Relationship between body weight and dorsal area in female buffaloes

Author:

,Gomez-Vazquez ArmandoORCID,Cruz-Tamayo Alvar-AlonzoORCID, ,Camacho-Perez EnriqueORCID, ,Chaves-Gurgel Antonio-LeandroORCID, ,Herrera-Camacho JoséORCID, ,Mota-Rojas DanielORCID, ,García-Herrera Ricardo-AORCID, ,Vinhas-Ítavo Luís-CarlosORCID, ,Dias-Silva Tairon-PannunzioORCID, ,Chay-Canul Alfonso-JuventinoORCID,

Abstract

Background: Body weight (BW) has been reported as important information in the decision-making process; therefore, it is necessary to determine if body measurements obtained from the dorsal view of the animal are related to BW, considering that we are currently living in the era of the so-called "livestock 4.0". Objective: The objective of the present study was to evaluate the relationship between BW and dorsal area (DA) in water buffaloes (Bubalus bubalis) reared in southeastern Mexico. Methods: The BW (340 ± 161.68 kg), hip width (BW), 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 calculating the area of a trapezoid, considering the HW, TW, and BL in the calculation. The relationship between BW and DA was assessed using correlation and regression models. Results: The correlation coefficient between BW and AD was 0.96 (P<0.001). The linear equation demonstrates the highest determination coefficient value (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 exhibits the highest values of MSE, RMSE, AIC, and BIC. The quality of fit using the k-folds technique allowed us to identify that the three proposed equations showed consistent adjustments, with an accuracy above 90% (R2 = 0.92). Among them, the quadratic equation exhibited lower values of mean squared prediction error and mean absolute error. Conclusions: The DA can be a good predictor of BW in buffaloes, especially when incorporated into first and second-degree linear equations.

Publisher

Universidad de Antioquia

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