Prediction of live weight in beef heifers using a body volume formula

IF 0.4 4区农林科学 Q4 VETERINARY SCIENCES

Arquivo Brasileiro De Medicina Veterinaria E Zootecnia Pub Date : 2022-12-01 DOI:10.1590/1678-4162-12886

L. Castillo-Sanchez, J. Canul-Solís, D. Pozo-Leyva, E. Camacho-Pérez, J.M. Lugo-Quintal, A. Chaves-Gurgel, G. T. Santos, L. Ítavo, A. Chay-Canul

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引用次数: 2

Abstract

ABSTRACT The objective of this study was to develop and evaluate linear, quadratic, and allometric models to predict live weight (LW) using the body volume formula (BV) in crossbred heifers raised in southeastern Mexico. The LW (426.25±117.49kg) and BV (338.05±95.38 dm3) were measured in 360 heifers aged between 3 and 30 months. Linear and non-linear regression were used to construct prediction models. The goodness-of-fit of the models was evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), coefficient of determination (R2), mean squared error (MSE), and root MSE (RMSE). In addition, the developed models were evaluated through cross-validation (k-folds). The ability of the fitted models to predict the observed values was evaluated based on the RMSEP, R2, and mean absolute error (MAE). The quadratic model had the lowest values of AIC (2688.39) and BIC (2700.05). On the other hand, the linear model showed the lowest values of MSE (7954.74) and RMSE (89.19), and the highest values of AIC (2709.70) and BIC (2717.51). Despite this, all models presented the same R2 value (0.87). The cross-validation (k-folds) evaluation of fit showed that the quadratic model had better values of MSEP (41.49), R2 (0.85), and MAE (31.95). We recommend the quadratic model to predictive of the crossbred beef heifers' live weight using the body volume as the predictor.

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用体体积公式预测肉用小母牛的活重

摘要本研究的目的是建立和评估线性、二次和异速生长模型，利用体体积公式(BV)预测墨西哥东南部杂交小母牛的活重(LW)。测定360头3 ~ 30月龄母牛的体重(426.25±117.49kg)和体重(338.05±95.38 dm3)。采用线性和非线性回归构建预测模型。采用赤池信息准则(AIC)、贝叶斯信息准则(BIC)、决定系数(R2)、均方误差(MSE)和均方根误差(RMSE)评价模型的拟合优度。此外，开发的模型通过交叉验证(k-fold)进行评估。根据RMSEP、R2和平均绝对误差(MAE)评估拟合模型预测观测值的能力。二次型模型AIC(2688.39)和BIC(2700.05)最低。另一方面，线性模型显示MSE(7954.74)和RMSE(89.19)的最低值，AIC(2709.70)和BIC(2717.51)的最高值。尽管如此，所有模型的R2值相同(0.87)。交叉验证(k-fold)拟合评价显示，二次模型的MSEP(41.49)、R2(0.85)、MAE(31.95)值较优。建议采用二次元模型以体体积为预测指标预测杂交肉牛的活重。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Arquivo Brasileiro De Medicina Veterinaria E Zootecnia 农林科学-兽医学

CiteScore

0.80

自引率

25.00%

发文量

111

审稿时长

9-18 weeks

期刊介绍： Publica artigos originais de pesquisa sobre temas de medicina veterinária, zootecnia, tecnologia e inspeção de produtos de origem animal e áreas afins relacionadas com a produção animal. Atualmente a revista mantém 628 permutas (419 internacionais e 209 nacionais), sendo um verdadeiro suporte para o recebimento de periódicos pela Biblioteca da Escola. A partir de 1999, a Escola de Veterinária delegou à FEP MVZ Editora o encargo do gerenciamento e edição de todas suas publicações, inclusive do Arquivo, ficando somente com o apoio logístico (instalações, equipamentos, pessoal etc.). O apoio financeiro é exercido pelo CNPq/FINEP e pela própria FEP MVZ.