Journal Article

Relationship between body weight and dorsal area in female buffaloes

Cruz-Tamayo, Alvar-Alonzo, Gomez-Vazquez, Authors Armando, Chaves-Gurgel, Antonio-Leandro, Camacho-Perez, Enrique, Chay-Canul, Alfonso-Juventino, Vinhas-Ítavo, Luís-Carlos, Mota-Rojas, Daniel, Dias-Silva, Tairon-Pannunzio, García-Herrera, Ricardo-A, Herrera-Camacho, José

2024

Overview

Background: The body weight (BW) of animals at various growth stages is an important piece of information for the decision-making process. In the current \"livestock 4.0\" or precision livestock farming it becomes necessary to know if body measurements obtained from the dorsal view of an animal are related to its BW. Objective: To evaluate the relationship between BW and dorsal area (DA) of water buffaloes (Bubalus bubalis) reared in southeastern Mexico. Methods: The BW (340 ± 161.68 kg), hip width (HW), thorax width (TW), and body length (BL) were measured in 215 female Murrah buffaloes aged between 3 months and 5 years. The DA (m2) was calculated using the mathematical formulae for the area of a trapezoid, considering HW, TW, and BL in the calculation. The relationship between BW and DA was assessed with correlation and regression models. Results: The correlation coefficient between BW and AD was 0.96 (p<0.001). The linear equation had the highest determination coefficient (R2 = 0.94) along with the lowest mean square error (MSE = 1716.86), root MSE (RMSE = 41.43), Akaike Information Criterion (AIC = 1603.36), and Bayesian Information Criterion (BIC = 1610.10). Conversely, the allometric equation exhibited the highest values of MSE, RMSE, AIC, and BIC. Based on the quality of fit by the k-folds technique, the three proposed equations showed consistent adjustments, with more than 90% accuracy (R2 = 0.92). The quadratic equation exhibited the lowest mean squared prediction error and mean absolute error. Conclusion: The DA can be used as a good predictor of BW in buffaloes, especially when incorporated into first and second-degree linear equations.

• Publisher: Universidad de Antioquía
• Subject: Area / Bayesian analysis / biometric measurements / Body composition / Body length / Body measurements / Body weight / Bubalus bubalis / Bubalusbubalis / bufalo / Buffalo / búfalo / Correlation coefficient / Correlation coefficients / crecimiento / crescimento / Criteria / Decision making / dron / drone / Farming / Females / ganadería 4 / ganadería de precisión / Growth / Linear equations / live weight / Livestock / livestock 4 / Livestock farming / Mathematical models / medidas biométricas / modelos matemáticos / pecuária 4 / pecuária de precisão / peso en pie / peso vivo / Precision agriculture / precision livestock farming / predicción del peso / predição do peso / Quadratic equations / Regression analysis / Regression models / Root-mean-square errors / Trapezoids / unmanned aerial vehicle / vehículo aéreo no tripulado / veículo aéreo não tripulado / weight prediction