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Revista mexicana de ciencias pecuarias

On-line version ISSN 2448-6698Print version ISSN 2007-1124

Abstract

CHAY-CANUL, Alfonso J. et al. Development and evaluation of equations to predict body weight of Pelibuey ewes using heart girth. Rev. mex. de cienc. pecuarias [online]. 2019, vol.10, n.3, pp.767-777. ISSN 2448-6698.  https://doi.org/10.22319/rmcp.v10i3.4911.

The main objective was to develop equations to predict body weight (BW) using heart girth (HG) in Pelibuey ewes. A second objective was to evaluate this model for precision using an independent dataset. For model develop a data set composed by 366, 2-3-yr-old, non-pregnant and non-lactating ewes; with a mean BW of 45.7 ± 9.16 kg and HG of 87.55 ± 7.93 cm was used. A linear equation was fitted: BW= -47.97 (±2.01) + 1.07 (±0.02)×HG (r2 = 0.86, Root mean square error (RMSE)= 3.46, y n= 366). A second data set composed by 67 animals, with similar characteristics (BW of 38.25 ± 8.62 kg and HG of 80.37 ± 7.03 cm) was used to evaluate the developed equations. For the evaluation, the relationship between observed and predicted values of BW by linear regression, the mean squared error of prediction (MSEP) and root MSEP (RMSEP), and concordance correlation coefficient analysis were used. The proposed equation was highly precise (R2 =0.913) and accurate (Cb=0.996) with a reproducibility index of 0.95. The MEF has indicated a higher efficiency of prediction with higher proportion of the total variance of the observed values been explained by the predicted data (0.91). The partition of the MSEP has indicated a very small mean bias (0.082). The systematic bias has shown that only 1.93 % of the error of prediction was associated with the slope and most of the error was explained by the random component indicating small biases with the predictions. The proposed equation accurately and precisely estimated the BW of non-pregnant and non-lactating Pelibuey ewe using HG and therefore is recommended to be used.

Keywords : Biometric measurements; Pelibuey sheep; Body weight; Prediction.

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