Autoregressive single‐step model for genomic evaluation of longitudinal reproductive traits in portuguese holstein cattle

“…Analysis of reproductive traits follows the same modelling approach. In a recent study, Silva et al (2020) demonstrated the applicability of the autoregressive model for genetic evaluation of longitudinal reproductive traits in dairy cattle. They reported better results of the AR-Model when compared with the traditional repeatability model, providing better fitting criteria and higher EBV reliabilities.…”