Heart girth-based bodyweight prediction for Sub-Saharan African ruminants: updated equations by species, breed, and...

Accurate prediction of bodyweight (BW) from measurable animal characteristics serves many practical purposes for livestock farmers in sub-Saharan Africa, where weighing scales are impractical or infeasible. A volume of literature is devoted to BW estimation using heart girth (HG) (circumference of chest diameter behind front legs) as a main predictor; most published equations apply to animals of specific breeds, ages, or production systems, limiting applicability to livestock populations broadly. Using a large and diverse repeated measurement sample of African bovines (n = 5549; 13,165 measurements) and caprinae (n = 1857; 5707 measurements) we developed prediction equations specific to species, geography, and production system by segmenting regression formulae at the 50th percentile of HG, leading to two segments applicable to growing (bottom 50th) and mature (upper 50th) animals respectively. At the extremes of HG, segmented regression had superior predictive accuracy for bovines in particular, with as much as a 32% reduction in normalized RMSE (nRMSE) relative to unsegmented. This study thus: (i) provides the most comprehensive, genetically and geographically rigorous set of BW prediction equations for African domestic ruminants to-date based on a single predictor (heart girth), and (ii) for bovines, using segmented regression, prediction formulae robust to extremities of BW/HG, yielding comparable or improved prediction accuracy (nRMSE 6-13%) over existing formulae with equal or greater input requirements. As Box-Cox formulae were most accurate but structurally complex, authors propose formula transformations embedded directly on weigh-tapes or charts, maximizing ease-of-use and enabling scalable, low-cost, and accurate BW estimation for African production systems.