Influence of maternal age-class and prediction of body weight from morphometric traits in indigenous small ruminant genotypes

This study investigated the relationship between body weight (BWT) and selected morphometric traits in young (2-year-old) and mature (4-year-old) females of indigenous Sabi sheep and Matebele goats. The aim was to identify the most reliable and biologically informative predictors of BWT for use in smallholder production systems. A cross-sectional observational design was applied to 60 Matebele goats and 53 Sabi sheep selected through purposive sampling of non-pregnant, non-lactating females exhibiting optimal body condition. Morphometric measurements included heart girth (HG), withers height (WH), body length (BL), and rump height (RH). Data were analyzed using descriptive statistics, Pearson’s correlation, stepwise regression, and path analysis to evaluate predictive accuracy and structural relationships between traits. Phenotypic correlations between BWT and morphometric traits were stronger in mature than in young females across both species. In young Matebele does, RH emerged as the best single predictor of BWT (R² = 0.71), whereas in young Sabi ewes, a combined model of HG and RH offered the greatest predictive accuracy (R² = 0.66). For mature Matebele does, HG and RH jointly accounted for most of the variation in BWT (R² = 0.69), while in mature Sabi ewes, HG alone was the most reliable predictor (R² = 0.53). Inclusion of additional morphometric traits yielded only marginal improvements in prediction models. Path analysis further showed that HG exerted the strongest direct effect on BWT, particularly among mature female sheep, highlighting age-dependent structural influences. Heart girth consistently emerged as the most stable and biologically meaningful predictor of body weight across age groups and species. These findings support the practical use of HG-based prediction models for estimating BWT in indigenous small ruminants, particularly in resource-limited smallholder production systems.