Models to predict live weight from heart girth in crossbred beef heifers

The objective of this study was to develop and evaluate linear, quadratic, and exponential mathematical models to predict live weight (LW) from heart girth (HG) in crossbred heifers raised in tropical humid conditions in Mexico. Live weight (363.32 ± 150.88 kg) and HG (166.83 ± 24.88 cm) were measur...

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Published in:Tropical animal health and production 2022-10, Vol.54 (5), p.275-275, Article 275
Main Authors: Chico-Alcudia, Denis R., Portillo-Salgado, Rodrigo, Camacho-Pérez, Enrique, Peralta-Torres, Jorge A., Angeles-Hernandez, Juan C., Muñoz-Benitez, Alfonso L., Lendechy, Víctor Hugo Severino, Gurgel, Antonio Leandro Chaves, dos Santos Difante, Gelson, Ítavo, Luís Carlos Vinhas, Chay-Canul, Alfonso J.
Format: Article
Language:English
Subjects:
Animals
Bayesian analysis
Beef
Biomedical and Life Sciences
Biometrics
Cattle
Correlation coefficient
Correlation coefficients
Criteria
Farms
Goodness of fit
Heart
Life Sciences
Livestock
Mathematical models
Performance prediction
Prediction models
Regular Articles
Root-mean-square errors
Veterinary Medicine/Veterinary Science
Weight
Zoology
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creator Chico-Alcudia, Denis R.
Portillo-Salgado, Rodrigo
Camacho-Pérez, Enrique
Peralta-Torres, Jorge A.
Angeles-Hernandez, Juan C.
Muñoz-Benitez, Alfonso L.
Lendechy, Víctor Hugo Severino
Gurgel, Antonio Leandro Chaves
dos Santos Difante, Gelson
Ítavo, Luís Carlos Vinhas
Chay-Canul, Alfonso J.
description The objective of this study was to develop and evaluate linear, quadratic, and exponential mathematical models to predict live weight (LW) from heart girth (HG) in crossbred heifers raised in tropical humid conditions in Mexico. Live weight (363.32 ± 150.88 kg) and HG (166.83 ± 24.88 cm) were measured in 400 heifers aged between 3 and 24 months. Linear and non-linear regression was used to construct the prediction models. The goodness of fit of the models was evaluated using the Akaike information criterion (AIC), the Bayesian information criterion (BIC), coefficient of determination ( R 2 ), mean squared error (MSE), and root MSE (RMSE). In addition, the developed models were evaluated through internal and external cross-validation ( k -folds) using independent data. The ability of the fitted models to predict the observed values was evaluated based on the root mean square error of prediction (RMSEP), R 2 , and mean absolute error (MAE). The correlation coefficient between LW and HG was r  = 0.98 ( P  
doi_str_mv 10.1007/s11250-022-03276-7
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Additionally, this model exhibited better goodness-of-fit values regarding external and internal validation criteria (higher R 2 and lower RMSEP and MAE), thus having better predictive performance. The RMSE represented about 8% of the observed LW. Heart girth is highly correlated ( r  = 0.98) with LW. 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subjects Animals
Bayesian analysis
Beef
Biomedical and Life Sciences
Biometrics
Cattle
Correlation coefficient
Correlation coefficients
Criteria
Farms
Goodness of fit
Heart
Life Sciences
Livestock
Mathematical models
Performance prediction
Prediction models
Regular Articles
Root-mean-square errors
Veterinary Medicine/Veterinary Science
Weight
Zoology
title Models to predict live weight from heart girth in crossbred beef heifers
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