Estimation of productive efficiency in ewes from the natural grasslands of Southern Brazil: A pilot approach

This pilot study quantified the proportion of ewes classified as Efficient, Inefficient, Productive, and Unproductive, using the data collected from an entire production cycle during 2024, provided by a sheep farm. For classification, two models were employed: a generalized linear model (GLM) using four body condition scores (BSCs) evaluations as explanatory variables, and a Bayesian mixed model (BMM) with four repeated measurements. The GLM results classified 8.82 % of ewes as Efficient, 7.84 % as Inefficient, 42.16 % as Productive, and 41.18 % as Unproductive. Conversely, the BMM categorized 19.61 % as Efficient, 4.90 % as Inefficient, 31.37 % as Productive, and 44.12 % as Unproductive. This study provides initial insights into productive efficiency indicators used in ewes, suggesting that further research over extended periods, preferably with the same animals, is required for achieving more conclusive results. Nevertheless, this approach presents a replicable evaluation model applicable to diverse scales and environments. In conclusion, GLM model proved superior in identifying ewes with favorable combinations of BSCs, coefficients of variation, and total weight of lambs at weaning.

Keywords:
ewe classification; body condition score; productive efficiency indicators; generalized linear model; Bayesian mixed model