Predicting body weight in fat-type pigs using morphometric measurements
DOI:
https://doi.org/10.5433/1679-0359.2026v47n1p81Keywords:
Morphometry, Multiple linear regression, Pig production.Abstract
This study aimed to develop predictive equations for body weight (BW) in fat-type (lard-type) pigs raised under extensive or semi-extensive systems, and to determine the most significant morphometric predictors. Data were collected from 240 pigs (122 males and 118 females) on smallholder farms, with BW ranging from 4.7 to 68.0 kg. The following traits were recorded: body weight (BW), carcass length (CL), thoracic circumference (TC), hip circumference (HC), withers height (WH), and hip height (HH). Descriptive statistics (means, standard deviations, coefficients of variation, and maximum values) were calculated separately for each sex. Pearson’s correlation coefficients indicated that all morphometric measurements were strongly correlated with BW (r ≥ 0.90) in both sexes. Data were tested for normality (Cramer–von Mises), and male and female datasets were analyzed separately using stepwise multiple linear regression. The resulting sex-specific equations were compared using an F test, with no differences detected between males and females (P = 0.376) Therefore, a single pooled equation was considered sufficient to explain BW variation in both sexes: BW = -35.51 + 0.80 × CT + 0.11 × CC (R2 = 0.93; P<0.0001). To assess practical applicability, the general equation was validated using CL and TC data from an independent set of 53 pigs (BW = 6.5–42.8 kg) not included in model development. Predicted and observed values were highly correlated (r = 0.96), indicating strong predictive performance. These findings demonstrate that CL and TC are sufficient to accurately predict BW in fat-type pigs, providing a practical tool for small-scale producers who lack access to weighing scales.
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Copyright (c) 2026 Claudia Cristina Paiva Coutinho, Marcos Antonio Delmondes Bomfim, Felipe Barbosa Ribeiro, Daphinne Cardoso Nagib do Nascimento, Yasmim Loiola Franca, Jefferson Costa de Siqueira
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