Development and evaluation of equations to predict body weight of Pelibuey ewes using heart girth

Abstract

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 (r 2 = 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 (R 2 =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.

Comparison of mathematical models to estimate live weight through heart girth in growing Pelibuey sheep

“…In sheep production systems in tropical regions of Latin America, native breeds are used, mainly hair sheep for meat, such as Pelibuey, Black Belly, Katahdin, and Santa Inês (Chay-Canul et al, 2016). In Mexico, the most widely used maternal breed for sheep rearing is the Pelibuey (Chay-Canul et al, 2016;2019a). These systems are characterized by minimal use of inputs, low or no application of modern technologies, and poor adoption techniques (Alexandre et al, 2021).…”

“…These systems are characterized by minimal use of inputs, low or no application of modern technologies, and poor adoption techniques (Alexandre et al, 2021). Under these conditions, the constant evaluation of the animals' growth poses a major challenge for small producers, more so for the measurement of live weight (LW), due to the high cost of direct measurement equipment, such as livestock scales (Chay-Canul et al, 2019a;Canul-Solis et al, 2020;Sabbioni et al, 2020).…”

ASAS-NANP SYMPOSIUM: Applications of machine learning for livestock body weight prediction from digital images

“…Some of the most popular morphometric measurements include heart girth circumference, wither height, hip width/height, and body length. These measurements are manually selected and used as features for traditional regression models, which result in predictive equations with one or more variables based on the number of selected measurements in various species, such as cattle ( Heinrichs et al, 1992 ; Franco et al, 2017 ; Goopy et al, 2018 ), pigs ( Groesbeck et al, 2002 ; Mutua et al, 2011 ; Sungirai et al, 2014 ; Al Ard Khanji et al, 2018 ), sheep ( Sowande and Sobola, 2008 ; Kunene et al, 2009 ; Chay-Canul et al, 2019 ; Canul-Solis et al, 2020 ), goats ( Sebolai et al, 2012 ), camels ( Fadlelmoula et al, 2020 ; Meghelli et al, 2020 ), and yaks ( Yan et al, 2019 ).…”

Application of Biometric Traits for Predicting Weaning Weight of Dorper Sheep using Path Analysis

“…Farmers depend on physical estimation of the animal weaning weight (may result in incorrect weight estimate) for purposes such as marketing, medical dosage, feeding and breeding (Hussain et al 2019). Hence, it is important to practice alternative methods which are easy and of low cost such as using biometric traits which will allow rural farmers to determine weight of their animals to monitor the growth of livestock (Chay-Canul et al 2019). According Mabu et al (2020) path analysis has been used in previous studies to provide more detailed information on the relationships (direct and indirect) between variables.…”