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Prediction of body weight of Brown Alpine goats by measuring body volume

Authors :
N.M. Oliveira
A.L.C. Gurgel
I. Fonseca
J.F. Lopes
G.S. Difante
L.C.V. Ítavo
M.J. Araújo
T.P. Dias-Silva
A.A. Carvalho
A.J. Chay-Canul
Source :
Arquivo Brasileiro de Medicina Veterinária e Zootecnia, Vol 76, Iss 4 (2024)
Publication Year :
2024
Publisher :
Universidade Federal de Minas Gerais, 2024.

Abstract

ABSTRACT The objective was to estimate the body weight (BW) of Brown Alpine goats by means of body volume (BV) measurements. We used 132 pieces of information with measurements of BW, body length (BL) and thoracic perimeter (TP) from 22 goats evaluated fortnightly, between March and May 2023. Based on this information, the BV of the animals was calculated. Three mathematical models were evaluated - a linear model, a quadratic model, and an exponential model - with the measurement of BV. The goodness of fit of the equations was evaluated using the coefficient of determination (R2), mean square error (MSE) and root of the MSE (RMSE). The predictive ability of the models was evaluated by k-fold cross-validation (k = 10). A high positive correlation between BW and TP (r = 0.95) and BL (r = 0.94) was observed. The correlation between BW and BV was higher than the other correlations (r = 0.98). The linear model showed the lowest values of MSE (9.49) and RMSE (3.08). In the cross-validation, the linear and quadratic models presented estimates of the mean BW and the standard deviation of this weight similar to the real data, and high R2 values (0.95) of the data predicted by the observed ones. The analysis of the coefficient of correlation and concordance (CCC) also showed that these models have accuracy and precision (CCC > 0.95). Thus, the linear and quadratic models estimate the body weight of Brown Alpine goats with precision and accuracy.

Details

Language :
English, Portuguese
ISSN :
16784162
Volume :
76
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Arquivo Brasileiro de Medicina Veterinária e Zootecnia
Publication Type :
Academic Journal
Accession number :
edsdoj.7c2660a159ce4de3aee4a31672c8e700
Document Type :
article
Full Text :
https://doi.org/10.1590/1678-4162-13170