Estimation of genetic trend of resilience indicators Rauto and Skewness over 37 years in Caracu heifers

Abstract

The aime of this study was to evaluate the genetic trend of the resilience indicators first-order autocorrelation of the residuals (r_auto) and skewness in Caracu (Bos taurus taurus) heifers. Data from 999 Caracu heifers born between 1982 and 2019, from the herd selected for post-weaning weight at the Instituto de Zootecnia (São Paulo, Brazil), were used. Indicators, r_auto and skewness, were obtained from the residuals of observed and predicted weights recorded from birth to 18 months, with predictions based on repeated measures linear model. Estimated breeding values (EBVs) for both traits were obtained via Bayesian inference using a single-trait animal model, with contemporary group (year and month of birth) as a fixed effect and additive genetic, as random effect. The pedigree matrix included 1,368 animals. Genetics trends were assessed by regressing EBVs on year of birth using SAS. Additionally, phenotypic and genetic means from two periods (1982-1985 and 2016-2019) were compared using the t-test. The regression coefficient ± standard error for r_auto was 0.00001699 ± 0.00003081 and for skewness was 0.00011953 ± 0.00005013, indicating no significant genetic trend over time for r_auto and a light improvement for skewness (p = 0.0173). The differences between periods were significant (p ≤ 0.05) for phenotypic r_auto -0.1175 ± 0.2813 (difference ± standard deviation) and not significant for genetic r_auto (0.000890 ± 0.00880), and phenotypic and genetic skewness (0.0694 ± 0.5526; -0.00371 ± 0.0173). These results suggest that selection for post-weaning weight did not compromise the recovery capacity of Caracu heifers. The stability and light differences of the indicators over time may reflect the adaptability of the breed to tropical climates. Further research on this breed is necessary to deepen the understanding of how resilience interacts with productive and reproductive traits in the context of genetic improvement programs.