Genetic and Environmental Factors Affecting Pregnancy Loss in Nellore Cattle: Insights from a Large-Scale Brazilian Field Database1

Pregnancy loss (PL) is a major constraint on reproductive efficiency in beef cattle, yet its genetic basis remains poorly understood. This study aimed to estimate genetic parameters for PL and to quantify sire-related variation in Nellore cattle managed under Fixed-Time Artificial Insemination (FTAI). Records from 305,325 FTAI services involving 667 Nellore sires, collected across 271 farms in Brazil between 2015 and 2022, were analyzed. Pregnancy loss was modeled as a binary trait using a Bayesian threshold sire model, assuming an underlying continuous liability. Fixed effects included contemporary group, dam category, body condition score, and cow age at pregnancy diagnosis, and sire effects were modeled as random. Variance components and sire effects were estimated via Markov Chain Monte Carlo sampling implemented in the BLUPF90+ software suite, and the accuracy of sire evaluations was computed following Beef Improvement Federation (BIF) guidelines based on prediction error variance. Pregnancy loss exhibited low heritability on the liability scale (h2 = 0.031; 95% HPD: 0.019-0.042), indicating that most of the variation is driven by environmental factors, and meaningful variation among sires was detected. Pregnancy loss rates averaged 6.64% in multiparous cows, 8.28% in primiparous cows, and up to 12.35% in precocious heifers. Approximately 15% of sires achieved BIF accuracy values of 0.24 or greater, and contrasts between the top and bottom deciles of sires were associated with a 31% increase in PL among precocious heifers. Pregnancy loss was also strongly influenced by age and dam category, with higher rates observed in younger females, particularly precocious heifers, and declining with increasing age and parity. Overall, these results demonstrate that, although PL has low heritability, exploitable genetic variation among sires exists when supported by large, well-structured FTAI datasets. Integrating PL indicators into multi-trait selection indices with targeted nutritional and reproductive management offers a practical strategy to improve reproductive efficiency in beef cattle production systems.