Genetics of growth resilience- and uniformity-related indicators derived from sparse body weight data in Angus–Brangus cattle under (sub)tropical conditions

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Abstract Background Resilience is an important breeding objective in livestock, reflecting the capacity of animals to maintain their performance or recover quickly from short-term environmental perturbations. The derivation of resilience indicators requires longitudinal measurements of key traits. In beef cattle, the limited availability of frequently recorded variables restricts the development of resilience-related indicators. This limitation is particularly relevant in (sub)tropical regions of the Southern Hemisphere, where animals are exposed to greater environmental variability and indicators of growth stability could therefore be especially valuable. Therefore, the main objective of this study was to derive resilience- and uniformity-related indicators from sparse body weight records in a Brazilian Angus–Brangus population, estimate their genetic parameters, and assess their associations with other economically relevant traits. Results Six indicators potentially related to growth resilience and uniformity were derived from observed and expected body weight trajectories, representing complementary biological dimensions: area under the curve, mean absolute deviation, logarithm of the mean of squares, logarithm of variance, relative maximum drawdown, and recovery slope index. A cubic quantile regression provided the best fit for reference growth trajectories compared with nonlinear models. All indicators were heritable, with direct and maternal heritability estimates ranging from 0.029 to 0.240 and from 0.024 to 0.071 for logarithm of variance and recovery slope index, respectively. Relative maximum drawdown (0.24) and recovery slope index (0.18) showed the highest heritabilities, while logarithm of the mean of squares (0.039) and logarithm of variance (0.029) had the lowest ones. The additive genetic coefficient of variation was highest for recovery slope index, indicating substantial genetic variability. Genetic and phenotypic correlations formed biologically consistent clusters, with area under the curve–mean absolute deviation and logarithm of the mean of squares–logarithm of variance closely related (> 0.90), and relative maximum drawdown–recovery slope index strongly associated (− 0.93) but distinct from the others. Partial genetic correlations, accounting for average growth potential, were modest but consistently favorable across 16 growth, carcass, adaptation, temperament, and reproduction traits. Mean absolute deviation showed favorable associations with key traits, including pre-weaning gain (− 0.39) and yearling conformation score (− 0.27), as well as with tick count (0.16). In contrast, the recovery slope index showed favorable correlations with pre- and post-weaning gain (0.39 and 0.32), backfat thickness (0.30), and age at first calving (− 0.15). Overall, the recovery slope index combined high heritability, favorable genetic relationships with key traits, and low redundancy with other indicators. Conclusions Resilience- and uniformity-related indicators derived from sparse body-weight records of beef cattle are heritable with substantial additive genetic variance. Recovery slope index and mean absolute deviation are the most promising indicators for breeding applications. Recovery slope index captured variation in growth recovery not represented by other indicators and showed strong potential for improving growth recovery ability, while mean absolute deviation provided a broad and consistent profile of favorable associations with growth, carcass, adaptation, temperament, and reproduction traits. Overall, this study establishes a framework for quantifying resilience- and uniformity-related variation in growth trajectories of Angus–Brangus beef cattle, thereby contributing to productivity and sustainability under challenging environmental conditions.